Bb Wk1 220 Measure Phase Intro

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Black Belt Training Ford Proprietary

Copyright © 2005-2006, Ford Motor Company – All Rights Reserved

Introduction

toMeasure



Introduction to Measure

Black Belt Training Slide: 1

The Measure Phase establishes techniques for collecting dataabout the current performance of the process identified in the

Define Phase.

The main purpose of the Measure Phase is to:

Determine what is known about the process

Identify key measures based on

Voice of the Customer (VOC)

and the Project Charter

Measurement System Analysis

Collect data

Calculate process capability

Measure Phase





Measure Phase Objectives

Define in-process measures for the specifications aligned to theVOC and organization’s key business plan objectives

• Note: In the absence of customer defined specifications, a Design for Six-Sigma (DCOV) project is required, using a systems view (i.e.,systems engineering/business approach)

Identify the types, sources, and causes of variation in processes

Determine data requirements for a 6-Sigma project

Develop a Data Collection Plan

Perform Measurement System Analysis (MSA)

Conduct data collection

Ensure process is in control before determining the baselinecapability as a Sigma value

Complete the first part of the FMEA on the current process





Achieving the Measure Phase Purpose

In order to complete the Measure Phase, the Project Team mustaccomplish the following:

Identify the Potential Xs.

Describe the process performance quantitatively (measured or

counted units).

Develop and validate the measurement system.

Determine baseline capability of the process as a sigma value.





Measure Phase Outcomes

A plan for collecting data that specifies the type of data needed,key measures to provide the data, and the techniques for

collecting the data.

A validated measurement system that ensures the accuracy

and consistency of the data collected. Sufficient data for problem analysis.





Measure Phase Objectives

Define process measures

Identify the types, sources, and causes of variation in processes

Determine data requirements for a 6-Sigma project

Develop a Data Collection PlanPerform Measurement System Analysis (MSA)

Conduct data collection

Determine the baseline capability as a Sigma value

Complete an FMEA on the current process





Measure Phase Elements

Collect Data and

Assess Capability

Identify Measurementand Variation

Determine Data Type

Develop DataCollection Plan

Perform MeasurementSystem Analysis

Complete FMEA

Let’s review what we learned in Green Belt training…





Identify Measurement and Variation

DetermineData Type

Collect Dataand AssessCapability

Complete FMEA

Develop DataCollection

Plan

IdentifyMeasurementand Variation

PerformMeasurement

SystemAnalysis





Identify Measurement and Variation: Definition of Measure

A measure describes the quantity,

capacity, or performance of a product,

process, or service, based onobservable data.

DetermineData Type

Collect Data andAssess

CapabilityComplete FMEA



PerformMeasurement

System Analysis





Identify Measurement and Variation: Measurement Usage

Measurements can be made of the inputsto the process, the process itself, or the

outputs of the process.

Inputs

Inputs

Process

Inputs

Outputs

Outputs

DetermineData Type





PerformMeasurement

System Analysis





Identify Measurement and Variation: All Processes Have

Variation

All repetitive activities of a process have a certain amount

of fluctuation

Input, process, and output measures also fluctuate

This fluctuation is called variation

Measurement

Time

DetermineData Type





PerformMeasurement

System Analysis





Identify Measurement and Variation: Shift & Drift in Processes

Data collected over ashort period of timeindicates a fairly capable

parking process

Over time, shift and driftin the parking process

produce data thatindicates a less capable

process

DetermineData Type





PerformMeasurement

System Analysis





Identify Measurement and Variation: Sources of Variation

Machines

Materials

Methods

Measurement

Mother Nature

People

PR

OCE

SS

DetermineData Type





PerformMeasurement

System Analysis





Identify Measurement and Variation: Why do we care about

Sources of Variation?

In 6-Sigma, variation is the enemy

We reduce variation by dealing with the sources

We need to understand the primary sources of variationWe also need to assess how controllable each source of variation

is:

Effort of control

Cost to control

DetermineData Type





PerformMeasurement

System Analysis





Determine Data Type

DetermineData Type


Complete FMEA


Plan


PerformMeasurement

SystemAnalysis





Determine Data Type: Definition of Data Types

FAIL

PASS

Electrical Circuit

Attribute

NO-

GO

G

O

QTY UNIT DESCRIPTION TOTAL

1 $10.00 $10.00

3 $1.50 $4.50

10 $10.00 $10.00

2 $5.00 $10.00

SHIPPING ORDER

Error

DetermineData Type





PerformMeasurement

System Analysis

Thermometer

Time

Variable

Caliper

TEMPERATURE





Variable

Determine Data Type: The Advantage of Variable Data

DetermineData Type





PerformMeasurement

System Analysis





Develop Data Collection Plan

DetermineData Type


Complete FMEA


Plan


PerformMeasurement

SystemAnalysis





Collect Data and Assess Capability: Perform Data Collection

Data collection is a process by which we

accumulate enough information to

calculate the current process capability(baseline) and identify the potential

causes of the problem.

DetermineData Type





PerformMeasurement

System Analysis





Develop Data Collection Plan: Definition of Data Collection

Plan

A data collection plan is the documentation of:

What data will be collected?

Why it is needed? Who is responsible?

How it will be collected?

When it will be collected?

Where it will be collected?

DetermineData Type





PerformMeasurement

System Analysis





Develop Data Collection Plan: Purpose of a Data Collection

Plan

A well-prepared data collection planhelps ensure successful analysis of the

problem by making sure there is

useful data collected.

DetermineData Type





PerformMeasurement

System Analysis





Develop Data Collection Plan: Data Collection Plan

Ask the following questions:

What knowledge is desired about the process?

What are the potential sources of variation in the process? (xs)

Are there cycles in the process?

Is data available? If not, how will the data be collected?

How much time is needed to collect data to capture a true picture?

Who will be collecting the data?

Are the operational definitions for measurement detailed enough?

How will the measurement system be tested?

Where could data collection errors occur? How will data collectionerrors be handled?

How will the data be displayed?

DetermineData Type





PerformMeasurement

System Analysis





Collect Data and Assess Capability: Training Data Collectors

To ensure the best possible data quality:

Properly train the data collector(s)

Monitor the data collection process frequently

Check whether the data looks reasonable, and challenge the dataresults if it doesn’t

Collect several small samples over time rather than one large

sample at a single point in time

Ensure measurements remain stable and consistent

DetermineData Type





PerformMeasurement

System Analysis

I d i M





Develop Data Collection Plan: Data Collection Tools

Data collection tools include forms,

checklists, checksheets, or other kindsof record-keeping devices used to

record data.

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Develop Data Collection Plan: Why Develop Data Collection

Tools?

Helps organize data collection

Helps standardize the data collection process

Accommodates stratification Accommodates sampling

Allows the Project Team to collect comments and exception data

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Develop Data Collection Plan: Developing Data Collection

ToolsA creative approach can help ensure proper data collection,e.g., diagrams or pictures rather than text.

Data collection tools should be simple to use and understand

The form should be tested before it is fully implemented

The tool should include only the information needed

The tool should include instructions on how to record data – using

examples whenever possible

The tool should provide space for comments and exception reporting

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Perform Measurement System Analysis: Definition of



(MSA) is a quantitative evaluation of the tools and process used in

making data observations.

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Perform Measurement System Analysis: Purpose of a


The purpose of performing a

Measurement System Analysis is toensure the information collected is a true

representation of what

is occurring in the process.

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Perform Measurement System Analysis: Operational

Definitions

The measurement system will be

set up using operational definitions

constructed by the Project Team toensure that all measurement takers

completely understand what is expected

during the data collection phase.

DetermineData Type





PerformMeasurement

System Analysis

I t d ti t M





Perform Measurement System Analysis: Walking the

Process

“Walking the process” is necessary when

developing a new data collection process

to ensure that all measurement takers

understand how to properly evaluate the

characteristics of interest.

DetermineData Type





PerformMeasurement

System Analysis






Perform Measurement System Analysis: How to

“Walk the Process” Train data collectors prior to beginning the data

collection activity

Follow the data collection process from beginning to endto ensure data is being properly collected

Continue “walking the process” until all data collectors

effectively understand the new measurement process

Assess the accuracy (if the new measurement process

does not include a calibration requirement)

Assess variability due to the measurement system

DetermineData Type





PerformMeasurement

System Analysis






Perform Measurement System Analysis:

Quantitative Aspects Accuracy – how close the indicated value is to the true value

Stability – ability to produce the same results over time

Linearity – difference in accuracy across the range of measuresRepeatability* – variability in values when everything else is held

constant

Reproducibility* – variability in values associated with different

people measuring the same elements under the sameconditions

* Green Belt training focused on Repeatability and Reproducibility

DetermineData Type





PerformMeasurement

System Analysis






Perform Measurement System Analysis: Measurement System

Analysis Summary At the conclusion of the Measurement System Analysis,the Project Team should know that:

The measurement system is capable of gatheringdata that accurately reflects variation in the process.

If there is measurement error, they should know how

big it is and have a method of accounting for it.

Measurement increments are small enough to show

variation.

Sources of measurement error have been identified.

DetermineData Type





PerformMeasurement

System Analysis






Collect Data and Assess Capability

Capability Analysis is the study of how well a process is

performing in meeting the expectations of customers

(CTQs).

DetermineData Type


Complete FMEA


Plan


PerformMeasurement

SystemAnalysis






In Consumer Driven 6-Sigma, process performance is reported

using the universal measure of Sigma value.

VARIABLE

DATA

CP CPK

PP PPK

DPUPPM DPMO

TYPE OF DATA TYPE OF METRIC

ONE

UNIVERSAL

METRIC

ATTRIBUTE

DATA

Collect Data and Assess Capability: Relationship to ProcessPerformance Metrics

DetermineData Type





PerformMeasurement

System Analysis






Collect Data and Assess Capability: Differences in ProcessCapability Over Time

Short-TermProcess Data

Long-TermProcess Data

DetermineData Type





PerformMeasurement

System Analysis






To calculate DPMO use the formula:

Collect Data and Assess Capability: Calculating ProcessCapability Using Attribute Data

The final step is converting DPMO to a Sigma Value

using the Z-Value Conversion Table in the Appendix.

DPMO =Total number of defects

Total units Opportunities per unit 1,000,000

DPMO =D

N O

1,000,000

Or

DetermineData Type





PerformMeasurement

System Analysis






Target

Specification limits

Data distribution

Normal distribution

Mean

Centering

Deviation

Standard deviation

Probability of producing

a defectYield

Rolled throughput yield

Collect Data and Assess Capability: Capability Analysis – Variable Data

Before determining process capability using variable data, it is

important to review a few more terms and symbols along with those

already defined:

DetermineData Type





PerformMeasurement

System Analysis






Collect Data and Assess Capability: Capability Analysis –

Variable Data TerminologyTarget

For many measurable characteristics, there is a desired level of

performance commonly called the target.

Examples:

Body temperature: 98.6°F

Overnight delivery: 10 AM the next day

Rural interstate speed limit: 70 mph

DetermineData Type





PerformMeasurement

System Analysis






LSL Target USL

Normal Distribution

Collect Data and Assess Capability: Capability Analysis – Variable Data Terminology

Normal Distribution

Data distribution is characterized by a smooth, bell-shaped curve

DetermineData Type





PerformMeasurement

System Analysis






98.6

Target Mean


Centering

Based on the relationship of the mean (the data set’s average) to

the performance target, centering is the process of making the

mean consistent with the target.

For example (body temperature):

DetermineData Type





PerformMeasurement

System Analysis






x

A particular

measurement

x

Deviation

| – | x x


Deviation

“Deviation” refers to the distance between a particular

measurement and the average of all measurements within

that data set.

DetermineData Type





PerformMeasurement

System Analysis






High Standard Deviation

High Variability

Low Standard Deviation

Low Variability


Standard Deviation(s)

Standard deviation refers to the collective deviation of the entire

data set.

For example:

DetermineData Type





PerformMeasurement

System Analysis






Target

LSL USL

Target

LSL USL

Target

LSL USL

NotCapable

NotCentered

CapableandCentered

Center ProcessReduceSpread

Defects Defects

Collect Data and Assess Capability: Relationship BetweenVariation & Process Capability

DetermineData Type





PerformMeasurement

System Analysis






Number of standard deviations from the mean

Normal Curve and Probability Areas

43210-1-2-3-4

30%

20%

10%

68%

95%

99.73%

40%

0%

Collect Data and Assess Capability: Capability

Analysis – Properties of a Normal Distribution

DetermineData Type





PerformMeasurement

System Analysis






Collect Data and Assess Capability: Cp and Cpk

A capability index is a number that represents the capabilityof the machine or process. A comparison between theprocess spread (what the process is able to do) and thespecification spread (what the customer requires).

Cp

The Cp number indicates whether the process is able toproduce parts with a process spread less than the specificationcustomer spread, this is potential process performance.

Cpk

The Cpk index is another type of capability index, whichindicates the process is actually producing parts within thespecification spread.

Similar to Cp except process location taken into account – thisindex indicates the actual process performance.

DetermineData Type





PerformMeasurement

System Analysis






Collect Data and Assess Capability: Cp/Cpk – A 6-SigmaProcess

4 5 63210-1-2-3-6 –5 -4

1σ

6σ

USLLSL

Process Width

Design Width

DetermineData Type





PerformMeasurement

System Analysis





Black Belt Training Slide: 47LSL Target

USL

1.5% 1.5%

Yield(97%)

Collect Data and Assess Capability: Relationship to

Yield and Probability of Defect Yield (probability of success

[producing a good part])

The percentage of data between

the lower and upper spec limits.

LSL Tar et

USL

1.5% 1.5%

Probability of Producing aDefect

The percent of data beyond

the lower and upper spec limits.

DetermineData Type





PerformMeasurement

System Analysis






Complete FMEA

FMEA: Documents the potential failures and their respectivecauses in the current process or design. Identifies actions to

eliminate or reduce these failures in the future

FMEA is used in the Measure Phase of a 6-Sigma project to identify

“Low-Hanging Fruit” in the current process.

In the Improve Phase, FMEA is used to assess potential failures

associated with our proposed changes

DetermineData Type


Complete FMEA


Plan


PerformMeasurement

SystemAnalysis





___ System Process Responsibility: ____________________ FMEA Name/Number: ____________________________

___ Subsystem Key Date: ____________________ Prepared By: ____________________________

___ Component FMEA Date (Orig.): _______________ (Rev.): _______________

Model Year(s)/Program(s): ____________________

Team: ____________________

Action Results

Item/FunctionPotential

Failure Mode

Potential

Eff ect(s) of

Failure

S

e

v

C

l

a

s

s

Potential

Cause/

Mechanism

of Failure

O

c

c

D

e

t

R

P

N

Recommended

Action(s )

Responsibility

and Target

Completion

Date

Actions

Taken

S

e

v

O

c

c

D

e

t

R

P

N

What is the

process step?

In w hat ways

does the Key

Input go

w rong?

What is the

impact on the

Key Output

Variables

(Customer

Requirements)

or internal

requirements?

H o w s

e v e r e i s t h e

e f f e c t t o t h e c u s t o m e r ? What

causes the

Key Input to

go wrong?

H o w o

f t e n d o e s

c a u s e o f F M

o c c u r ?

H o w w

e l l c a n y o u

d e t e c t c a u s e o r F M ? What are the

actions f or

recuing the

occurrence of

the Cause, or

improving

detection?

Who's

responsible

for the

recommended

action?

What are the

completed

actions to

take with the

recalculated

RPM? Be

sure to

include

completion

month/year

Current Process

Controls

(Prevent/Detect)

What are the existing

controls and

procedures that

prevent either the

cause or the Failure

Mode?

FMEA – Form

Spreadsheets such as the one shown below can be used todocument the FMEA

DetermineData Type





PerformMeasurement

System Analysis





Understanding the FMEA Spreadsheet

1

Process

Step/Part

Number

2

Lists Failure

Modes

3

Lists the

Effects of

Each Failure

Mode

4

Rates the

Severity of

the Effect to

the Customer

Item/FunctionPotential

Failure Mode

Potential

Eff ect(s) of

Failure

S

e

v

C

l

a

s

s

What is theprocess step?

In what w aysdoes the Key

Input go

w rong?

What is theimpact on the

Key Output

Variables

(Customer

Requirements)

or internal

requirements?

H o w s

e v e r e i s t h e

e f f e c t t o t h e c u s t o m e r ?

5

Classifies

Any Special

Product or

Process

Characteristics

DetermineData Type





PerformMeasurement

System Analysis





Process Severity Rating Table (SEV)Effect Criteria: Severity of Effect

This ranking results when a potential Failure Mode results in a final customer and/or amanufacturing/assembly plant defect. The final customer should always be considered

first. If both occur, use the higher of the two severities.

Ranking

Customer effect Manufacturing/Assembly effect

Hazardous

without

warning

Or may endanger operator (machine or

assembly) without warning.10

Hazardous

with

warning

Very high Severity ranking when a

potential Failure Mode affects safe vehicle

operation and/or involves noncompliance

with government regulation withoutwarning.

Or may endanger operator (machine or

assembly) with warning.9Very high Severity ranking when a

potential Failure Mode affects safe vehicle

operation and/or involves noncompliance

with government regulation with warning.

Very High Or 100% of product may have to be

scrapped, or vehicle/item repaired in

repair department with a repair time

greater than one hour.

8Vehicle/Item inoperable (loss of primary

function).

High Or product may have to be sorted and a

portion (less than 100%) scrapped, or

vehicle/item repaired in repair department

with a repair time between half an hour

and an hour.

7Vehicle/Item operable but at a reduced

level of performance. Customer very

dissatisfied.

DetermineData Type





PerformMeasurement

System Analysis





Process Severity Rating Table (SEV), continued

Effect RankingCustomer effect Manufacturing/Assembly effect

Moderate Or a portion (less than 100%) of the

product may have to be scrapped with no

sorting, or vehicle/item repaired in repair

department with a repair time less than

half an hour.

6

Low

Vehicle/Item operable but Comfort/

Convenience item(s) inoperable.

Customer dissatisfied.

Or 100% of product may have to be

reworked, or vehicle/item repaired off-linebut does not go to repair department.

5Vehicle/Item operable but Comfort/

Convenience item(s) operable at areduced level of performance. Customer

somewhat dissatisfied.

Very Low Or the product may have to be sorted,

with no scrap, and a portion (less than

100%) reworked.

4Fit and Finish/Squeak and rattle item does

not conform. Defect noticed by most

customers (greater than 75%).

Minor Or a portion (less than 100%) of the

product may have to be reworked, with noscrap, on-line but out-of-station.


not conform. Defect noticed by 50 percentof customers.

Very Minor Or a portion (less than 100%) of the

product may have to be reworked, with no

scrap, on-line but in-station.


not conform. Defect noticed by

discriminating customers (less than 25%).

None Or slight inconvenience to operation or

operator, or no effect.1No discernible effect.

DetermineData Type





PerformMeasurement

System Analysis






DetermineData Type





PerformMeasurement

System Analysis

7

Rates how often

a particular

Cause of Failure

Mode occurs.

8

Documents how

the Cause is

currently being

controlled in the

process.

9

Rates how well

the Cause or

Failure Mode can

be detected.

10

Risk Priority

Number (RPN):

Sev×Occ×Det

6

Lists the Causes

for each Failure

Mode. Each

Cause is

associated with a

design weakness

or a ProcessInput out-of-spec.





Using Occurrence Ratings (OCC)

Suggested PFMEA Occurrence Evaluation Criteria


Probability of Failure Likely Failure Rates Ranking

Very High:

Persistent failures

> 100 per thousand pieces

50 per thousand pieces






0.5 per thousand pieces

0.1 per thousand pieces

< 0.01 per thousand pieces

10

9

8

7

6

5

4

3

2

1

High:Frequent failures

Moderate:

Occasional failures

Low:

Relatively few failures

Remote:

Failure is unlikely

DetermineData Type





PerformMeasurement

System Analysis





Using Detection Ratings (DET)

Suggested PFMEA Detection Evaluation Criteria


Detection Ranking Criteria A B C Suggested Range of Detection Methods

Almost

Impossible

Absolute certainty of

non-Detection.

10

Very Remote Controls will probably not detect. 9

Remote Controls have poor chance of

Detection.

8

Very Low Controls have poor chance of

Detection.

7

Low Controls may detect. 6

Moderate Controls may detect. 5

Moderately

High

Controls have a good chance

to detect.

4

Very High Controls almost certain to

detect.2

Very High Controls certain to detect.

Cannot detect or is not checked.

Control is achieved with indirect or random checks only.

Control is achieved with visual inspection only.

Control is achieved with double visual inspection only.

Control is achieved with charting methods, such as SPC (Statistical

Process Control).

Control is based on variable gauging after parts have left the station, OR

Go/No Go gauging performed on 100% of the parts after parts have left the

station.

Error Detection in subsequent operations, OR gauging performed on setup

and first-piece check (for setup causes only).

Error Detection in-station (automatic gauging with automatic stop feature).

Cannot pass discrepant part.

Discrepant parts cannot be made because item has been error proofed by

process/product design.

1

High Controls have a good chance

to detect.

3Error Detection in-station, OR error Detection in subsequent operations by

multiple layers of acceptance: supply, select, install, verify. Cannot accept

discrepant part.

DetermineData Type





PerformMeasurement

System Analysis




The order in which risk should be

addressed:

SEV

Criticality (SEV × OCC)

RPN = SEV × OCC × DET

Evaluating Risk

DetermineData Type





PerformMeasurement

System Analysis