engi 5708 design of civil engineering...
TRANSCRIPT
Shawn Kenny, Ph.D., P.Eng.Assistant ProfessorFaculty of Engineering and Applied ScienceMemorial University of [email protected]
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