The High Cost of Duplicating Post Flight Data Centers

The High Cost of Duplicating Post Flight Data Centers

Author: Dr. Stephen R. Vickers

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Copyright © 2017 Published by Lulu Press, Inc.

Raleigh, North Carolina

ISBN: 978-1-365-92733-1

Edition 1 Revision 4 Published 2017

All rights reserved. No part of this publication may be reproduced, stored in a retrieval system, or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the author.

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Dedication

This book could not be possible without the continual support from loving wife Janet. Janet’s encouragement to press forward when I raised thoughts of putting aside all educational pursuits help drive this research to completion. This book is dedicated to Janet.

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Acknowledgments

Dr. Caroline Howard and Dr. Jeffery Stevens steered my journey during this research. Each has my gratitude as they spent many hours examining the accuracy of my research. My acknowledgment to the many flight test engineers who donated their time to filling out questionnaires and conceded to interviews. A special thanks to my loving wife Janet who encouraged me throughout these past years to complete my research

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Preface

Non-aerospace companies have always distributed their data centers or centralized their data centers based on the current technology to maximize their profits. Aerospace companies on the other hand started from the beginning of the first flight by the Wright Brothers to the present to collect and analyze all flight data in a central location.

To determine the thesis for my Doctorate I visualized all the duplication of post-flight data processing at each flight test site. The cost of continual hiring, laying off, system purchase and replacement, system administration schooling, management, operational personnel, at each site. The continued duplication and not centralizing using present technology, as other companies, appeared to be a very high cost.

Today post flight data systems fall into the redundant category. These systems are continually developed for each flight test program with some programs developing more than one data system in different geographical locations.

This book was written based on the doctorate dissertation “Examining the Duplication of Flight Test Data Center ©” of this author which studied the cost of post-flight data system duplication. The research was performed from 2008 to 2011 and is applicable today.

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About the Author

[email protected]

Dr. Vickers worked in the field of flight test telemetry for over 30 years. Programs worked on were the Fairchild A10, Boeing B1 Bomber, ASAT (Anti-Satellite), JPL Ozone Satellite, Army Helicopter, F22 and F35 Fighter, Titan, Taiwan Air Force Processing System, Viking Spacecraft, Mercury Spacecraft, Utah Proving Ground Systems, and many others.

Dr. Vickers has project engineered and managed telemetry systems plus called upon to correct system problems uncorrectable by other project engineers. He developed and taught telemetry courses nationally and internationally the standards of telemetry, telemetry systems, and telemetry hardware design and operation.

Dr. Vickers holds a BSEE, BSIT, Masters in Information Systems, and Doctor of Computer Science from Colorado Technical University in Colorado Springs, Colorado.

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Table of Contents

CHAPTER 1: INTRODUCTION

Introduction to the ChapterOverview 1Significance of the problem 1Clarification 2

Background of the StudyBackground 5Technological beginning 7First test phase 8

Statement of the ProblemBudget considerations 10Presence of stress 10Enterprise solution 13Research questions 14Sampling stress 14Limitations and assumptions 15Hypotheses 16Research 17Purpose of the study 18Objectives of the study 18

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CHAPTER 2: LITERATURE REVIEW

IntroductionChapter organization 20Sources of literature 22Conceptual map 23Background of convention 25

Theories Affecting Data Center DuplicationResearch on data center cost 31Research on relocation stress to employees 33Research on employee relocation affecting employers 35

Data Center Consolidation TheoriesMerging data centers 37Telemetry network theory for data center consolidation 40Time synchronization theory of data center networks 42

Data Center Collaboration TheoryImportance of communication 43

Existing Technology Supporting ConsolidationTelepresence theories 45Virtual data center theories 46Centralized data storage 48Enterprise methods of consolidation 49

Summary 52

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CHAPTER 3: METHODOLOGY

Classification 54Research design 55Data collection plan 56Sampling strategy 57Instrumentation 59Critique of the design 60Testing 61Variables 62Validation 68Target population 70Testing conditions 70Data analysis 71Summary 73

CHAPTER 4: RESULTS

IntroductionStatement of the problem 75Overview of the chapter 76

Literature Review ResultsFlight test data center duplication 76Development expenses resulting from duplication 78Expenses due to relocation caused by duplication 79Enterprise consolidation 82

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Data CollectionCollecting developing costs 83Collecting relocation stress levels 88

Research ResultsRelocation 90Stress measurements 92Limitations affecting the findings 99

Analysis of the Research QuestionsRQ1: Discussion 100RQ2: Discussion 100RQ3: Discussion 101

Summary of Findings 101

CHAPTER 5: SUMMARY

Statement of the ProblemPresenting the problem 103Purpose of the study 105

Analysis of the MethodologyDesigns employed 106Research methods 107

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Analysis of the Research LimitationsDevelopment costs 108Relocation stress 109Unanticipated findings 110

Analysis of ResultsRedundant costs 111Relocation stress 113

Relationship to Previous ResearchConsolidation of data centers 114Employee relocation stress 115

Analysis of the HypothesesHypothesis 1 (H1) 117

Discussion 117Conclusion 117

Hypothesis 2 (H2) 118Discussion 118Conclusion 118



Discussions and Future ResearchPresent model 121Proposed model 124Future research 127

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ATTACHMENTS 129REFERENCES 137DEFINITION OF TERMS 147

List of Tables 150List of Figures 151List of Attachments 151

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CHAPTER 1: INTRODUCTION

Introduction to the Chapter

Overview

Each new military aircraft development contract awarded results in one or more sites created to flight test the aircraft. This research examined the effects of developing a post-flight data center (PFP) at each test flight location and proposes a method to consolidate these data centers to lessen the effects. The background of this duplication is presented to establish a reason the duplication has become a conventional method of development which continues today.

Some engineers have embraces this convention of duplication while others have not. Opposing theories were recorded by Strock and Weaver and mentioned in Chapter 2. One major effect of duplication is the redundant cost of data center development. Another major effect is the cost to employer’s due to engineer relocation stress when engineers are moved from one geographical location to the test site only to relocate to another flight test program site once the emphasis on the program diminishes.and development cost.

Significance of the problem

Aircraft test flight data processing began with on-site data analysis from the very first aircraft design. Initially data was gathered from the pilot and engineer notes examined after each

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flight at the test site. This method of local data processing remained the same throughout the years of aircraft development. As technology produced the first and then faster computer the method of locally analyzing the flight data continued.

Technology today has advanced the speed and data sharing of information over vast distances. This advancement in technology has produced no change in the methodology of data center duplication. Software and hardware development duplication makes each data center to absorb millions of dollars out of each flight test program.

Adding to the effects of duplication are the constant moving of flight test engineers (FTE) to each test flight program location to support initial test and development of the aircraft.

After this first phase of flight test points has been achieved the FTE are moved to other projects to continue the cycle. The problem therefore is the effects relating to costs of developing dedicated flight test data centers for each aircraft test program.

Clarification

Data processing in respect to flight testing of aircraft is a specialized field. This field is different when compared to enterprise data processing. Enterprise data processing is concerned with the data representing people, places, things, and dollar amounts. All which can be processed by one data center.

Flight testing requires data to represent measurements of aircraft parts and functions. These types of measurements use signal analysis and other software utilities to examine the

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measurement. While enterprises can use one data center a flight test site can contain multiple data centers for varying levels of security classifications. Figure 1-1 represents the differences between enterprise and flight test data centers.

Data Type Data Center Customer

PublicPeople,

places, things, dollars

Aircraft Measuremen

ts

Enterprises

Flight Test

Security Level 1

Processing

Security Level 2

Processing

Security Level 3

Processing

Security Level 1

Processing

Flight Test Engineers

Enterprise and Flight Test Data Center DifferencesFigure 1 – 1

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Flight test data centers are dissimilar to enterprise data centers in methods of security level. Flight test data centers can be under strict government security regulations to avoid foreign interest from attaining high technology secrets. Enterprise security is concerned with keeping private the data of customers and preventing competitors from attaining company proprietary information.

Flight test data centers can be one of two different types; real-time or post-flight. This research is concerned with the post-flight and should not be concerned with the real-time data center. Real-time data centers capture a portion of the aircraft measurements transmitted directly from the aircraft. The importance of a real-time data center is due to flight safety.

Engineers look at the measurements in a real-time environment to determine the characteristics of the aircraft and make decisions to safely return the aircraft. These decisions are based on safety of flight to prevent destruction of the aircraft and loss of the pilot. The post-flight data center processes the data after the aircraft has landed. All measurements are stored on removal media in the aircraft and brought into the post-flight data center for processing. These measurements are available to flight test engineers (FTE) for analysis for years after the flight test.

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Users of both types of data centers are the FTE many who are moved from another geographical location to support the flight test program. The number of FTE is in the hundreds at the beginning of the flight test program and can be reduced in head count into the 20’s when the emphasis on the program reduces. This study exams the effects only to the post-flight data center, hereafter referred to as a data center. Figure 1-2 depicts the data center development methodology.

Background of the Study

Background

Data analysis at the site of the flight test program was practiced by the Wright brothers with hand written notes containing flight performance information studied after the test flight. This method of data analysis was the first form of post-flight data processing. Lack of technology prevented real time analysis during aircraft flight.

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New aircraft contract awarded

Develop real time data

center

Relocate FTE to support

Develop postflight

classified data center

Develop post flight

unclassified data center

Data Center Development MethodologyFigure 1 -2

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After World War II the United States Defense Department approached EMR Inc. to design a frequency modulated method of remotely measuring aircraft data. The design was completed and EMR constructed a telemetry station at the site of an aircraft test program. Telemetry allowed analyzing flight data from a remote location during aircraft flight and was a means to eliminate dependence on pilot notes. The new technology of telemetry was not immediately popular due to lack of technical documentation and aircraft companies continued to rely on pilot inscribed notes of flight characteristics into the 1950’s.

Technological beginning

As documentation on the technology of telemetry started to increase the aircraft companies slowly changed their method of flight test data collection. Telemetry technology slowly increased after World War II moving designs of data processing from frequency modulation to pulse coded modulation, which is a form of digitally recording the aircraft performance measurements.

Mainframe computers contributed to the changing telemetry field increasing the power and speed of processing the aircraft measurements. Network technology merged with the telemetry technology and none of these technological advances could assist

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in consolidating the data centers as the technology could not support high speed network data communication. The convention of developing on site data centers therefore continued.

Today technology does exist to allow consolidation of data centers using high bandwidth private wide area networks, virtual systems, and common databases, although literature within the flight test community does not examined the need for such technology. Core software applications are available today to develop an attempt to place commonality among the data centers, but this attempt continues to use data centers at each flight test program site.

First test phase

Contracts awarded by the U.S. Government to develop aircraft contain specifications as to performance expected when the aircraft is produced. These specifications are closely monitored by the government during phases of the aircraft testing. The Engineering, Manufacturing and Development program (EMD), although this terminology changes per program, is the first phase of testing and highly political as the aircraft must meet performance test points to keep Congress allocating the program funds.

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The importance of EMD forces the aircraft company to relocate FTE from other programs so flight data from the data center supporting EMD can be analyzed. After an EMD period of three to five years the amount of FTE is reduced.

The Chief Engineer for a major aircraft test program indicated the engineering level during the EMD was 200 FTE. After EMD the Chief Engineer placed the number of FTE at 20 which is only one tenth of the original number of FTE, see Figure 1-3. This begins another period of relocation for the 90 percent of FTE and his/her family to another test program or in some cases the FTE accepts employment with another aircraft company.

Number of Progam Years (Horizonal)Flight Test Engineer Levels (Vertical)

Figure 1-3

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Statement of the Problem

Budget considerations

One study within this research was the duplication of data centers and cost of development. Software development of the applications to process this aircraft’s data, man hours of development both regular and overtime, and third-party upgrades contributed to consuming a higher amount of the flight test program budget.

System development life cycle consisted of hardware replacement and new software versions of the operating system years later added to the cost. This cost was for an unclassified data center. A second data center was developed at similar costs for classified data. The example given was for only one test site.

Repeating the development cycle and costs Lockheed as an example has developed numerous other data centers to support flight test throughout the United States. Figure 1-4 is an example of Lockheed aircraft test sites. Boeing, Northrop and other aircraft manufactures follow the same convention of data center development

Presence of stress

A form of stress within this research studied the stress levels of FTE reacting to leaving a known environment and suddenly thrust into an unknown environment due to company relocation placing the FTE at the site of a flight test data center. Past researchers have researched this issue on people from different geographical areas and occupations and the research showed a

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detrimental effect on the people and their families as researched by Anderson & Stark (1988) and Manion & Rantz (1995).

These severe effects due to high stress are listed by Anderson and Stark (1988) as depression, health deterioration, and divorce and identified as Relocation Stress Syndrome (RSS). FTE moving from location to location following flight test programs could possibly experience the same effects throughout their flight test career because of high stress.

Research questions were then asked to discover if high stress would explain the reluctance of some FTE to accept relocation offers from their employer increasing the difficulty to staff FTE at remote data centers:

1) Does the FTE experience increased stress by relocating to support a remote flight test data center which can lead to the effects listed by researchers studying relocation stress?2) If these stress levels are high could the stress contribute to loss of employee production based on previous research?

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LMFt Worth

F22 GA

F16EAFB

JSF PAX

C130GA

JSFFW

JSFEAFB

ADCCA

F22EAFB

F16

Lockheed Flight Test Sites (Circa 2015)Figure 1-4

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Enterprise solution

Enterprises have recognized the redundant problem of developing and operating multiple data centers and solved this problem by consolidating the data centers. The financial effects of multiple flight test data centers raise a question if consolidating flight test data centers into one central data center would reduce overhead costs. Research shows the success of enterprises in this effort.

If high stress is shown to be detrimental to FTE and loss of FTE productivity due to relocation then consolidation could open an opportunity for a nucleus FTE group dedicated to a consolidated data center without fear of relocations. Enterprise data center consolidating has differences with flight test data centers which must be noted if the two are compared. Enterprises with separate data centers perform very similar tasks which reduce consolidation problems.

In comparison flight test data centers are developed based on aircraft instrumentation designs which vary from flight test program to flight test program. This complicates consolidation and places more emphasis on higher technology. There is significant population within the flight test community to gather the required data to answer these questions. Referring to Figure 1-1 Lockheed staffs FTE across the United States at many locations.

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Research Questions

This research studied the data center development costs and stress levels of FTE reacting to leaving a known environment and suddenly thrust into an unknown environment due to company relocation. Past researchers have researched the stress issue on people from different geographical areas and occupations and the research show a detrimental effect on the people with employers losing employee productivity. Three research questions were asked.

RQ1: What are the budget effects of data center development at various flight test sites to flight test programs?

RQ2: Does the FTE experience the harmful effects of increased stress with could lead to productivity decline and higher employer cost?

RQ3: Does technology exist to support consolidating data processing of numerous flight test programs to relieve possible high stress effects and reduce the budget effects to flight test programs?

Sampling stress

A research method of participation used to gather data was the validated Perceived Stress Scale (PSS) created by Dr S. Cohen (Cohen, 1988). The PSS is composed of ten questions for participant response of predominantly qualitative data relating to stress. The PSS was used by empirical studies to measure stress

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due to environmental conditions and stress due to emotional response.

This was qualitative research using purposeful sampling of predetermined questions. The questions were not expected to generate additional questions for inclusion into the survey. The participants were selected within the flight test department at the work location of the researcher. There was a high probability these participants reflected the probability sampling of other FTEs located at different geographical locations and performing the same type of tasks.

The method of probability sampling was Cluster as the group of FTEs is identified and studied. Sampling was expected to be 25 to 30 using interview techniques of local FTE where 80% rate of participation was expected due to familiarity and access to FTE. A sampling of remote FTE at either Lockheed or Boeing remote locations would be substituted if the expected rate is not reached. A 5% rate of requested participation was expected of remote participants contacted via email or telephone.

Limitations and assumptions

During this research, there was a limitation on communication using the budget survey with past and present project managers. Some of these subjects located for information were data processing managers. Some of whom did not take the time to respond to inquiries due to work requirements. Data received from project managers was limited by failure of the project manager to keep records on development cost due to pasting of time.

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There was a high confidence the stress sampling size would be achieved as the local participants have a working proximity to the researcher and can easily be contacted. This lowers the limitations on the number of samples which must be taken. Questions asked were not invasive otherwise the type of questions would be a limitation on sampling results.

If the local sampling was too small a limitation of contacting remote participants is possible. Participants were asked ten questions from the PSS on past memories of stress conditions before their worse relocation and the same ten questions during the period of the same relocation. Limitations were the accuracy of remembering the past conditions.

The same questionnaire was uploaded onto the researcher’s web site. An email was sent requesting the Society of Flight Test Engineers (SOFTE) Webmaster to place a link on the SOFTE forum page with connectivity to the researcher’s web page containing the PSS questionnaire. A limitation is the number of visits to the web site and desire of engineers to volunteer three minutes to complete the survey. The assumption is five surveys will be filled out for addition to the one-on-one interviews using the survey.

Hypotheses

H1: Duplication of data center development will show a redundant cost to make data centers operational.

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H2: Results of engineers reporting relocations will show high stress data similar in pattern to previous relocation research on employee stress.

H3: Loss of productivity can be affected by the engineer’s stress due to relocations

H4: Existing technology used by enterprises can provide a means to consolidate flight test data centers.

Research

The effects of this research held the prospects of a paradigm shift from the beginning of the twentieth century in the method flight test data centers are developed for each flight test program. This shift from the conventional method of development and operation would place a core FTE group at a centralized location to perform data analysis on not just one but numerous flight test programs.

Any high levels of stress among FTE would be greatly reduced as the core of FTE is stationary and not moving from flight test program to flight test program. Human resource departments would see less emotional problems among FTE and any problem in convincing FTE to relocate would be reduced. Cost savings would be enormous as the duplication of effort in development is no longer a factor. Man-hours in software development is reduced as a central software department at the centralized location would be tasked with each method of aircraft processing.

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Purpose of the Study

The flight test community constantly looks for new engineering changes to test aircraft designs. INET is one suggested improvement by engineers within flight test to gain efficiency in data sampling and data transmission bandwidth. Designs of test flight data processing systems are changing with technology by moving from mainframe computers to high performance personal computers and the new blade technology.

The method of bringing this new technology into a more efficient design of data center has not occurred. The same idea to analyze post-flight data at dedicated data centers for each flight test program remains the same. The purpose of this research is to determine if large negative effects are present to warrant consolidating all program flight test data centers for post-flight data analysis at one location to save program costs and reduce any possible stress among flight test engineers.

Objectives of the Study

The objectives of this study were to awaken data processing managers and human resource departments to possible negative effects on producing multiple flight test data centers. A conventional method of tasking data processing development is easy to duplicate as the method already exists.

Researching more efficient methods takes valuable time from managers and this research can provide data for study

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by managers to reduce cost and increase stability among FTE employees. Objectives included interviewing flight test engineers to gather data on the stress effects of relocation, contacting previous and present program managers to determine cost of various data center development projects, and presenting existing information on enterprise success or failure to determine if the enterprise method of consolidating data centers can be applied to flight test.

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CHAPTER 2: LITERATURE REVIEW

Introduction

Chapter organization

Every flight test program develops a flight test data center for analyzing test aircraft performance. This chapter begins by reviewing literature explaining the history of how this method has become a conventional method of data center development. Theories on continuing duplicating data centers are contrasted with theories on consolidation.

These theories are presented from past respected authors in the field of flight test telemetry. Strock and Weaver held the theory of a commonality among data center architecture. This is in contrast to Smith, Matthews and Van Der Velde whose theory was the architectures are different to conform to different designs of test aircraft. The next section of this literature review looks at the effects of theories of duplicating data centers. Sub-sections show these effects relating to program budget, flight test engineers, and employer relocation expenses.

A review of literature presenting enterprise methodologies presents the positive and negative theories of consolidation in the next section. Enterprises have embraced the theory of consolidating data centers while the flight test

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community has not. Technology theories allowing flight test consolidation to exist today is discussed in the next section.

The review in this section presents technologies which can be used to design a consolidated flight test data center. Figure 2-1 depicts the outline of this literature review with Table 2-1 listing the sources.

History

Duplication vs Consolidation

TheoriesImpacts to Duplication

Consolidation Pro vs Con Theories

Enterprise Consolidation

Theories

Technology to Support

Consolidation

Literature Review OutlineFigure 2-1

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Sources of literature

Category Sources

Budgets Air Force Internet public itemsProgram Managers

Centralization Manufacture web sitesProQuest databaseEBSCOhost database

Data Center EBSCOhost databaseInternet scholarly publicationsSociety for Flight Test EngineersGoogle Scholar

Flight Test International Telemetry Conference attendance –October 2008Professional flight test organization sitesEBSCOhostEdward Air Force Base Technical LibraryInternet scholarly publications

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Category Sources

Relocation Research Library DatabaseManufacture web sitesInternet scholarly publicationsEBSCOhost

Stress Internet scholarly publications EBSCOhost

Telemetry International Telemetry Conference attendance –October 2008Authored technical booksInternet scholarly publications

Sources of LiteratureTable 2-1

Conceptual map

The methodology of developing flight data centers is depicted in the conceptual map of Figure 2-2. Development of a data center begins after a contract is awarded to an aircraft company to conduct flight tests of an aircraft (1). A

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conventional method is to develop a data center at the aircraft test site and at the home site of the aircraft company (8). This methodology began with the Wright brothers first flight (9) when aircraft performance data was analyzed locally (Giadrosich,1995), (10).

Today this convention of development has not changed resulting in duplications of data centers at the test sites of each test program (2). Funding of the test flight program provides a budget to relocate FTE from geographical locations to the test site (6). This relocation supplies numerous FTE for the first phase of aircraft testing to conduct the data analysis from data processed by the data center. The amount of FTE hired to support the first phase of flight test is necessary as data analysis is higher during the first phase for political reasons of maintaining the test budget received from Congress.

After the first phase of flight testing is completed (4) the number of FTE are reduced (5) and relocated to other programs (6). There are two major effects to developing on site data centers. The first effect is the relocation of FTE to support data center processing producing stress which could lead to Relocation Stress Syndrome on the FTE and families (Munton,1990), (15). The second effect is to the program budget spent by the employer to pay for the FTE relocations (7).

Consolidating flight test centers is a theory to eliminate the effects discussed (Moore, et al.,2007). This can be accomplished by researching the methods enterprises use to consolidate data centers (14). These methods are compared to the methodology

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of developing flight test data centers (12) and from the comparison developing a new methodology of consolidating flight test data centers (13).

Background of convention

The convention of administering individual data processing methods at the flight test site can be traced to Orville and Wilbur Wright. Donald Giadrosich (1995), former Director of Operations and Analysis and Chief Scientist, of the U.S. Air Force Air Warfare Center alluded to Orville’s methodology of operation by referring to Wilbur Wright’s report of the December 17, 1903 test flight as an early Test and Evaluation (TE) report.

This first theory of flight test processing methods is confirmed in the Wright brothers paper submitted to the Western Society of Engineers in 1903 titled Experiments and Observations in Soaring Flight. Samuel Langley (n.d.) an early pioneer in aviation during the time of the Wright brothers agrees this was the first recorded theory on how to process flight data as Langley quoted the Wright brothers in referring to direct experiments followed by conclusions. Langley (n.d.) backs up his statement by publishing the paper Story of Experiments in Mechanical Flight containing written evaluations of test flight.

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Conceptual MapFigure 2-2

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Without the present telemetry technology existing today historically TE continued at each location of the test flight. Van der Velde (n.d.) mentioned how in 1930 cameras photographed the pilot’s instrument panel during flight. The History of Flight and Test Instrumentation at Flight Test and Verification article states that when Saab Aircraft Company was founded in 1937 the theory of on-site data evaluation continued 30 years after the Wright brothers published paper. The article tells how the first flight conducted at Saab was accomplished by the pilot’s written notes and observations (Straff, 2008). This methodology 20 years after Saab’s first flight remained unchanged as stated by Straff’s (2008) The Development and Use of In-Flight Analysis under the section A Flight Test Observer tells how in the fifties pilots were recording gauge readings onto notes Hartley (1995).

Harley’s comment lends belief to the theory of continuous note taking for 50 years of flight test after telemetry technology was created. Telemetry allowed a test article to be measured for performance with the data analyzed at a distance. Stiltz (1965) stated otherwise by believing there was a limited use of telemetry for data collection before World War II by aircraft manufacturers and after World War II a huge increase in telemetry use started with the missile age.

Perry (1963) agrees with the statement of Stiltz by saying the difficulties of recording by hand in flight was due

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to the changing parameters and this occurred until the beginning of World War II. Hartley, Perry and Stiltz’s theories could be correct as the method of telemetry surfaced after World War II. Strock (1983), a senior telemetry engineer and respected author, put forth the theory that not all manufacturer’s embraced telemetry. Strock pointed to the lack of written material on the subject of telemetry in application to flight test and this is the reason only a fraction of users’ embraced telemetry.

Van der Velde (n.d.) concurs with Strock. Van der Velde records how during the 1950s frequency modulation (FM) recorded data to tape for analysis at the data center. Then in the 1960s pulse coded modulation (PCM) and form of digital recording became the standard. Both FM and PCM are methods of coding telemetry data. The new technology of telemetry allowed real time processing of flight test parameters, yet did nothing to change the theory of post flight processing at the test flight site.

Not until the early 1980’s were the combination of software, hardware and methods of testing established to allow important data analysis to be completed after the test flight on the ground (Hartley, 1995). One hundred years after the Wright Brothers the Wrights theory of on-site data processing has not changed. Data processing systems are designed based on the type of flight data to be analyzed and the methods created for use of the system

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(Smith and Matthews, 1981). This statement continues the theory of separate data processing development and operation at each test site.

The basis for this theory is not completely true as all telemetry processing systems have portions of their design that are common. Stock (1983) recorded that every customer has unique requirements to process flight test data and the system design always contains basics portions which are common with other flight test data systems.

Table 2-2 illustrates with data extracted from The Evolution of Flight Testing at Edwards Air Force Base (1996) how data was post-flight processed on site from 1946 to 1992 for multiple flight test programs. This data shows manual recordings of flight test at Edwards Air Force Base continued until 1966 when automated processing using telemetry became common.

Strock’s statement indicates a common data processing system for multiple test flight programs is possible. This early eighty’s statement is echoed years later when Harold Weaver (2007) suggested a consolidated data processing system located at the contractor site is the best method to process data by sending the raw data from the test site to the contractor site for processing. This theory of processing and operation completely contradicts the theory by Van der Velde (n.d.) who believed a data processing environment was best located at the major test project site and contains unique procedures and requirements for the processing environment.

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Year Post-Flight Processing Method

Program

1946 Manual P-59,P-80, B-47

1956 Manual F-100, 101,102,104,B-52

1966 Automated Processing

YF-12, SR-71, F-111, XB-70


C-5, LWF


B-1


F-16

1987 Interactive Processing

F-15E

1992

Interactive Processing

ATF

Flight Test Program Table 2-2

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Although the centralization theory put forth by Weaver contradicts Van der Velde’s theory of duplication the convention of system duplication continues today. Table 2-3 compares the theories of each author. Lockheed-Martin in 2009 manages multiple aircraft programs at different test sites each with separate data processing systems; Ft Worth, Marietta, Patuxent River Maryland, Palmdale, California, and Edward Air Force Base (Lockheed-Martin web page, 2009). Boeing manages aircraft programs at Seattle, Wichita, and Edwards Air Force Base (Boeing web page, 2009).

Author Separate Data Centers Consolidated Data Centers

Smith & Matthews YES NOStrock NO YES

Weaver NO YESVan Der Velde YES NO

Flight Test TheoriesTable 2-3

Theories affecting data center duplication

Research on data center cost

Duplication of processing systems creates a redundancy in system purchase and operational cost when emphasis today is on reducing program costs. Hughes, Gardner, and Painter (1996) theorized this as a major problem due to shrinking flight test organization budgets causing personnel

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shortages, shortening test cycle time and simultaneously trying to improve competitiveness.

Contributing to the demand on the program budget is the high cost of processing the flight data. Smith and Matthews (1981) stated flight test processing are consuming 40 per cent of the entire flight test program budget. As an example, system purchases at Edwards Air Force Base in 1999 was $2,625,000 (Air Force Budget Item, 1999), in the year 2005 the amount was $ 3,484,000 (Air Force Budget Item, 2005) and in the year 2006 the amount spent was $3,056,000 (Air Force Budget Item, 2006) at the same test site. L-3 Communications (Business Services Industry, 2000) supplied the Patuxent River Naval Air Warfare Center Telemetry Processing Systems valued at one million dollars with follow on orders.

Separate budgeted amounts for acquisitions purchases are only a part of the overall cost. In the beginning of a flight test program a budget is established to fund research and development. After the system is designed the major cost is production followed by budgets for operation and support. Systems become outdated as the flight test program advances and equipment must be replaced. Finally, a budget must be created for disposal at the end of the flight test program (Giadrosich, 1995).

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Research on relocation stress to employees

The change of FTE from one work location to another to support various data centers of flight test programs could produce harmful effects often overlooked by human resource departments. Change is not easily tolerated by humans as change can affect a person’s equilibrium and trying to restore this equilibrium can make organisms’ vulnerable (Moyle and Parkes, 1991). Studies at the University of New Haven show when rated with other forms of stress job relocation stress is at the top of the list as humans have problems adapting to change (Frank, 2000).

A condition which can easily bring harmful effects to FTES relocation often is a syndrome identified as Relocation Stress Syndrome. This is a syndrome resulting from physiologic and/or psychosocial disturbances due to environment transfers (Manion and Rantz Ph D., 1995). Manion and Rantz Ph.D. continued to state how multiple transfers produce worse stress on the employee as often is the case when some programs scale back and other programs build up their workforce forcing relocations.

Relocation Stress Syndrome is a stress related disease and is becoming a big problem in the high technology business as recognized by Anderson and Stark (1988). Due to national and international markets the high technology business relocates employees for customer support and sales. Symptoms listed which can occur in any population experiencing relocation are:

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1. depression,

2. deterioration of health

3. little community involvement

4. strong dependency on the marital relationship for emotional satisfaction

5. high divorce rate

These conditions parallel Frank (2000) who mentioned increased anxiety or physical disturbances due to workplace transitions as effects of:

1. increased workload

2. loss of control

3. reduced social support

Anthony Munton of the University of Sheffield conducted studies which agree with Anderson and Stark. Research shows 75% of employees were somewhat to very stressful after relocation (Munton, 1990). This percentage could be much higher in the range of 80% to 100% with relocations causing apprehension and anxiety (Manion and Rantz Ph.D.,1995). Relocation stress is not central to just the employee as this condition affects the employee’s family trying to reestablish social and educational connections. When the children are in the adolescent stage the stress is more acute. (Munton, 1990).

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Geographical moves can cause destructive acting out in teenagers causing their social relationships to be impaired due to geographical moves (Anderson and Stark, 1988). A special needs child of an employee can produce serious issues due to relocation. Listed by Mumma (2001) are issues of medical conditions, emotional instability and behavior problems. Stress can affect the female harder than men. Elsass (2000) at Clark University researched the stress level in professional women. Since women often take on the household chores more so than men the stress level is often high. The home responsibilities of stress added to the work stress level could increase much higher with relocation.

Research on employee relocation affecting employers

Not all employees are eager to relocate as their relocation concerns can produce an unwillingness to move. Munton (1990) recorded how refusal by employees from 1986 to 1989 almost doubled. The refusal rate grew during this time from 36% to 70%. The number of managers refusing relocation as reported by Munton (1990) was 60%. The refusal to relocate is higher with the older workers as they are more entrenched within their

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communities and have higher equity in their homes (Feldman & Bolino, 1998).

Unable to convince employees to fill remote positions is a challenge for Human Resources (HR) as some employees will seek employment with other companies rather than relocate. This presents a challenge to HR people trying to satisfy the needs of the employees and their families. When this need is not met, the employee seeks other employment (Mumma, 2001). This trend continues as Russell (2000) from the University of Georgia wrote how companies are going to find keeping a mobile workforce much harder due to recent trends due to refusals to relocate. A figure stated by Mumma (2001) was 87% of employees in 1999 declining relocation were due to family issues.

Atlas Van Lines (2008) conducted a study which declared family issues and family ties were a reason 63% of employees declined relocation. Feldman and Bolino (1998) believe family issues can be overcome and relocation possible when the employee has seniority and a psychological commitment to his or her employer. When family issues place strain on the employee’s marriage divorce can occur.

The IMPACT Group (2003) defines a Circle of Chaos theory as the point during relocation when the dynamics of a marriage can disintegrate. The Circle of Chaos affects the employee’s job performance. IMPACT Group (2003) mentions this condition by saying if the family issues are not dealt with the company can lose six months of productivity from the employee.

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Considering the mean wage of an FTE is $45.18 per hour as reported by the Bureau of Labor Statistics (2008) this translates to a projected loss to the aircraft employer of $43,000 over six months. Relocation is expensive for companies.

Mumma (2001) records the average cost of an employee to relocate at $45,000 to $50,000 and the cost of transitional services at $650 to $3,000. Greg Hoover (2002) placed the average cost to move a homeowner at more than $60,000. Shinkly (2003) mentioned how a survey of 300 corporations by the IMPACT Group listed a figure of $26,000 and $50,000 spent on each employee for relocation, which was 58% of those surveyed. A figure of $76,000 and $100,000 was spent by 11% of the surveyed group.

Data center consolidation theories

Merging data centers

Data center consolidation is a method to merge the number of distributed data centers into one centralized data center capable of processing all data. This method is popular among enterprises as a means to reduce cost and make the data center easier to operate (Brodkin, 2008). Sun Systems (2002) puts forth the theory for enterprises embracing this method as due to lower costs in network usage and the difference in wages caused by the location standard of living in various parts of the world. Both theories are different from Mendelson’s theory.

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Mendelson (1987) applies Grosch’s Law by declaring consolidation must take into effect the economies of scale. Measurement with this method is by comparing the computer speed in MIPS with cost. Theories put forth by Bort are the reduction of the total cost of ownership due to less material and labor resources due to consolidation which can be 30%. Not only are the amounts of servers reduced but the maintenance cost and vendor contacts decreased.

Standards for software and ease of security implementations can be established (Bort, n.d.). Flight test has not embraced this method of data center consolidation although other enterprises are moving in this direction. Most IT executives are considering data center consolidation (Brodkin, 2008).

Forty-seven percent of U.S. companies have consolidated data centers to save money, along with 32% of non-U.S. companies, according to the Symantec State of the Data Center Report (2008). Another study found that 39% of IT organizations have a data center consolidation project in the last three years, and nearly half are either considering such a project or planning one. Just 14% have no plans to consolidate (Brodkin, J. 2008).

Repudiating each of these theories is Staten (2008). Staten believes consolidation results in numerous servers and several server rooms. This produces a condition were a person cannot determine which applications are in use and which are legacy. Consolidation involves firing people from distributed data centers and running out of physical space or power. Brodkin (2008) points to other theories as to the negative aspects of consolidation.

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Disaster recovery is a reason not to consolidate Brodkin declares. Brodkin further believes placing all processes and operation within one data center can result in total loss in event of a disaster. Brodkin reasons multiple sites can act as recovery sites and this protects disaster. Similar to Staten’s theory the issue of power and space depletion can be obstacles with consolidation. One theory Brodkin presents is the issue of latency. Information must travel from distribution points to the consolidated data center and this latency can prevent information from being retrieved in a timely manner.

Although the theories each stated by Brodkin and Staten have merit their theories are contradicted by Tarzey. Tarzey (2008) believes distributed data centers are facing a problem with enough space and power. This statement is exactly what Brodkin and Staten each declared about consolidated data centers.

Tarzey offered another theory supporting consolidation. Tarzey (2009) wrote how many large companies have thousands of servers and only 10% to 20% of the server capacity is being used. The average utilization of a corporate server operating is less than 10% as reported by the Hewlett-Packard Company (2008). Table 2-4 compares the differences in each author’s theory.

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Author Theory Consolidation?Sun Systes Lower Cost YES

Tarzey Unused Server Capacity YESBrodkin Latency,disaster recovery NOStaten Application location

confusionNO

Bort Reduction in cost, ease of security

YES

Mendelson Economies of scale YES

Author’s TheoriesTable 2-4

Telemetry network theory for data center consolidation

Consolidating flight test data centers involves moving vast amounts of data from the remote sites to a central site over a high bandwidth network. (Moore, et.al., 2007). Lending support is a theory of a networked based system management interface methodology for telemetry systems. The method described must be standards based. Each device on the network centrally controls all switches, data acquisition units, recorders, and telemetry equipment. Network protocol must be IP to quickly react to changing test scenarios with actions transparent to the user. (Moore Ph.D, Abbott Ph.D, 2008).

A system management approach was put forth by Moore, Grim, Kamat, Moodie, (2007) to design system algorithms for automatic management. This theory was to remotely configure, control, and monitor the health of flight test system devices. Not

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included in the 2008 theory above was the inclusion of IEEE 1588 time synchronization and optimizing each end node and applications running on the network.

Moore, Grim, Kamat, Moodie, (2007) specified a more detailed design theory than Moore Ph.D, and Abbott Ph.D. Suggested was using fixed IP addresses for all devices rather than using DHCP. Stated was a DHCP server with dynamic IP addressing does not allow for startup time which is critical during power losses and resets which commonly occur during flight test. The drawback mentioned using assigned IP addresses is the loss of flexibility and the requirement to configuration control all the IP addresses.

The detailed management of the network was not presented by Bertrand, Moore Ph.D, Abbott Ph.D (2008). Only general theory was presented by reference to plug and play devices and theorization of vast amounts of status data from each node to the central server. Another theory is a standard networking technology for network-centric telemetry systems.

The iNet project is an attempt to establish this type of system. The purpose is to insure products from various vendors are interoperable to the user providing flexibility and making the products economical. The suite of IP protocols need to be used to standardize data transfer at each layer together with the standards being defined by the integrated Network Enhanced Telemetry project (iNET) (Ragsdale Ph.D., et al., 2008)

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Time synchronization theory of data center networks

Synchronization of accurate time by device clocks is recognized as to the importance of proper time correlation of data over networks. Precision Time Protocol (PTP) is suggested for used as the standard defined by the Institute of Electrical and Electronic Engineers (IEEE). This synchronization should extend from the test article to the ground station. (Ragsdale Ph.D., et al., 2008). Latency of data transfer was a concern mentioned by Brodkin (2008).

Traditional Pulse Coded Modulation telemetry systems contained guarantees of throughput and latency. Developing telemetry systems must maintain similar guarantees (Ragsdale Ph.D., et al., 2008). Singling out the latency of PCM rather than the general mention of data transfer by Brodkin over the network is a more pointed approach. PCM as defined by the IEEE standards of the IRIG 106 suite has predominately been the design of flight test data acquisition systems. Advances in flight test and network technology has created integration issues in flight test systems.

A network –centric approach can optimize the recording and processing of data. Developing an Interface Control Documents (ICD) for each interface in the system is a method to control network communication. In addition, the implementation of IEEE 1588 is necessary for time correlation of all network nodes. These theories were put forth by Smith, Newton, Moodie (2008).

The iNET program is a study to create architecture with created standards to allow the use of new telemetry technologies.

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An operational study was conducted to incorporate the iNET architecture with traditional PCM stream architecture using an H-60 helicopter as the test article and legacy PCM telemetry systems. Instead of IRIG 1588 timing synchronizing the study transmitted data over a serial telemetry link with the IRIG PCM time tagged into each major frame.

The telemetry network link using iNET provided a means to request duplicate data back to the test article in event of data loss. This was an attempt to demonstrate the theory of an error free means of receiving telemetry data over a wireless network (Hodack,2008). Yacob Astatke and Doctor Richard Dean offer a different theory using a mixed network architecture developed at the Morgan State University.

This theory uses a hybrid network to extend the range of network telemetry from the test article to the ground station. The network is composed of sub-networks clustered to receive telemetry data based on the signal strength and location of the test article. The sub-networks are composed of clustered cells with the ground station at the center of the locations (Astatke, Dr Dean, 2008).

Data processing collaboration theory

Importance of Communication

Within the flight test community communication between the principle engineers is important to gather quality flight test data as stated by Van der Velde (n.d.). This importance on

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communication makes consolidating a data center difficult. Some principle engineers would continue to reside at different geographical locations. Fokkerweb (n.d) understood how the collaboration of the Data Engineer, Instrumentation Engineer, and Disciplined Flight Test engineer must continue a close relationship for planning and communication purposes. See Figure 2-3.

Since all measurements begin at the instrumentation level a large concern is the coordination which must exist upon instrumentation engineers. Crounse (n.d.). When computers started interfacing with telemetry data in the 1980s this importance on face-to-face communication was recognized. This method has to exist among the data processing engineers and airborne instrumentation engineers where the data processing engineers must know the limitations and operation of the airborne instrumentation (Smith and Matthews, 1981).

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Flight Test Collaboration ProcessFigure 2-3

Existing technology supporting collaboration

Telepresence theories

The technology of telepresence bridges the distance between two or more parties as a means to maintain group collaboration. However, this mode of communication cannot replace the

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richness of face-to-face communication when offices are close by and employees work physically together. As a result, collaboration deteriorates even when the subject matter is related. The best method of collaborate over distances is to put the focus on the quality of communication and create a system where physical distance replicates physical proximity states Hollan and Stornetta (1992).

Bielski (2008) mentions how telepresence to be effective must show natural skin tones and colors with life size pictures. The sound must come from the direction of the person on the screen. This method can fool the brain into believing the virtual presence of another person is physically nearby. Communications from a remote to a central data center using telepresence dampens the theory of maintaining flight test collaboration due to cost. An installed product costs from $329,000 to $399,000 and monthly expense can approach $18,000 states Hathi (2008).

Virtual data center theories

Efficiency in data center consolidation must involve a method to change from a static design to a dynamic system design based on current flight test program requirements. Van der Velde although arguing for decentralizing data centers admits each test program contains unique procedures and requirements. Table 2 illustrates the various aircraft programs from 1946 to 1992 to support Van der Velde’s theory and supports the methodology for a dynamic system design to support various flight test requirements.

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System virtualization is dynamic, and a technology used by enterprises to provide business continuity and disaster recovery as a strategy during failures. Flexibility extends to allocating efficiently computer resources and ability to change system design to meet new requirements (Violino, 2009). Estimates of downtime worldwide in loss productivity were $140 billion dollars in the year 2007. Cautions are raised about virtualization as a virtual machine (VM) is faster to install and the prospect of creating too many VMs can lead to unused resources. Identification of VMs can be lost therefore to system administrators; IT must understand which resources are in use and available (Dubie, 2008).

Linsenbach (2008) agrees with theories of better efficiency and decreased costs with virtualization. Linsenback believes data center lowering of costs and greater efficiency is proven by server virtualization methods. This agreement is clarified by warning of problems combining storage with virtualization. Linsenbach quotes the theory of Jim DeCaires, manager at Fujitsu, who thinks people have the wrong idea about storage virtualization as the answer.

Storage virtualization can consolidate data quickly from multiple sources although legacy storage methods can do the same. This creates a deficiency with storage virtualization. More archived and critical data can be restored leaving the data open to corruption. Another deficiency is the virtual layer creates latency during data restore and retrieval (Linsenbach, 2008). Research at the University of Michigan involved studying the security of virtualization.

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A malicious hypervisor was created which resided underneath the operating system and was undetectable. This study proved the concept of how a malicious program could easily attack a virtual system (Carbone, Lee, Zamboni, 2008). A theory is the concern about malicious attacks on virtualization is a myth. This theory did not take into the account of the success by the University of Michigan in creating a malicious hypervisor. Citrix/Xen, Microsoft, or VMware technologies have no history of a virtual server being critically compromise. (Schreck, 2008). Schreck points out vulnerability could only exist if the virtualization was not implemented properly. This state would be very difficult to recognize if the system was compromised.

Centralized data storage

Consolidating multiple databases from many locations of test flight is possible by examining the number of enterprises successfully consolidating mass amounts of data into a single database. Bradshaw, et al. (2008) states how enterprises use mass archive storage systems for the storage and retrieval of billions of documents using either a parallel file system or a Tivoli storage system. Both are scalable systems capable of storing numerous petabytes of data with global access.

NASA’s Earth Observing System Data and Information System (EOSDIS) has taken advantage of this storage technology to store petabytes of spacecraft information from 66 locations. Daily storage rates can approach three Terabytes. (Behnke, et al., 2005) Moving petabytes of data over a wide area network to a

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central data storage can over time cause data corruption either from dropped bits in transfer or failing network equipment.

Behnek, et al. (2005) suggests using a checksum generated at the source and verification at the receiving end. Hewlett-Packard (HP) examined their distributed systems and functions and reached the conclusion to centralize. The result was 28 data centers containing data storage was reduced to less than ten. This consolidation by HP solved purchasing duplicate software licenses for each of the 28 datacenters. Reduced was database maintenance, reporting and system management (Goldman, 2006).

Enterprise methods of consolidation

Flight test datacenters use the same method of architectural design since the Wright brother in contrast to enterprises taking advantage of changing technology to change system design. Enterprises mainly used centralized computer systems in the 1960s. This was due to the limited technology and architecture of the systems using mainframe computers. A small amount of decentralization occurred during the 1970s using dumb terminals communicating over telephone and lease lines to the mainframes.

During the early 1980s decentralizing increased with the use of microcomputers. By 1987 into the early 1990s enterprises were considering the advantages of centralizing for economies of scale by realizing the high cost of separate data centers. In 1992 the emphasis on web development tilted the enterprise business plans towards decentralizing their data centers. As an example,

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Amazon.com started installing multiple servers internationally located to increase sales and response time of orders. By 2000 enterprises are seeing an increase in IT costs. These lead enterprises to shift towards centralizing to reduce the number of employees, improve security issues, and improve access to data. (Evaristo, Desouza, Hollister, 2005).

This argument was supported by Markus, Tanis, & Fenema (2000) by stating how enterprise resource planning (ERP) decisions are formulated locally and when the enterprise is distributed over many locations the ERP is difficult to manage. Reasons stated were costs to support the various data centers, software configurations, platforms and duplication of data storage; although consideration must be given to the size of the database in a centralized system.

Carr (2005) wrote how some enterprises are switching to IT utilities instead of spending huge sums of money on creating numerous data centers. One savings the enterprises are seeing is the elimination of the maintenance of backup generators for each of the data centers in addition to the support staff for the generators. Additional savings is the duplications costs for software licenses, hardware and system maintenance.

Carr mentions how virtualization is allowing applications for different platforms to be run; web services are standardizing the human interface; grid computing allowing centralizing of data storage. HP is mentioned by Carr as consolidating 52 financial management systems which gave a 14% improvement in the

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operating margin. The successful attempts by enterprises are in contrast to flight test data centers whose development does not mirror the success of enterprises.

An example of consolidation by enterprises is listed in Table 1-5. One of the basic motivations for enterprises to consolidate is the passage of Federal regulation, especially the Sarbanes-Oxley Act in 2002 which forces enterprises to centralize IT systems where corporate decisions can be implemented faster to respond to Federal mandates (Mahato, Jain & Batasubramanian, 2006). These three authors’ list six phases’ enterprises are taking to implement centralization.

1. Identify Phase – Upper management identifies the role of ERP by creating scenarios of action.

2. Define Phase – Program management approaches are defined

3. Decide Phase – Program management structure decided upon

4. Prioritize Phase – Priorities established for program goals

5. Execute Phase - System launched

6. Maintain Phase – Production is sustained

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Enterprise Action Cited in ArticleCommonwealth of Pennsylvania

Consolidated 17 data centers

Carr (2005)

Quantas Airway LTD

Consolidated over a hundred servers

Carr (2005)

Quantas Consolidated reduced costs by 40%

Carr (2005)

BICC Cables, U.K. Consolidates 40 data centers

Markus & Tanis (2000)

Millipore Corp. Consolidated three international data

centers

Markus & Tanis (2000)

Hewlett-Packard Consolidated 56 data centers

Goldman (2006)

EOSDIS Centralized storage from 66 locations

Behnke, et al., (2005)

Enterprise Examples of ConsolidationTable 2-5

Summary

Aircraft companies continually develop flight test data centers to support aircraft testing at the site supporting the flight test. This is a convention dating back to the Wright brothers which has not changed. The technology of telemetry was a step-in processing data remotely from the actual test flight yet the technology was not advanced to the point of consolidating the post-flight data center. As a result, two hundred flight test engineers could be relocated from geographical points to the

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location of the flight testing to analyze data processed at the post-flight data center.

The continual ramp up in man power to support the first phase of flight test then later the reduction in head count after the phase is completed moves the engineers to new locations to support other flight test programs. As a result, the aircraft company spends large amounts of dollars in relocation cost. The engineers are subject to higher levels of personal stress from the relocation which could lead to loss of productivity incurring higher cost on the employer.

The effect to the aircraft program budget is reflected in the high cost of designing, writing new software code, purchasing new hardware, and system testing of the post-flight data center. The system development life cycle of the hardware and current software versions expend even more dollars from the program budget. Consolidating the post-flight data center to emulate the consolidating practices of enterprises is a method to reduce both engineer stress and reduce expenditure of data center development costs.

Enterprises have demonstrated the effectiveness of either consolidating IT systems or decentralizing IT systems based on the level of existing technology throughout the years. To date enterprises is embracing centralization of data center functions for economies of scale using a detailed planned methodology of established planning phases. In comparison flight test data centers have remained decentralized by the refusal to create any planned phases for centralization.

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CHAPTER 3: METHODOLOGY

Classification

Data sheets showing the amount spent were kept on file on computer disk for evidence of receiving the data. Values of development show how cost were incurred each time a FTDC were developed. The second method of data gathering was by the use of a pre-validated survey form used by professional researchers to measure stress on individuals. This stress survey form is composed of ten questions for participant response of stress related situations during company job relocation to another geographical location.

Results were compared to Cohen’s Norm Mean levels of stress (Cohen, S. 1994) to determine if engineer productivity was affected. Presence of stress could produce evidence for consolidation of data centers if stress levels meet or exceed Cohen’s measured stress level. The research method was qualitative using predetermined questions from the validated Perceived Stress Scale (PSS) developed by Cohen (1996). The questions were not expected to generate additional questions for the survey although the researcher could return to the participant for clarification of responses. The classification for this type of sampling is Formal Study.

Protection for participants responding to the stress instrument was coded labels instead of participant names. The coding was acronyms followed by incrementing integers. The

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acronyms are INV for interview; WS for website; EM for email. An example is:

INV(n+1)

WS(n+1)

EM(n+1)

The participants selected were within the flight test engineers at Edwards Air Force Base, California, Fort Worth, and Marietta. All engineers work within the data processing, measurement analysis, and instrumentation fields. There was a high probability these participants reflected the sampling of other engineers located at different geographical locations and performing the same type of tasks if the sampling was performed elsewhere. This technique is identified as Probability Sampling. The method of Probability Sampling to be used was Cluster as the group was identified and studied.

Research design

The research design was formal study as stated by Cooper (2008, p. 143) as the study used a survey form with qualitative research questions. Exact procedures were used with each subject and the goal to test the hypothesis. There was no control attempt of any variable for an ex post facto design (Cooper, 2008, p. 143). However, the causation effect of one stress variable upon another stress variable could be analyzed using statistical software.

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An ex post facto design was to be used on the design cost of the data centers as the researcher can only report what is happening to the development budget. The stress research design contained a pretest to establish validity of the survey to accurately measure the stress of relocation. The survey contained two sections and can be represented by the design:

O1 X O2

Results are measured differences between O1 and O2 represented by the design:

E = O2 – O1

Data collection plan

The stress instrument (survey 1) was distributed by face-to-face interviews, email, and web site access. To reduce participant error the subjects were asked to volunteer, have the necessary information, understand their role in the survey and be motivated to assist the researcher in collecting the data (Cooper, 2008 p. 219).

Participants were contacted by email from collected email lists. All interviews were requested from the FTE with no obligation enforced upon the FTE. A consent form was presented to each person interviewed and electronically signed by the participant. The importance of the research and three to four minutes of time required is explained and accepted by the

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subjects. Interviews were held in the cubicle work place of the subject during a lunch hour with assurance from the subject there were no intrusion on work tasks. No participation by any organization was requested.

Contacts to participants were direct from researcher to participant. Emails with requests for survey 1 input were sent out over the Internet individually and not mass emailed to give a personal touch to each request. Emails requesting participation and consent were emailed to each targeted geographical location; Ft Worth, Marietta, Patuxent River and Edwards, California. Timing of the emails and interviews occurred over a month to give email subjects time to respond and interviewed subjects a quiet period during the work day to relate and respond.

A web site was created at http://www.vickersstudent.com with the Personal Stress Scale Survey on the home page. Each survey 1 question contained a pull down click window with selection for Never, Almost Never, Sometimes, Fairly Often, and Very Often. Selection by this method allowed the subject to complete the survey 1 in two minutes. Survey 1 results were recorded to a web form and the results emailed to the researcher. A links to http://www.vickersstudent.com was placed on the Society for Flight Test Engineers (SFTE) web page after permission from SFTE.

Sampling strategy

Purposeful sampling was the method of choice as each local participant was selected individually; this included preselected remote participants when contact information on the individual

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was attained through organizational charts of each flight test site. Probability sampling was used through the web contacts as these individuals were not preselected.

Purposeful sampling of numerical values was collected from program managers experienced in designing past and present data centers to attain data center development costs. The program managers were identified by data processing managers and other program managers. A personal interview of the participants was attained with an expected sample of 25 participants. Contacts with engineers by email at other company locations increased this to 35 samples.

Oates (2007, p.100) indicates if quantitative sampling is less than 30 calculating the Mean is not accurate therefore only qualitative sampling is to be used. The response rate was expected to be 80% for the local interviews as the researcher has a working relationship to the participants. Remote participants contacted via email or telephone was expected to produce a 5% rate of response rate. Both local and remote participants were questioned using the same type of PSS form.

The PSS form was filled out twice during each interview. The purpose of the first PSS form was to measure the stress level of the participant a month before the occurrence of relocation as a determination of a baseline of stress. This required a remembrance on the part of the participant as to his/her life before the relocation. On the ten questions of the second PSS form the participant was asked to remember the period of the actual relocation. Both forms contained exactly the same ten questions. Data from Project Managers was collected via email

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from email requests for amounts spent on data center development at various sites.

Instrumentation

Instrument Survey 1 is a pre-validated Perceived Stress Scale survey consisting of ten questions relating to stress situations. The PSS is based on the Perceived Stress Questionnaire (PSQ) by Levenstein et al. (1993) in German. The PSQ was converted to English and a scale placed on the questionnaire by Dr. Sheldon Cohen. The PSS is not copyrighted and available for free used for research or educational purposes although written permission was attained. The survey is available at http://www.psy.cmu.edu/~scohen/.

The permissions of use are from Dr. Sheldon Cohen’s laboratory for the Study of Stress, Immunity and Disease web site http://www.psy.cmu.edu/~scohen/. Permission was obtained in writing from Dr. Ellen Conser at the Department of Psychology, Carnegie Mellon University (see attachment). Dr Conser is the point of contact for Dr Cohen. Subjects responded to the survey based on a four-point scale and the answers are analyzed based on harassment, overload, irritability, lack of joy, fatigue worries, and tension (Fliege, 2005).

For remote response emailing of the survey forms the returned data was by email. In cases of telephone contact the researcher would fill out the form as the participant responds. Two survey forms were used. Survey form 1 targets flight test engineers from all disciplines for stress data. The reason to target all disciplines is all flight test engineers regardless of discipline is

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subject to relocation. Therefore, the targeted population is flight test engineers regardless of discipline.

Survey form 2 targets program managers within the flight test engineering group for data center development costs. Survey form 2 information was identified as location and amount with program titles omitted to avoid any company proprietary information rules. Survey Form 1 collected data during face-to-face interviews, email, telephone, and web page responses. Each was presented with a complete explanation of the research project and assurances to the participant the data collected would be kept confidential.

The PSS form does not contain flight test specific questions therefore added to the form are questions; years in flight test, discipline, number of relocations and flight test discipline. The purpose of the addition to the PSS is to correlate the flight test experience with the measured levels of relocation stress. The PSS asks for answers based on the subject’s feelings of last month and is part of the first section of Survey 1. The statement of ‘last month’ was omitted from the second part of survey 1 as part 2 of the survey relates to feelings based during relocation. The nature of the questions was a measure of degree to situations in a person’s life.

Critique of the design

This author believed the research design was stable and contained a minimum of errors in the data collection. The usage of a pre-validated stress scale and questionnaire gives credibility to the design as the survey is proven. The process of the

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interviews were between the researcher and those within the flight test site where the subjects work. This provided better accuracy of data collected and increased the percentage willing to participate in the research.

Limitations of the design were the email responses. Remote subjects sending in emailed surveys do not have the instant access to the researcher where clarification of a question can be given. The email method forced the increase in the number of requests sent as the return percentage was much lower than the interview method.

The web method produced a much lower response due to flight test engineers not knowing where the site was located and the method produced a lower personal touch which lowered the number of elements for the sample. The design relied on subject remembrance of events which could produce errors in answers. These errors if any were factored out by proper statistical presentation of the data.

Testing

Survey 1 form was placed on the web site http:www.vickesrstudent.com where remote flight test engineers could access the form. The survey 1 forms for PSS was pre-tested on three subjects to understand how the form would accurately record relocation stress. Using Survey 1 twice a baseline of stress was established and the stress during relocation was measured. The difference in stress was expected to revealed actual stress of the relocation from the pretest subjects increasing above the baseline stress measurement.

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Survey 2 indicates data relating to data center development for location and cost. This method was chosen to avoid proprietary rules which would be in effect if the name of a test program, company, or government entity was attached to a dollar amount. Requests for program development costs were sent to Edwards Air Force Base, Fort Worth, and Marietta flight test sites.

Variables

The quantitative independent variables established conditions within the subject’s flight test career and were used to determine the amount or length of the data gathered. The qualitative independent variables were stress related questions to record how often the events occurred. These variables each contain one of the following answers; never, almost never, sometimes, fairly often, and very often.

Each of the variables was converted to a numerical value to establish the quantitative dependent variable. Questions four, five, seven and eight are positive questions therefore the values are reversed from the other questions values. Values assigned to questions are:

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Question# Never Almost Never

Sometimes Fairly Often

Very Often

1 0 1 2 3 42 0 1 2 3 43 0 1 2 3 44 4 3 2 1 05 4 3 2 1 06 0 1 2 3 47 4 3 2 1 08 4 3 2 1 09 0 1 2 3 4

10 0 1 2 3 4

Question ValuesTable 3-1

Survey 1 calculated a quantitative dependent variable as a total numerical value derived from answers to ten quantitative independent variables indicating the total amount of stress.

An explanation of the variables in each survey follows.

Survey 1 section A (before relocation):

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Quantitative independent variables:

fte_yrs Number of years in the flight test career –for comparison with the number of relocations to establish a mean value of relocations verse seniority.

relocations Number of times subject relocated – Numerical value use to compare with length in the field of flight test.

age Age of subject – for determination of stress to age

Quantitative dependent variable:

Stress_A The value indicating the amount of calculated stress based on questions 1 to ten.

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Qualitative independent variables contain the data of never, almost never, sometimes, fairly often, or very often:

Upset_A how often the subject was upset

Nocontrol_A how often the subject was unable to control important things in life

Nervous_A how often the subject was nervous and upset

Confident_A how often the subject felt confident about handling personal problems

Thingsok_A how often the subject felt things were going his/her way

Cannot_cope_A how often the subject was unable to cope with events during this period

Control_irritation_A how often the subject was able to control irritations

On_top_A how often the subject was on top of things

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Angered_A how often the subject was angered

Difficulties_A how often the subject felt difficult events

Gender if the subject is male or female

Discipline the subjects area of work within flight test

Marital status Married or Single

Survey 1 section B (during the relocation):

Quantitative dependent variable:

Stress_B The value indicating the amount of calculated stress based on questions 1 to ten.

Qualitative independent variables contain the data of never, almost never, sometimes, fairly often, or very often:

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Upset_B how often the subject was upset

Nocontrol_B how often the subject was unable to control important things in life

Nervous_B how often the subject was nervous and upset

Confident_B how often the subject felt confident about handling personal problems

Thingsok_B how often the subject felt things were going his/her way

Cannot_cope_B how often the subject was unable to cope with events during this period

Control_irritation_B how often the subject was able to control irritations

On_top_B how often the subject was on top of things

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Angered_B how often the subject was angered

Difficulties_B how often the subject felt difficult events

Survey 2 (use to gather cost data on data center development)

Qualitative independent variables (number of variables based on amount of cost data received)

Location (n + 1)

location of the data center development

Cost (n + 1)

amount spent on development

Validation

The type of validity of the research was Conclusion. The result of each survey was analyzed with the other surveys by comparison to the stress levels. Validity was measured when the data was compared to existing research by other researchers. If the data showed a large disparity with previous research then the methods of data gathering must be faulty.

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To insure validity a set time for the interview was explained and kept. Outside influences were kept to a minimum if not completely zero to maintain a stable environment. This control of additional influences was accomplished with survey questions which did not reflect self-bias and participant interviews which were kept strictly to the survey.

The survey form was pretested on selected engineers to assure reliability and input of any ideas to increase reliability. This pretest was not a pilot study and conducted only to determine if the PSS was a viable instrument for the survey. A request from any participant to clarify initial data input on a survey form was answered. Subjects were explained the nature of the research and asked to volunteer to ensure the subject was at ease and giving correct answers to the survey questions.

Collection of the data was based on a previously validated survey used for stress research by researchers. This ensured all questions were approved and worded correctly. The threat to the internal validity was maturation. This is due to the subject trying to remember over a passage of time the stress events which occurred both before the relocation and during the relocation. One researcher administered the survey to all subjects to minimize a self-bias so the questions are asked in the same order and wordage. Construct validity was approached by informing the subjects of the research’s purpose and confidentially to build trust with the subject (Cooper, 2008, p.291).

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Target population

The methodology incorporated both 80% qualitative and 20% quantitative approaches based on the type of data collected in the research on a target population of professional flight test engineers from two major aircraft development companies. Targeted FTE were largely from a major flight test program at Edwards Air Force Base, Fort Worth and Marietta. The FTE were not selected due to their discipline, age or career years. Other FTE volunteered referrals from local FTE and known FTE who have departed Edwards Air Force Base.

Expected were 25 to 30 elements to compose the sample based on the size of the flight test community tested. Qualitative data was collected on human participants agreeing to interview and answering questions relating to human emotion. Quantitative numerical values were converted from the qualitative data and supplied by the same human participants answering questions relating to time and degree of effect. Numerical cost data was to be supplied by program managers for quantitative data collection.

Testing conditions

The context of the interview was within a U.S. Air Force Flight Test Center in a participant’s cubicle office area. Due to work responsibilities, the subjects were contacted during the lunch hour on a no interference basis with work requirements. One to two interviews per day were collected using this method for a period of three weeks.

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The second context was interactive as participants used the web at http://www.vickersstudent.com to email and deliver stress data to the researcher. Local participants were engineers of the flight test community supporting flight test data center operations. Participants within this community work within group disciplines associated with flight test data analysis. Meaning; flying qualities, structures, propulsion, and vibration disciplines among others.

Remote participants were within the flight test community located at distant flight test centers. These participants were contacted via telephone, email, or a web link on a professional flight test organization’s web home page. Requests for flight test engineer contacts were requested through the Society of Flight Test Engineers organization with requests for the web page link be placed on the society’s forum page.

Data analysis

Data from the survey 1 forms was inputted into a SPSS statistical software database. Maximum, minimum, median, normal distribution, standard deviation, and mean were calculated using descriptive statistics to describe the data values. Survey 2 results were analyzed in relationship to each other. No comparison of development costs was attempted as new technology throughout the years reduces the cost of development preventing comparisons.

Results were indicative of high amounts spent for each development. Project names were omitted to prevent correlation of amount spent verses project. This excludes the risk of breaking

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government and company proprietary rules. Numbered locations were to indicate each data processing system development. The methods and purposes and are defined in Table 3-2

Method Purpose

Total of emails sent compared to emails received.

Establishes the efficiency of email response

Total of interviews requested to interviews granted.

Establishes the efficiency of the interview process.

Comparison of web site hits to web forms completed.

Establishes the efficiency of the web site data collection method.

Analysis of stress levels between the pretest portions to the post test portion of all subjects.

Determines the amount of stress due to relocations. Based on maximum, minimum, and mean values using the pretest as a baseline.

Average number of relocations calculated based on time in career field.

Determines the number of relocations expected per year within the field.

Stress level calculated based on Determines if age is related to

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age. relocation stress.

Stress level calculated based on marital status

Determines if being married or single affects the amount of relocation stress.

The six negative questions on all surveys are calculated.

Determines the worst and least property of the stress survey affecting relocation stress.

Types of AnalysisTable 3-2

Summary

This chapter presented the research methodology to accumulate data on two major effects to developing duplicate flight test data centers. The method of data collection for data system development costs was email to various project managers experienced in developing flight test data systems. Inputs on location of development were represented by location numbers to avoid delays in attaining company proprietary approval for information release.

Location numbers provided a security level whereby program type and cost are not connected. The data gathering method on these effects of FTE relocation stress and data processing system cost were explained using two different forms. The purpose of the stress measurement is to determine if

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employer cost is added to the program budget due to loss of engineer tasks resulting from job relocations. The relocation stress collection uses a pre-validated form called the Perceived Stress Scale (PSS) used by many researchers on human stress levels.

Permission to use this form is contained on the Internet web site Sheldon Cohen of Mind Garden, Inc. and written permission. The form was used twice for each subject. The first form was a pre-test to develop a baseline of stress before the relocation. The second form was a post-test to measure stress during the relocation process. Difference between the pre-test and post-test gave results due to the relocation. Limitations of the test were the remembrance by the subject of life conditions in the past.

Three methods of data collection were attempted. One method was face-to-face interviews. The second method was email. The third method was a web page with the PSS and automatic emailing of data to the researcher. The method of data collection for data system development costs was limited to acceptance by program managers to provide the information.

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CHAPTER 4: RESULTS

Introduction

Statement of the problem

As stated in Chapter one the development of post-flight data centers continues to follow a conventional method of duplication. This convention is traceable to the first flight of man aircraft and little deviation from this convention occurs. The reluctance to embrace technological advances continues to feed this process of duplication with one result being the spending of development dollars at each data center as discussed in Chapter 2 regarding the Air Force Budget Items.

The continued surge of engineers, as shown in Chapter 1 Figure 3, relocated to examine flight data at each data center during the beginning of aircraft test programs drains vast amounts of dollars from program budgets for relocation expenses as researched by Shinkly (2003). The relocation process may produce high stress on engineers reducing the engineer’s accomplishments and wasting salaries on non-performance. After the initial test phase flight test engineers are released from the program only to relocate to other flight test programs creating a cycle which is repeated throughout many of the engineer’s career. The relocation expenses paid by the employer are another layer of dollars drained from the program budget. Identifying waste in cost due to duplication is not attempted by aircraft companies although enterprises have effectively consolidated their data centers to increase efficiency.

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Overview of the chapter

This chapter reports the results of the research process as detailed in Chapter 3 together with results contained within the Literature Review of Chapter 2. Analysis of the results within Chapter 4 is limited to the research questions described in Chapter 1. Results of the Literature Review shows a historical overview of how a conventional method of duplicating flight test data centers developed.

These results are referenced to professional authors in the field of flight test and telemetry. Other results from literature draw a contrast to enterprise data center development. Results of research in this chapter displays the expenses incurred in the hardware and software purchase for flight test data centers which are a redundant cost burden on flight test programs.

Additional cost to employers is shown in the data presented and calculated for individual and group FTEs for relocation cost to support multiple data centers. Supplementing this cost is shown in the stress element results from research inputs of FTEs.

Literature review results

Flight test data center duplication

Results of the Literature Review supports a theory of duplicating the development of FTDC which has become a conventional method of development practiced to date. Literature reveals the background of flight testing and how this method was

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originated by the Wright Brothers (Langley, n.d.) and confirmed by Giadrosich (1995). Evidence of continuation of the method is supported by the writings of Van der Velde (n.d.) and Straff (2008) who described cameras and note taking during the 1930s to the 1950s. Writings by the author Hartley (1995) indicated gauge readings for flight test data evaluation. These results from literature show a clear pattern of continued FTDC duplication for over 50 years.

This fact is confirmed in Chapter 2 Table 2 showing data from The Evolution of Flight Testing at Edwards Air Force Base (1996). Literature shows manual data processing through the 1950s until 1966. Further results from this literature present the numerous aircraft programs and how automated and interacted processing of aircraft data until 1992 were used at each flight test data center developed. The reluctance to change this established conventional method of FTDC development is contained within the writings of Strock (1983) in his mention of how the new technology was not immediately accepted by many aircraft manufactures for data collection.

The review of literature does surface two conflicting theories of FTDC development. One theory by Strock and Weaver arguing for consolidation and the other theory by Van der Velde, Smith and Matthews for continued duplication of FTDC. Neither theory affects this study although the results are confirmed in Figure 4 of Chapter 1 showing the duplication of numerous data centers developed and operated by Lockheed-Martin today.

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Development expenses resulting from duplication

The redundancy in purchasing software and hardware in addition to development time was exposed by Hughes, Gardner, and Painter (1996). The authors added to this redundancy the cost of processing the flight data. Smith and Matthews (1981) writings presented how 40 percent of the flight test budget is dedicated to flight test data processing.

These statements are validated from literature showing the results of Air Force Budget Items in years 1999, 2005, 2006 and Business Services Industry in year 2000 identifying cost for flight test data processing. Table 4-1 reveals the budgeted costs during these years. Literature by Giadrosich (1995) added to this the cost of end of life disposition for the data processing system.

Source Year Budgeted AmountAir Force Budget

Item1999 $2,625,000

Business Services Industry

2000 >$1,000,000

Air Force Budget Item

2005 $3,484,000

Air Force Budget Item

2006 $3,056,000

Table 4-1Data Processing Expenses

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Expenses due to relocations caused by duplication

Expenses due to data center duplication are not just the development costs. Literature results indicate employee stress due to relocations can increase the expense of programs to employers. Duplication of labor in system design, software purchases, license renewals, hardware purchases, labor in configuration and testing drive up this cost. Although the literature identifies relocation stress of employees from occupations other than flight test a FTE could experience the same type of stress and cause the same loss of job performance.

This theory was noted in Moyle and Parks (1991) statement in their paper of how a person’s equilibrium changes during relocation making the body’s organs vulnerable to improper functioning. Relocation change can cause physiologic and psychosocial disturbances with multiple relocations further increasing the stress in the research by (Manion and Rantz Ph D. ,1995). The literature review surfaced the same theory by Frank (2000) saying how stress is at the top of the list when people are subject to change.

The Literature Review listed numerous stress symptoms and identified the condition as Relocation Stress Syndrome. Literature published by the IMPACT Group (2003) shows how these symptoms could make a company lose six months of productivity from the employee. In the case of an FTE making a median national income of $45.18 per hour as written by the Bureau of Labor Statistics in 2008 the loss to an aircraft company from loss productivity would amount to a projected amount of

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$46,987 over six months. The expense of stress to the employer is not confined to the loss of wages and productivity.

Relocations expenses paid by the employer can add to the expense of supporting multiple data centers. Literature shows this expense in table 4-2. The cost of multiple relocations per engineer is tabled in Figure 4-1 calculated with a median of $38,000 per relocation during the year 2003. This amount is calculated using the minimum figure of $26,000 and maximum of $50,000 reported by Shinkly for relocation expenses in the year 2003. The medium amount is projected over 10 relocations for one flight test engineer.

Medium = (26,000 + 50,000) / 2

Medium = $38,000

Year Source Range

2001 Mumma $45,000 to $50,000

2002 Hoover >$60,000

2003 Shinkly $26,000 to $50,000

Table 4-2Relocation Expenses

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Figure 4-1Cost of multiple relocations per engineer

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Enterprise consolidation

A conventional method of data center development does not exist with enterprises when considering the data in Table 4-3 of how enterprises examine current technology and adapt the data center system designs to best use the new technology. In contrast to flight test data center development using only decentralization methods since the year 1903 a review of the literature showed how the design method for enterprises changed over the years alternating from decentralization and centralization based on technology.

This theory was presented by Evaristo, Desouza & Hollister (2005). Mahato, Jain & Batasubramanian, (2006) labeled six phases of planned development during 1960 to 2000. Table 4-3 illustrates the phases and changing methods of enterprises. The reason for enterprise consolidation today was brought forth in theories by Brodkin (2008), Sun Systems (2002), Bort (n.d.) and Brodkin (2008). These reasons were the reduction of total cost of ownership due to less material and resources. Results of the literature review gave statistics for the year 2008 showing 47% of US companies and 39% of IT organizations changing to consolidated data centers. This is in contrast to 14% reported by Brodlin (2008) with no plans to consolidate. Arguments for consolidation and the opposing theory of duplication are presented in Table 4 of Chapter 2

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.

Years Method Reason1960s Centralization Limited architecture

of Mainframes1970s Move Towards

CentralizationAvailability of dumb

terminals using telephone leased

lines1980s Decentralization Availability of

microcomputers1987 Centralization High cost of separate

data centers1992 Decentralization Web development2000 Centralization Increase IT costs

Table 4-3Enterprise Methods

Data Collection

Collecting development costs

Emails to nine program managers who built data systems were sent to flight test sites requesting development costs for flight test data centers. Data collected were from Edwards Air Force Base, Marietta, Patuxent River, Fort Worth and Marietta. A total of 31 separate costs for system development were received. Data requested from Palmdale was not available as one program manager retained no record of expenses and a second had since retired. Data was requested from two separate groups of a second

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aircraft manufacturer. One group designed data systems. The second group built the data systems. The both groups chose not to distribute their costs for proprietary reasons. Table 4-4 shows the results of collecting development costs.

Location Requests Costs ReceivedMarietta 2 1

Edwards AFB 2 27Seattle 2 0

Patuxent River 1 2Fort Worth 1 1Palmdale 1 0

Table 4-4Collected Results of Development Costs

The dollar amounts were collected from actual invoices filed away during the years of 1995 to 2009. Amounts from Fort Worth, Patuxent River and one Edwards AFB are exceptions with the data attained verbally from the project manager. Any other amounts for data center development spent during this period could not be verified. The amounts shown in Figure 4-2 are amounts reported by flight test programs that were spent per year from 1995 to 2010. Table 4-5 lists the yearly amounts collected during the research.

These amounts are reflective of the yearly amounts in Figure 4-2. The amounts include replacement of systems where old systems were discarded and new systems with current technology were purchased as the replacement. Costs include hardware,

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software and licenses purchases. No labor costs are included in the amounts shown. Maintenance of the systems is not a factor in showing the development costs and therefore not included in the data collected. Forced upgrades are included for the year 2000 to accommodate Y2K software purchased. System development costs collected were for new data centers mixed with upgrade costs for the data centers.

Figure 4-2Data Center Development Costs

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YEAR SITE COSTS

1995 Marietta $113,023

1995 Edwards AF Base $3,355,000

1997 Edwards AF Base $350,640






1998 Marietta $549,850



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2000 Patuxent River $1,000,000





2006 Fort Worth $3,600,000


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2008 Patuxent River $900,000


Table 4-5Yearly Costs for Data Center Development

Collecting relocation stress levels

Three methods of data collection were used for a total collection of 35 completed survey forms. Emails to remote engineers, Interview requests from engineers local to the researcher and web page requests for engineers to complete the survey form comprise this number of surveys. Interviews returned the highest number of surveys; emails returned a lesser amount although only two less than the interview method, web page response returned the smallest amount of data.

A total of 26 interviews were requested from local engineers. From this amount 10 engineers responded indicating no past experience with company relocations. The remaining 16 engineers admitted to company relocations and consented to an interview. Data collection from interviews was 61.5 percent successful. A total of 152 emails requesting relocation data were sent to four remote flight test sites at Fort Worth, Marietta, Georgia and Patuxent River, Maryland. The return rate was 14 from all three locations or 9.25 percent.

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A web page was created at http://www.vickersstudent.com. This web page received 152 visits with five survey forms filled out for a 3.2 percent return rate. Total participants requested for the survey was 330 for 10.6 percent success. Total response to the requests in Figure 4-3 demonstrates the correlation of results from the three methods of data collection.

Figure 4-3Survey collection

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Research results

Relocation

The length of flight test careers reported by the FTEs in all 35 surveys ranged from a minimum of two years to a maximum of 40 years. Per engineer the minimum number of relocations was one and the maximum number of relocations 21 with the mean of 4.29 relocations (Table 4-6). Using the mean value of 4.29 for the number of relocations from the thirty-five engineers surveyed and the value of $38,000 as the medium expense for relocation the total amount spent on those surveyed was $5,705,700.

Applying the same formula to the FTE levels shown in Chapter one Figure 1-3 is calculates the maximum amount possibly spent during this EMD phase for one program for relocation expenses. The mean amount based on the FTE level relocating for this one program can be calculated;

Where:

n = medium amount spent

FTE_level = 200

Relocation_medium_expense = $38,000$

Mean_number_career_relocations = 4.29

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n = FTE_level * Relocation_medium_expense

n = $7,600,000

Based on the medium number of relocations per engineer spanning the engineer’s career the engineer’s company is spending approximately $32Mil on relocation expenses over the careers of this FTE level. This calculation is arrived at with the following:

n = FTE_level * Relocation_medium_expense * Medium_number_of_relocations

n = $32,604,000

Table 4-6Career Years versus Relocations

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Stress measurements

As mentioned in Chapter 3 the purpose of measuring the stress on FTEs resulting from company relocations is to determine if the engineer’s company can experience revenue loss from decrease productivity. Chapter five will analyze these results in comparison to Dr Sheldon Cohen’s data on stress levels. The level for stress recorded by Doctor Cohen’s research was 12.9.

Doctor Cohen’s measured level can be compared to this researcher’s data showing the median in 1stress level, before relocation, to the median in 2stress level, during relocation. The measured median stress level of 13.0 for FTEs before the relocation is consistent with Dr Cohen’s recorded stress level. The FTE 1stress level median increased five points to a value of 18 measured in 2stress level. The histogram of 1Stress level in Figure 4-4 demonstrates 37% below, 17% equal to and 46% above of participants in comparison to Dr Cohen’s recorded level. These values are the baseline to compare with the 2stress levels for the same 35 participants during the relocation process.

The frequency in Figure 4-4 is the number of times the stress level occurred for the participants. During the relocation, there is an increase in stress shown in 2Stress level Figure 4-5. This data is reported in Table 4-9 as 23% below, 6% equal to and 71% above Dr Cohen’s stress level. Differences in the 35-participant’s stress before relocation and after relocation are demonstrated in table 4-8.

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This data from the 35 surveys show four participants who indicated a reduced stress during the relocation. Six participants reported no increase in stress and twenty-five participants experienced increased stress. The percentage is 11.4% with less stress, 17.25 without stress and 71.4% experiencing increased stress. Calculating the impact on the FTE level in Figure 1-3 of 200 for the EMD phase of one program and assuming all 200 relocated the number of engineers possibly stressed by relocation can be calculated at 142.8 FTEs.

FTE no stress = 10

FTE stress = 25

FTE_level = 200

N = percentage of increase

N1 = FTE Stressed

N = FTE no stress / FTE stress = 71.4%

N1 = N * FTE_level = 142.8 FTEs

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Table 4-7Median Stress Levels

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Figure 4-4Stress level before relocation

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Figure 4-5Stress level during relocation

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Valid Frequency Percent %Valid Cumulative%

-7 1 2.9 2.9 2.9-6 2 5.7 5.7 8.6-5 1 2.9 2.9 11.40 6 17.1 17.1 28.61 7 20.0 20.0 48.62 3 8.6 8.6 57.14 3 8.6 8.6 65.76 3 8.6 8.6 74.37 2 5.7 5.7 80.08 2 5.7 5.7 85.79 1 2.9 2.9 88.6

11 2 5.7 5.7 94.312 1 2.9 2.9 97.113 1 2.9 2.9 100.0

Total 35 100.0 100.0

Table 4-8Differences in Total Stress

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Table 4-9Participants Stress Level during Relocation

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Limitations affecting the findings

Limitations discussed in Chapter One considered the possibility of project managers not keeping budget records from previous data center developments. The results of collecting budget amounts proved this limitation to be true as the number of sites contacted was six and sites responding were three for a 50% success. The number of requests for data was nine and collected was ten due to Edwards Air Force Base providing eight data inputs.

Four project managers either did not retain the development amounts or refused to supply the data. Collection of stress survey data relied on participant recollection from past company relocations. All participants interviewed gave no indication of failure to remember events before or during their relocation. Response using a web page proved to be limited as only 3.2 percent of the people visiting the site filled out and submitted the survey. Limitations on email returns were better than the web site although the participants were contacted directly using their email addresses. The return rate using email was 9.25 percent or three times greater than the web site. The only limitation affecting interviews with FTEs were ten who indicated no previous experience with company relocation. These engineers were hired locally for the aircraft project.

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Analysis of the research questions

RQ1: What are the budget effects of data center development at various flight test sites to flight test programs?

Discussion:

The budget effects on flight test programs to develop data processing systems are supported in literature to show development cost ranging from $1,000,000 to $3,484,000. Research for this research shows the value as high as $11,160,000 with four costs exceeding the literature maximum of $3,484,000. A total of 26 cost items collected during this research as reflected in Table 4-5 demonstrates a continual amount of program dollars spent at four test sites.

RQ2: Does the FTE experience the harmful effects of increased stress which could lead to productivity decline and higher employer cost?

Discussion:

This research collected stress data during flight test relocations with a high stress value of 18 on the PSS. This is a 38.5% increase above the level stress level of 12.9 established by Doctor Cohen’s research. Literature review (IMPACT Group, 2003) states a high level of stress can produce family stress and possible loss to the employer of six months of the employee’s productivity. Given the mean wage of an FTE as reported by the Bureau of Labor Statistics (2002) of $45.18 the predicted loss to an employer over six months would be greater than $43,000.

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RQ3: Does technology exist to support consolidating data processing of numerous flight test programs to relieve possible high stress effects and reduce the budget effects to flight test programs?

Discussion:

Enterprise methods of data center development follow the trends set by present information system technology. This trend is to consolidate data centers for efficiency of operation and savings on operation. The Symantec State of the Data Center Report (2008) mentions how 47 % of U.S. companies have consolidated using new technology. Brodkin (2008) wrote how only 14 % have no plans to consolidate. Data in Table 1-5 list corporations and the number of data centers the corporations have consolidated. The example set by enterprises can be used by flight test data centers to follow the same trend.

Summary of findings

Historical literature records a pattern of flight test data processing at the site of the flight test. Literature continues to record from the period of the Wright Brothers to the present day where multiple data centers are used in the processing of flight data. Theories on consolidation existed in the 1980s although the method of data processing continued to favor duplication of data centers rather than a method to consolidate various test site data centers.

Literature records the expenses of different flight test programs towards developing and maintaining the data centers.

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Results of this research show Flight test careers of the engineers supporting the data centers ranged from two to 40 years with 21 relocations of one engineer. The Mean value of relocations of all participants was 4.9. When this figure was calculated against the Mean cost of relocations the expense paid by a company would amount to $5,705,700. This cost increases to $32,604,000 when the cost of relocating 200 engineers at one site is considered. The high cost of flight test data center development can approach $13,000,000 as proven by literature and proving true Research Question 1.

The stress results showed an increased in the engineer’s stress level above previous research by Doctor Sheldon Cohen putting at risk a loss of productivity to the engineer’s company. Research Question 2 (RQ2) is confirmed by the stress results. A review of literature states how enterprises reduced their relocation expenses and employee relocation stress by consolidating data centers; which is a method flight test programs have not embraced. This data shows how flight test can consolidate with today’s technology proving Research Question 3 (RQ3) is true.

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CHAPTER 5: SUMMARY

This is the final chapter and begins by summarizing the purpose of this research as written in Chapter 1. The research methodology is analyzed in addition to an analysis of the limitations on the research. The research results stated in Chapter 4 are analyzed and the research compared to previous research. Based upon the analysis of the research results the null hypotheses were tested upon each hypothesis. This chapter concludes by discussing how future research should be conducted and the benefits of conducting future research.

Statement of the problem

Presenting the problem

The development of flight test data centers consumes tens of millions of dollars in resources. These resources as stated in Chapter 1 consists of man hours spent on system design, software creation, software purchases, hardware purchases, hardware integration and labor for system testing. Added to this is the cost for replacement hardware and software to refresh the system in conformity to a planned System Development Life Cycle.

A convention of duplicating data processing dates back to the era of the Wright brothers when data was analyzed at the test site. Today separate data centers are created whenever a government contract is issued to an aircraft company for design, development and production of military aircraft. Government

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contracts are not the only source of aircraft programs as aircraft companies build commercial aircraft and duplicate data centers for the testing of the aircraft. As an example, Lockheed Aeronautical spends duplicate money for flight test data centers at the following locations.

Marietta – F22 aircraft

Edwards Air Force Base – F16 aircraft



Palmdale – Advanced Development aircraft

Fort Worth – F35 aircraft

Fort Worth – F16 aircraft

Marietta – C130 aircraft

Patuxent River – F35 aircraft

Added to development costs are the repeated costs of staffing flight test engineers at each test site to analyze flight test data from the data center. Flight test programs ramp up the amount of FTE and after the initial phase of flight testing is completed the majority of FTE are moved to another project often by geographical relocation. The effects on employee due to relocations were studied by a number of researchers such as

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Anderson & Strark (1988), Fliege (2005) and Cohen (1988). These researchers showed how relocations can cause stress on employees.

This stress can be sufficient to cause loss in an employee’s production sometimes extending to six months. The experienced stress causes some employees to reject relocation offers from their company. Loss in program dollars is another cause of relocation. This expenditure is the cost of relocating each FTE similar to the expense experienced by enterprises of relocating employees to support multiple data centers.

Enterprises recognize the high expenses involved in duplicating data centers and research shows how enterprises consolidate the data centers in an effort to reduce overhead costs. Flight test data centers continue to be duplicated based on the convention set forth by aircraft development history regardless of technology.

Purpose of the study

Chapter 2 presented how enterprises have changed their method of data center operations over the past. Enterprises have embraced new technology as a means of either consolidating data centers or duplicating data centers based on the current level of technology. A purpose of this study is:

1. To show the high expenses associated with employee stress on relocation to support multiple flight test data

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centers, the high relocation expenses for FTE and the high costs spent on data center duplication.

2. To awaken flight test program managers and data processing managers to the negative effects of not embracing current technology to consolidate and to break the current convention of continued duplication of data center development.

Aircraft programs exam new methods of improving flight test data for example the INET program which uses new technology to gain efficiency and lower cost. The INET methodology is presented each year on technical presentations at the International Telemetry Conference. This type of program is targeted towards the efficiency of data transmission bandwidth and does nothing to address the redundant cost of data center development.

Analysis of the methodology

Designs employed

Two instruments were used in the collection of data. The first instrument was a basic table of two columns and multiple rows (Survey form 2). The first column showed location and the second column listed the data center development costs. No program names were used to avoid company proprietary rights. The table was simple yet ineffective in collecting data due to reluctance of program managers contacted to fill in the tables. Substitution for this instrument was the collection of system invoices for purchases to develop flight test data centers.

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The purpose of the using the second instrument, the

Perceived Stress Scale (PSS), was to use a valid scale proven by the research of Dr Sheldon Cohen (Survey form 1). The design of the scale obtained qualitative answers and converted the answers to quantitative figures suitable for graphical analysis. This design was successful in providing data showing an increase in employee stress due to company relocations to support data centers.

Research methods

The methods used in this research provided data on data center development and employee stress due to company relocations in support of flight test data centers. Four methods were used; emails to program managers, emails to FTEs, web site collection of stress data and interviews with FTEs. Program managers were not responsive to filling out the table with development costs. As an example, the Palmdale program manager did not keep any development data from previous data center projects. The second manufacturer contacts did not respond to the inquiry using the table, possibly to avoid any type of company proprietary rights. The alternative method of research was to locate system invoices stored in file cabinets and locate Internet sources of public data.

This research method was successful in locating 31 separate

costs for system development allowing graphing of development costs (Figure 4-2), tabling of locations costs (Table 4-4) and tabling of cost per year (Table 4-5). Results from the research

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methods to collect stress data followed predicted results described in Chapter 3 Methodology. Approached face-to-face FTEs were very willing to submit to an interview regarding relocation stress conditions. The interview method returned the highest amount of data as shown in Figure 4-3. Emails returned the next highest amount of data followed by a web page on the Internet.

Analysis of the research limitations

Development costs

The costs collected are sampled costs of budgetary amounts spent to develop and maintain a flight test data center during portions of the data center life cycle. The amounts include initial costs for first time development and later costs for developing replacement of legacy systems. The costs are not all the amounts spent per year only the amounts located on discovered invoices.

The amounts are reflective of a high cost to develop any flight test data center and pertain to only hardware and software purchases including on some invoices software licenses for third party applications. Limitations to these amounts are the annual renewal of operating system software and special software application licenses not shown in the invoices. Contractual maintenance per year and parts replacement is further limitations on collecting cost data.

Labor to software design, hardware specification determination and system testing add to the development cost and are not included in the data. Operation of the data center at each

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site is more limitations not included in the data. Most sites run a three shift round the clock operation during the first phase of aircraft development. These labor costs are redundant to each flight test site and not shown in the data.

Relocation stress

Collecting relocation stress data to determine productivity lost was limited by the span of relocations per FTE. The minimum number was one while the maximum relocations reported were 21. This prevented an accurate numerical figure for relocation per employee as the number of FTE surveyed was 35. The mean was calculated with the result of 4.28 relocations per employee.

Considering the reported career span was two to 40 years the expected number of relocations per employee over a 40-year career was 4.28 relocations. The amount of relocations limited how the stress data was collected so the FTE was instructed to report on a worse case relocation. Testing one relocation event limits a range of test results for multiple relocations. Therefore, only a worst-case relocation was tested.

Personal, job and family life can affect the measuring of relocation stress. To overcome this limitation the FTE was surveyed twice. One survey was for stress before relocation and a second survey for during the relocation. The difference in stress levels was compared with Dr Cohen’s level of researched stress and this difference was successful in giving an indication of a stress level where company productivity could be lost

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(Table 4-9). Data collected from the survey was limited in accuracy due to the time span between relocation and survey. This span was over years and required the subject to remember events for answers to the survey.

Unanticipated findings

Unanticipated was the peak number of relocations at 21. This peak number if linear would indicate a minimum time between relocations as 1.9 years based on a 40-year flight test career. Due to the actual non-linearly the number of years in the flight test career did not directly correspond to an increase in relocations as expected. Table 5-1 shows how the number of relocations was dispersed from one career year to forty career years. The assumption is the FTEs worked at some flight test programs were longer than other programs.

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FTE Years Relocations FTE Years Relocations2.0 1 19.0 15.0 1 20.0 15.0 2 20.0 48.0 1 20.0 219.0 1 20.0 1

10.0 12 20.0 510.0 8 22.0 610.0 3 23.0 510.0 7 24.0 210.0 4 25.0 310.0 1 25.0 311.0 1 25.0 313.0 3 25.0 413.0 2 25.0 226.0 11 28.0 326.0 6 30.0 127.0 9 35.0 640.0 6

Table 5-1FTE Career Years and Relocations

Analysis of results

Redundant costs

The relocation of a FTE adds to the expense of the FTE’s last relocation. Figure 4-1 shows the amount spent for one FTE and the redundant costs accumulating at ten relocations. There

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were 12 participants out of the 35 participants exceeding the mean location of 4.29. This means an aircraft company can spend above the mean on relocation funds for 34.3% of the flight test engineers the company relocated throughout the FTEs career.

N = 35

Exceeding_Above_Mean = 12

Spending above the mean = 12/35 = 34.3 %

If the participants were employed by one company with each FTE relocated once the cost to the company cost can be calculated.

N = 35

Relocations = 1

Relocation_medium_expense = $38,000

Relocation expense = N * Relocation *

Relocation_medium_expense

Relocation expense = $1,330,000

Changing the formula to reflect all the 35 participants and their total relocations the redundancy is apparent. This redundancy in relocation in support of redundant data centers increases by a factor of 150 as shown in the following formula.

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Relocations = 150

Relocation_medium_expense = $38,000

Relocation expense = Relocations *

Relocation_medium_expense

Total relocation expense = $5,700,000

The results of data collected at the locations in Table 4-5 show annual costs range from a minimum of $73,660 in the year 1997 to a maximum of $11,160,000 in 1999 for support of flight test data centers. The average for the Edwards Air Force Base invoices is $2,008,893 per invoice. The amounts shown in Table 4-5 reflect the redundancy in data center development.

Relocation stress

Research results in Chapter 4 show 77 percent of subjects whose survey recorded relocation stress. This percentage is very close to the percentage of 75 % in research reported by Munton (1990) of employees being stressful after relocation. Chapter 4 results show 28.5 percent of subjects with stress indicators above Dr Cohen’s level of 12.9 for stress. The deduction based on the percentage of 28.5 percent of FTEs relocated is this percentage will experience very high stress.

Table 4-7 records a medium stress level of 13 before relocation and is compatible with Dr Cohen’s recorded level for stress of 12.9. The medium level of 13 recorded as 1stress level

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increases sharply to a medium level of 18 for the 2stress level exceeding Dr Cohen’s level by a factor of 1.38. Relocation 2stress level with a maximum of 27 exceeds Dr Cohen’s level by a factor of 2.08. This maximum level if compared with the maximum relocations of 21 and maximum career years of 40 as shown in Table 4-6 suggest a maximum worse case relocation could occur every two years for 28.5 percent of FTEs relocated.

The high stress recorded makes possible an increase in FTE refusal to relocate and possible creation of family issues. The high stress will possibly cause loss of productivity to employer as defined by the research of the IMPACT Group (2003) described in Chapter 2.

Relationship to previous research

Consolidation of data centers

This research shows no attempt by the flight test community to consolidate data centers. This lack of attempt is due to the conventional methodology practiced by the flight test community to duplicate data centers regardless of current IT technology. Therefore, previous research on data center consolidation does not exist for comparison.

Existing research on consolidating enterprise data centers is available and the review of literature in Chapter 2 shows various authors stating their theories on the benefits of consolidation. These theories are shown in Table 2-4 for enterprise data centers. These theories can be compared to the flight test theories are shown in Table 2-3. The difference is flight test theories are

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system design in comparison to the enterprise theories regarding usability of systems. Only two authors, Strock and Weaver held the theory of consolidating flight test centers.

Employee relocation stress

The relocation stress of FTEs in support of data center processing has not previously been researched to show a potential for FTE productivity loss. Existing research oriented towards other occupations is available. The results of this research show the correlation of FTE stress to previous research on relocation stress to employees of other occupations. Table 5-2 shows how this relationship exists. The analysis indicates FTE relocation stress is similar to other occupations and FTEs can experience the same type of stress problems.

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Previous Research

Researcher Applicable to FTE?

Relationship

Multiple transfers, Loss of productivity

Manion & Rantz Ph D (1995)

YES Average 4.28 relocations per 40-year career. Maximum 21.

75% employees very stressful after relocation

Munton (1990)

YES 71.4% of FTEs stressed

80% to 100% experienced apprehension & anxiety

Manion & Rantz Ph D (1995)

Very Possible 71.4% of FTEs stressed

Medical conditions, emotional instability & behavior problems

Mumma (2001)

Very Possible Max stress level of 27 exceeds Dr. Cohen’s level of 12.9

Family teenaged social relationships impaired due to geographical moves

Anderson & Strark ((1988)

Very Possible Maximum of 21 moves

Table 5-2Relationship to Previous Research

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Analysis of the hypotheses

Hypothesis 1 (H1)

H1 as stated in Chapter 1 is “Duplication of data center development will show a redundant cost to make data centers operational.”

Discussion:

The cost for data center development are presented in Figure 4-2 from 1995 through 2010 and peaked at over $12,000,000 for a single year. Table 4-5 lists 26 separate development cost for test sites at Edwards Air Force Base, Patuxent River, Fort Worth and Marietta. These costs are representative of redundant costs required to develop and support flight test data centers at the flight test sites with a peak of $11,160,000 at one test site.

Savings can be achieved by consolidating flight test data processing from all programs at one central data center. This savings would eliminate the duplication of employee technical training, software licenses, hardware maintenance, management staffing and labor used for data center development.

Conclusion:

This research shows the convention of duplicating flight test data centers duplicates the expenses to develop and operate a flight test data center. Based on the results of the duplicated development costs listed in the research data shown in Table 4-2 the null hypotheses is true.

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Hypothesis 2 (H2)

H2 as stated in Chapter 1 is “Results of engineers reporting relocations will show high stress data similar in pattern to empirical relocation research on employee stress.”

Discussion:

This research collected data showing FTEs can expect multiple company relocations throughout their flight test career. The data shows FTEs past relocations produced stress with some engineers experiencing over twice the established minimum stress level set by Dr Cohen. The Norm Table for the PSS 10 item inventory shown in Attachment 5 records a mean stress level for males of 12.1 and for females a mean stress level of 13.7 for an average of 12.9.

This research on FTEs recorded a mean of 13 in 1stress level, before relocation, (Figure 4-4) for a 1 % difference from Dr Cohen’s data. The maximum relocation 2stress level of the FTE stress data was 27 for an increase of 209% above Dr Cohen’s average of 12.9.

Conclusions:

Based on the high stress levels of data collected above Dr Cohen’s stress level the null hypothesis is proven to be true. These high levels are recorded in Table 4-8 for 35 participants in the survey. This table records the differences in stress representing data from FTEs before a relocation and stress data after a relocation.

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Hypothesis 3 (H3)

H3 stated in Chapter 1 “Loss of productivity can be affected by engineer’s stress due to relocation.”

Discussion:

Empirical research has shown how a person’s equilibrium can be affected by relocation (Moyle and Parkes, 1991). This physiologic condition can develop into Relocation Stress Syndrome (Manion and Rantz Ph D., 1995) and possibly create a Circle of Chaos where the employee’s marriage disintegrates (IMPACT Group, 2003). Based on the research data showing 71.4% of FTEs stressed, stress levels exceeding twice established minimum levels and relocations peaking at 21 there is a possibility of an aircraft company losing FTE productivity during flight test. Based on a mean FTE wage of $45.18 per hour (Bureau of Labor Statistics, 2008) this projected loss over a six-month period could be greater than $43,000

Conclusion:

The null hypothesis is true based on a high probability of productivity loss due to multiple relocations resulting in high stress as shown in the FTE data and the amount of productivity loss as calculated from the Bureau of Labor Statistics (2008).

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Hypothesis 4 (H4)

H4 in Chapter 1 states “Existing technology used by enterprises can provide a means to consolidate flight test data centers.”

Discussion:

Research of literature shows the evolution of flight test testing and the slow transition of manual data processing to interactive processing (Chapter 2, Table 2-2). This convention of duplication the methods of flight test data processing is proven to continue as illustrated in the duplicated expenses of development shown in the Air Force Budget Items in Table 4-1. This duplication of effort and funds shows no attempt by flight test to use new technology for purposes of consolidating data centers. This is in contrast to the literature review data in Table 1-5 showing how enterprises have embraced technology to consolidate their data centers.

Conclusion:

Based on collected data showing continuation of flight test duplication of development funds in contrast to researched literature showing successful enterprise data center consolidation the conclusion is flight test data centers can use methods similar to enterprises to consolidate data centers. Therefore, the H4 null hypothesis is true.

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Discussion and future research

Present model

The success of enterprise data centers consolidating as shown in Table 1-5 can be applied to flight test data centers. There is a difference to recognize when describing a suggested model. Enterprise data centers before consolidating were copies of each other. Each data center contained the same functions and used similar databases to perform the same operations for users.

Flight test data centers are different in operation as each data center is designed based on the flight test specifications of the tested aircraft. Aircraft designs require differences in the type and number of transducers to sample functions of the aircraft and therefore the flight data must be processed in separate data centers. This is a theory held by Smith, Matthews and Van DerVelde as shown in Table 2-3 and continues today.

Due to this theory, the convention of separate data centers continues although no person has created a model to consolidate and accommodate different aircraft designs. This conventional theory can be modeled as shown in Figure 5-1. Each site is structured with an instrumentation and data processing department creating a separate silo independent from other test site data centers.

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Figure 5-1Present duplication of Flight Test Data Centers

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The implications of this model are the continual duplication of:

1. Databases2. Tape backups3. Data processing engineers4. System administration engineers5. Data base administration engineers6. Company paid schooling for system and database

administrators7. System development time, resources, and labor8. System licenses, hardware, and software purchases.9. Data processing managers and supervisors10. FTE located at each data center11. Data center facility

The redundancy becomes apparent when each attribute of data center development at each site is considered. Databases require high capacity and fast servers capable of outputting information to hundreds of remote and local users. The database licenses must be renewed periodically at a cost to the data processing department.

The database must be administered by experienced database administrators who are paid at a senior engineering level. Partial backups must occur daily with full backups every week. This process adds to the equipment purchases for tape robotic hardware and software with software license purchases. System administrators must be experienced in the system platform and paid at a senior level. Data processing engineers must be more

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experienced than enterprise data processing operators as the skill for flight test data processing involves data analysis and a background in telemetry theory.

This skill takes years to attain as data processing engineers must collaborate with flight test engineers to deliver a quality product. At each site system administrators, data processors and database administrators are often sent to company paid schools such as UNIX, Server2003, VMS and Oracle which adds to the redundancy of data center development. Management staff is duplicated with mid-level data processing managers and skilled lead data processing supervisors each drawing high salaries. Flight test engineers responsible for analyzing the flight data are moved to each location of a test site adding to the cost of relocation and loss of productivity due to relocation stress.

Proposed model

Centralizing a flight test data centers is possible and proposed using today’s technology. A central location can accommodate one large data center capable of processing all data from numerous aircraft programs. One group of FTEs can support multiple aircraft programs without relocating their homes and families to another geographical location. Data operators support all programs and not dedicated to one program.

When aircraft programs go into production and flight testing priority decreases the FTE is simply given tasks to analyze data from another program avoiding relocation. Data processing uses virtual systems by movement of aircraft processing to other

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hardware during system upgrades or failures. Legacy systems can be reloaded anytime in the future to process stored data from programs shutdown in the past.

The data processing departments can concentrate system administration to only the processing systems. Databases, database servers, offset backups, network maintenance and disk storage requirements move into the responsibility of the corporate IT Company relieving the data processing department of funding schooling, extra manpower and much software licenses.

An example is moving these IT tasks from a data processing department to a corporate IT business unit. Each test site retains a small group of FTE for safety of flight during aircraft testing. Instrumentation engineers and engineers supplying real time data upload the aircraft test data over a virtual private network to a data mart within a data warehouse corresponding to the aircraft program generating the test data. Data operators process this data and store the derived data at the same data storage site.

Database servers can run multiple instances of Oracle to support each aircraft program. Offsite backup can be performed at a central location. Tape backups can be located anyplace geographically. All users are given access by program authority to required program data. Figure 5-2 models the consolidated methodology.

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Flight Test Engineers Data Processing Engineers

Aircraft Program 1

Aircraft Program 2

Aircraft Program 3

Aircraft Program 4

Aircraft Program 5

Data Processing ManagerSystem Administrator

Centralized Data Center

Data Warehouse

Data Mart Prog 2

Data Mart Prog 3

Data Mart Prog 1

Data Mart Prog 4

Data Mart Prog 5

Aircraft Data UploadTest Site 1





Remote Data

Backup

Remote Users

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Figure 5-2Proposed model of Centralization

Future research

This research has presented data showing how the duplication of flight test data centers is requiring a duplication of funds spent and how the relocation of FTEs is causing stress and possible loss of productivity. Further research is needed to survey a larger number of FTEs using Human Resources involvement to collect larger amounts of data on actual relocation costs and to correlate loss of labor time to relocation events.

Data using psychological surveys of employee family stress before a relocation event and conducting the survey after the event can produce more data on employee relocation stress. This survey will need to be conducted over a number of years with employee information provided by Human Resources. Data on network timing of data transfer time across a network must be researched and a determination of the time for data ready for data analyzing by FTE predicted. Security requirements must be researched when the network is used by more than one security classification and how this network can be security separated by security classification levels, possibly by encryption of aircraft data.

Communication techniques need to be research on how remote data processing operators can continue collaboration with safety of flight FTEs and instrumentation engineers at each site, possibly by the technology of telepresence. Last future research is

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needed on how to consolidate funding from multiple aircraft programs to the operation of a centralized flight test data center.

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ATTACHMENTS

Attachment 1: Survey form 1

This is a professional stress scale used here for the purpose of measuring the stress level of flight test engineers due to their relocation by the engineers company. All data is kept confidential and only used to complete a doctorate research. Please help by taking only a few minutes to fill out. Click Reply, X the boxes and Send to:

[email protected]

The scale can also be found at http://vickersstudent.com

(The links no longer existing, 2017)

Perceived Stress Scale

Initials (no name)________ Age____ Years in Flight Test ___ Married or Single?_____

Number of relocations while in flight test _____ Male or Female_____

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Discipline (FQ, Structures, etc. includes data processing and instrumentation) ___________

Two questionnaires were given with the same questions.

1) Remember your worse company relocation and answer for the month right before the relocation

2) Remember your last company relocation and answer for the period during the relocation

Question selections were:Never, Almost Never, Sometimes, Fairly Often, Very Often

Questions were:How often have you been upset because of something that happened unexpectedly?How often have you felt that you were unable to control the important things in your life?How often have you felt nervous and stressed?How often have you felt confident about your ability to handle your personal problems?How often have you felt that things were going your way?How often have you found that you could not cope with all the things that you had to do?How often have you been able to control irritations in your life?How often have you felt that you were on top of thing?How often have you been angered because of things that were outside of your control?How often have you felt difficulties were piling up so high that you could not overcome them?

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The PSS 1984 is used by permission of Sheldon Cohen, Mind Garden Inc

Perceived Stress Scale Scoring

PSS-10 scores are obtained by reversing the scores on the four positive items, e.g., 0=4, 1=3, 2=2, etc. and then summing across all 10 items. Items 4,5, 7, and 8 are the positively stated items.

The PSS was designed for use with community samples with at least a junior high school education, Items are easy to understand and the response alternatives are simple to grasp. Moreover, as noted above, the questions are quite general in nature and hence relatively free of content specific to any sub population group. The data reported in the article are from somewhat restricted samples, in that they are younger, more educated and contain fewer minority members than the general population. In light of the generality of scale content and simplicity of language and response alternatives, we feel that data from representative samples of the general population would not differ significantly from those reported below.

Conditions of Scale Use

Permission for use of the scale is not necessary when use is for academic research or educational purposes by Sheldon Cohen, http://www.psy.cmu.edu/~scohen/

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Attachment 2: Survey form 2

Program Manager,

This is a research survey to collect data for a doctoral research. Your assistance is collecting this data is requested and information you provide will be held in confidence. This survey collects data to determine the financial effects of developing post flight data centers.

Please indicate the location and cost to develop past and present data centers at flight test sites.

Location Amount12345

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Attachment 3: Permission for use of the PSS

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Attachment 4: Permission for use of the Norm Table

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Attachment 5: Doctor Sheldon Cohen’s Norm Table

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Attachment 6: Web site

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The IMPACT Group (2003). Reality Based Relocation. Retrieved January 20, 2009 fromhttp://www.the-impact-group.com/who/article/RA0010.HTM

Van der Velde,R.(n.d.) Historical Perspective, One Hundred Years of Flight Testing. National Aerospace Laboratory NLR.

Violino, B. (2009). Virtualization’s New Frontier. Strategic Technology. Retrieved December 15, 2008from the EBSCOHost database.

Weaver,H. (2007). Trends in Flight Test Data Requirements to Final Data. Society of Flight Test Engineers. Retrieved March 5, 2009 from http://www.sfte.org

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DEFINITION OF TERMS

Chief engineer A senior engineer within upper management who is responsible for all test engineers.

Classified data Flight test data given a very high security classification with strict regulations on handling and dissemination of data.

Consolidation Assembling multiple data centers into one central data center at one location.

Data analysis A method chosen to examine data from flight test aircraft to determine characteristics of a measurement.

Data center A data laboratory created to process flight test data. In this study it refers to the post-flight data center.

Enterprises Business companies outside the field of aircraft manufacturing and test flight.

EMD Test phase of F22 engineering, manufacturing and development. This phase of aircraft testing is where performance tests must be reached before the aircraft is acceptable by the customer.

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EMR A telemetry company created in 1947 to design and sell telemetry systems.

ERP Enterprise Resource Planning. A computer system integrated to serve all functions of an enterprise.

EUCON A core software technology developed by Lockheed-Martin developed as a method to processing telemetry data.

Flight test engineers Engineers within all disciplines of flight test data analysis including the engineers within the data center doing the data processing.

IRG 1588 Telemetry standard used to synchronize telemetry timing

Network A technology allowing computers to communicate with each other over distances.

Post-flight data center A data center processing flight data after the aircraft lands.

Parameter A measurement taken from a transducer physically placed on the aircraft.

PCM Pulse coded modulation. A form of telemetry digital encoding

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Real time data center A data center receiving real time data as the aircraft is in flight and processing this data.

Relocation The act of physically moving a flight test engineer and family away from his/her present living location to another geographical location to support flight test programs.

Relocation Stress Syndrome A syndrome which produces personal and family stress conditions due to relocating from one geographical area to another.

Telemetry Derived from the Greek word ‘tele’ meaning to communicate and the work ‘metry’ meaning at a distance. It is a technology where measurements can be sampled and analyzed at a distance.

Test site Location where a flight test team works together to maintain, plan, and analyze aircraft data.

Transducer A device which converts mechanical motion to a measurable voltage representing the motion of the device measured.

Unclassified data Flight test data given a very low security classification

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List of Tables

Table 2-1: Sources of Literature 23Table 2-2: Flight Test Programs 30Table 2-3: Flight Test Theories 31Table 2-4 Author’s Theories 40Table 2-5: Enterprise Examples of Consolidation 52Table 3-1: Question Values 63Table 3-2 Types of Analysis 73Table 4-1: Data Processing Expenses 78Table 4-2: Relocation Expenses 80Table 4-3: Enterprise Methods 83Table 4-4: Collected Results of Development Costs 84Table 4-5: Yearly Costs of Data Center Development 88Table 4-6: Career Years versus Relocations 91Table 4-7: Median Stress Levels 94Table 4-8: Differences in Total Stress 97Table 4-9: Participants Stress Level during Relocation 98Table 5-1 FTE Career Years and Relocations 111Table 5-2 Relationship to Previous Research 116

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List of Figures

Figure 1-1 Enterprise & Flight Test Data Center Differences3 Figure 1-2 Data Center Development Methodology 6Figure 1-3 Flight Test Engineer Levels 9 Figure 1-4 Lockheed Flight Test Sites 12Figure 2-1 Literature Review Outline 21Figure 2-2 Conceptual Map 26Figure 2-3 Flight Test Collaboration Process 45 Figure 4-1 Cost of Multiple Relocations Per Engineer 81Figure 4-2 Data Center Development Costs 85Figure 4-3 Survey Collection 89Figure 4-4 Stress Level Before Relocation 95Figure 4-5 Stress Level During Relocation 96Figure 5-1 Present duplication of Flight Test Data Centers 122 Figure 5-2 Proposed model of Centralization 126

List of Attachments

Attachment 1: Survey form 1 129Attachment 2: Survey form 2 132Attachment 3: Permission for use of the PSS 133Attachment 4: Permission for use of the Norm Table 134Attachment 5: Doctor Sheldon Cohen’s Norm Table 135Attachment 6: Web site 136

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