Shawn Kenny, Ph.D., P.Eng.Assistant ProfessorFaculty of Engineering and Applied ScienceMemorial University of Newfoundlandspkenny@engr.mun.ca

ENGI 5708 Design of Civil Engineering Systems

Lecture 02: Overview of Systems Engineering

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Lecture 02 Objective

To provide an overview of systems engineering

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Systems Engineering is …

… an interdisciplinary approach that encompasses the entire technical effort, and evolves into and verifies an integrated and life cycle balanced set of system people, products, and process solutionsthat satisfy customer needs.

Ref: EIA (1994)

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Systems Engineering is …… an interdisciplinary approach and means to enable the realization of successful systems.

It focuses on defining customer needs and required functionalityearly in the development cycle, documenting requirements, then proceeding with design synthesis and system validation while considering the complete problem: Operations, Cost & Schedule Performance, Training & Support, Test, Disposal and ManufacturingSystems Engineering integrates all the disciplines and specialtygroups into a team effort forming a structured development process that proceeds from concept to production to operation.Systems Engineering considers both the business and the technical needs of all customers with the goal of providing a quality product that meets the user needs.

Ref: INCOSE (2007)

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Systems Engineering is …

… an integrated, quantitative and objective interdisciplinary engineering framework to support decision making processes by establishing optimal solutions to complex problems that satisfy business and technical performance requirements over the life-cycle.

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Systems Engineering Framework

Systems Engineering

Management ProcessesSystems

EngineeringTechnical Processes

Life Cycle Integration

Planning /Development Phasing

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Knowledge Integration

Communications

Complementary Studies

Mathematics

Engineering Design

Engineering Analysis

Systems EngineeringTechnical Processes

Engineering Science

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Systems Engineering Applications

Civil EngineeringTransportationCivil and energy pipeline systemsElectrical utilities and telecommunicationsWater resource managementAgriculture and forestryConstruction industry

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Systems Engineering Applications (cont.)

BusinessFinanceOperations managementHuman resourcesMarketing

Production and ManufacturingBiological and Physical SciencesMilitary

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Systems Engineering Applications (cont.)

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Systems Engineering Applications (cont.)

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Systems Engineering Lessons LearnedHistory

Planning 1968; Delivery 1971Cost $38 million

Systems ApproachIntegrated working models

• Human factors unit• Design and subsystems integration unit• Deployment mechanism, vibration and qualification test units• Astronaut trainer

Client (NASA astronauts) participation through system life-cycleLesson

Successful project due to applied system engineering management processes and principlesPerformed all functions reliably with no major anomalies

Lunar Roving Vehicle

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Systems Engineering Lessons LearnedHistory

Planning 1980’s; Launch 1990Cost $1.5 billion

ProblemMain mirror spherical aberration

CauseFaulty QC during manufacturingRequirement was specified but not properly tested or controlledDevice assumed to work correctly

Lessons LearnedRepair in space $50millionConduct appropriate tests on component and system levelFAT and SIT

Hubble Telescope

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Data Gathering

Systems Engineering Approach

Problem DefinitionGeneration of AlternativesModel FormulationEvaluation of AlternativesImplementation

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Problem Definition

Probably Most Critical Systems PhaseGet it right the first time• Analogue: Free-body diagram

Potential negative impact• Ineffective use of resources• Cascading effect on systems approach• Eliminate alternatives• Uninformed or incorrect decision making

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Problem Definition (cont.)

Key ElementsProblem statementObjective statementEvaluation criteria

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Problem Definition (cont.)

Problem StatementSystem Environment Characterization• Engineer ⇔ Client • Systems hierarchy • Systems interrelationship• Work scope• Qualitative and quantitative elements

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Problem Definition (cont.)

• Clear and concise• Focus on issues, root cause• Expansive, options• Tied to work scope

• Ambiguity• Symptoms focus• Narrow view point• Preconceptions

AvoidAvoidProblem Statement

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Problem Definition (cont.)Problem Statement

Address root cause not symptomsSymptom• High accident rate

at an intersectionPotential root cause• Traffic volume

exceeds capacity• Inadequate line of sight• Poor alignment or grade• Ineffective control systems• Driver inattention• Weather• Combination

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Problem Definition (cont.)Objective Statement

Decisions to be made• Essential variables

Parameters• Influence decision variables• Fixed, uncertainty

Constraints• Decision variable ⇔ parameter relationship• Natural, physical or practical bound limits

Capacity, legal, economic, political, social, moral, ethicalConcerned with optimization• Exceptions

Goal seek problemMultiple objective functions

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Problem Definition (cont.)Objective Statement – Multiple Objectives

Characteristic of most complex systems• May appear to be in conflict or mutually exclusive• Course focus on single objective problems

Production Facility ExampleObjectives• Maximize profits• Minimize O&M costs• Minimize waste discharge

Possible objective statement• Maximize profits subject to environmental and waste

discharge regulationsRemaining objectives become constraints

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Problem Definition (cont.)

Evaluation CriteriaMeasure of performance or effectiveness• Rational and objective basis to facilitate decision

making• Quantitative or qualitative

Ex: Money/time/quantity, aesthetics, perception

• Absolute or relativeEx: Profit/loss, product unit cost, benefit/cost ratio

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Problem Definition (cont.)

Range of StakeholdersSocietal engagement• Inherent nature with major civil engineering

projectsVarying concerns, viewpoints and values• # “problems & solutions” ∝

system complexity

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Generation of Alternatives

BrainstormingKeep problem and objective statement in focusQuantity but no prolonged diversionLateral thinking and unorthodox ideasAvoid criticismFilter and improve alternatives

Best Practices and Lessons Learned

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Model Formulation

Transform Problem Definition Qualitative ⇒ quantitative• Objective framework• Parametric sensitivity analysis

Mathematical Models• Descriptive• Prescriptive

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Model Formulation (cont.)

CaveatsUnderstand theoretical basis• Linear, nonlinear• Idealizations and limitations

Appropriate use and application• Deterministic, stochastic process• Calibration and validation

Quantifiable ≠ fact or importance• Uncertain or unknown quantities

Qualitative limits or thresholds• Ex: Land use, noise, aesthetics

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Model Formulation (cont.)

Descriptive ModelsClassical engineering models• Input and initial condition ⇒

output

Differential equationsFinite difference equations

• Decision making rests with the modeler

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Model Formulation (cont.)

Prescriptive ModelsDetermine optimal decision or strategy• Main focus of systems engineering• Problem definition reformulated in mathematical

terms• Range of mathematical and engineering tools

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Model Formulation (cont.)

Types of Prescriptive Models

Ref: Pike (2001)

Mathematical ProgrammingAnalytical MethodsLinear ProgrammingInteger ProgrammingGeometric ProgrammingQuadratic ProgrammingConvex ProgrammingDynamic Programming (Discrete)Nonlinear Programming or Multivariable Search MethodsSeparable ProgrammingGoal Programming or Multicriterion OptimizationCombinatorial ProgrammingMaximum Principle (Discrete)Heuristic Programming

Variational MethodsCalculus of VariationsDynamic Programming (Continuous)Maximum Principle (Continuous)

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Model Formulation (cont.)

Systems Analysis TechniquesCourse focus• Graphical solutions• Linear programming• Network analysis• Decision theory• Resource management tools• Economic analysis

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Evaluation of Alternatives

Systems Analysis OutcomeMinimize or maximize objective function• Establish single or alternate optimal solutions

Informed Decision BasisEvaluation or performance criteria• Objective (quantitative)• Subjective (aesthetic, political)

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Evaluation of Alternatives (cont.)

OptionsStatus quo• No action or “do nothing alternative”

Reject optimal solution(s)• Diverse opinion, no consensus ⇒ “open ended problem”• May restart systems engineering cycle

Select non-optimal solution• Subjectivity, external factors

Select optimal solution• Sensitivity analysis

Investigate “What if…” scenarios and variability

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Implementation

Final StageOn-track with problem definition• Tangible results• Client engagement

Minimal feedback• May be dynamic due to variability with time or uncertainty

Engineering reporting• Technical and non-technical• Conclusions and recommendation within systems context

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ReVelle et al., (2004)

Relevant ChaptersCh. 1 Explaining Systems Analysis• Section 1A through 1E

Ch. 2 Models in Civil and Environmental Engineering• Section 2A through 2C

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ReferencesEIA (1994). EIA Standard IS-632, Systems Engineering.INCOSE (2007). http://www.incose.orgWikipedia (2007). http://en.wikipedia.orghttp://www.nlh.nl.caPike, R.W. (2001). Optimization for Engineering Systems. Professor of Chemical Engineering and Systems Science, Louisiana State UniversityReVelle, C.S., E.E. Whitlatch, Jr. and J.R. Wright (2004). Civil and Environmental Systems Engineering 2nd

Edition, Pearson Prentice Hall ISBN 0-13-047822-9