book

Systems Engineering

Name: Systems Engineering
Author: Dahai Liu
ISBN: 9781482282467

by Dahai Liu

October 2018

Intermediate to advanced

479 pages

13h 41m

English

CRC Press

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Preface
Author
Section I: Systems and Systems Engineering Concepts
Chapter 1: Introduction
Systems and Systems Engineering1.1 Systems1.2 Systems Classification1.2.1 Natural Systems versus Man-Made Systems1.2.2 Static Systems versus Dynamic Systems1.2.3 Conceptual Systems versus Physical Systems1.2.4 Open Systems versus Closed Systems1.3 Systems Engineering1.4 Brief History of Systems Engineering1.4.1 From Reductionism to System Thinking1.4.2 Early Practices1.4.3 Government Role1.4.4 Information Age1.5 Summary
Chapter 2: Systems Life Cycle and Design Processes
2.1 System Life Cycle2.1.1 Operational Need2.1.2 System Concept2.1.3 Systems Concept Exploration and Validation2.1.4 Engineering Model Development2.1.5 System Production, Distribution, and Deployment2.1.6 System Operations and Maintenance2.1.7 System Phase-Out and Retirement2.2 Systems Engineering Processes2.2.1 Definition of Systems Engineering Process2.2.2 Basic Concepts and Terminologies for Design Process2.2.3 Systems User Classes2.3 Systems Engineering Design Processes2.3.1 Conceptual Design2.3.1.1 Identification of Needs2.3.1.2 Feasibility Analysis2.3.1.3 System Planning2.3.1.4 Requirement Analysis2.3.1.5 Functional Analysis at the Systems Level2.3.1.6 System Specification Type A2.3.1.7 Conceptual Design Review and Evaluation2.3.2 Preliminary Design2.3.2.1 Functional Analysis and Function Allocation2.3.2.2 Design Tools and Analytical Models2.3.2.3 Design Reviews2.3.3 Detailed Design2.3.3.1 Detailed Design Requirements and Specifications2.3.3.2 CAD Tools and Prototypes in Detailed Design2.3.3.3 Component Selection2.3.3.4 Detailed Design Review2.3.4 System Installation and Deployment, Operation, and Maintenance2.4 System Engineering Design Process Models2.4.1 Waterfall Model2.4.2 Spiral Model2.4.3 Vee Model2.5 Summary
Section II: Systems Methods, Models, and Analytical Techniques
Chapter 3: Systems Requirement Analysis
3.1 What Is a System Requirement?3.1.1 Types of Requirements3.2 Characteristics of Systems Requirements3.3 Requirements Capture Technique3.4 Requirements Analysis (RA)3.4.1 Affinity Diagram3.4.2 Scenarios and Use Cases3.4.3 Quality Function Deployment (QFD)3.5 Requirements Management3.5.1 What Is Requirements Management?3.5.2 Why Requirements Management?3.5.3 Requirements Management Using CORE3.5.3.1 Requirements Management Software Tools3.5.3.2 Requirements Management Example Using CORE3.6 Summary
Chapter 4: Functional Analysis and System Design Models
4.1 What Is a Model?4.1.1 Characteristics of Systems Models4.2 Model Categorization4.2.1 Classification Based on Model Format4.2.1.1 Physical Models4.2.1.2 Analogue Models4.2.1.3 Schematic Models4.2.1.4 Mathematical Models4.2.2 Classification Based on the Nature of the Variables4.2.2.1 Deterministic Models4.2.2.2 Stochastic Models4.2.3 Other Types of System Model Classification4.3 System Design Models4.3.1 Functional Models4.3.1.1 What Is a Function?4.3.1.2 Functional Flow Block Diagram (FFBD)4.3.2 Functional Allocation4.3.2.1 Resource Requirements for Functions4.3.2.2 Allocation of TPMs4.3.2.3 A CORE Example of Detailed Functional Analysis4.3.3 Task Analysis Model4.3.3.1 Input Requirements4.3.3.2 Procedure4.3.3.3 Output Product4.3.4 Timeline Analysis Model4.3.5 Link Analysis Based on Network and Graph Model4.3.5.1 Input4.3.5.2 Procedure4.3.6 Center of Gravity Model for Facility Location Planning4.4 Summary
Chapter 5: System Technical Performance Measures
5.1 Technical Performance Measures (TPMs)5.2 Systems Reliability5.2.1 Reliability Definition5.2.2 Mathematical Formulation of Reliability5.2.2.1 Reliability Function5.2.2.2 Failure Rate and Hazard Function5.2.2.3 Reliability with Independent Failure Event5.2.3 Reliability Analysis Tools: FMEA and Faulty Trees5.2.3.1 Failure Mode Effect Analysis (FMEA)5.2.3.2 Faulty Tree Analysis (FTA)5.3 System Maintainability5.3.1 Maintainability Definition5.3.2 Measures of System Maintainability5.3.2.1 Mean Corrective Time 5.3.2.2 Preventive Maintenance Time (Mpt)5.3.2.3 Mean Active Maintenance Time 5.3.2.4 Mean Down Time (MDT)5.3.3 System Availability5.3.4 System Design for Maintainability5.4 System Supportability5.4.1 Definition of Supportability5.4.2 Supply Chain and System Supportability5.4.3 Inventory Management: EOQ Model5.4.3.1 Ordering and Setup Cost5.4.3.2 Unit Purchasing Cost5.4.3.3 Unit Holding Cost5.5 Human Factors and Usability Engineering5.5.1 Definition of Human Factors5.5.2 Work System Design5.5.3 Application of Anthropometric Data5.5.4 Usability Engineering5.6 Summary
Chapter 6: Decision-Making Models in Systems Engineering
6.1 Elements of Decision Making6.2 Decision-Making Models under Risks and Uncertainty6.2.1 Decision Making under Uncertainty6.2.1.1 Laplace Criterion6.2.1.2 Maximax Criterion6.2.1.3 Maximin Criterion6.2.1.4 Hurwicz Criterion6.2.1.5 Minimax Regret6.3 Decision Making under Risks6.4 Utility Theory6.5 Decision Tree6.5.1 Expected Value of Sample Information6.5.2 Expected Value of Perfect Information6.6 Decision Making for Multiple Criteria: AHP Model6.6.1 AHP Algorithms6.7 Summary

Chapter 7: System Optimization Models
7.1 What Is Optimization?7.2 Unconstrained Optimization Models7.2.1 Derivatives and Rate of Change7.3.1 Linear Programming7.3.1.1 Formulation7.3.1.2 Solving LP Models Using Graphical Method7.3.1.3 Simplex Algorithm7.3.2 Solving LP Using a Spreadsheet7.3.2.1 Step 1. Activation of Solver Function in Excel7.3.2.2 Step 2. Set-Up of LP Model in Excel7.3.2.3 Step 3. Solving the LP Model7.4 Summary
Chapter 8: Process Modeling Using Queuing Theory and Simulation
8.1 Basic Queuing Theory8.1.1 Queuing System8.1.1.1 Arrival Process8.1.1.2 Queue8.1.1.3 Service Process8.1.2 M/M/1 Queuing System8.1.2.1 Exponential Time Arrival and Poisson Process8.1.2.2 Birth-Death Process8.1.2.3 Measures of M/M/1 Queue8.1.3 Multiserver Queuing Systems8.1.4 Queuing Systems with Finite Population8.2 Application of Queuing Theory8.3.1 Introduction to Simulation8.3.2 Discrete Event Simulation (DES)8.3.3 Data Analysis Using Goodness of Fit8.3.4 DES Model Using Arena8.3.4.1 Entity8.3.4.2 Attribute8.3.4.3 Resources8.3.4.4 Queue8.3.4.5 Variable8.3.4.6 Step 1: Generate Parts Arrival and Assign Parts Attributes8.3.4.7 Step 2: Drilling Process8.3.4.8 Step 3: Decide for Rework8.3.4.9 Step 4: Collect Time in System and System Exit8.3.4.10 Step 5: Execute the Model and Obtain Results8.4 Summary
Chapter 9: Engineering Economy in Systems Engineering
9.1 Interests and Time Value of Money9.2 Economic Equivalence9.2.1 Present Value (P) and Future Value (F)9.2.2 Annual Value (A) and Future Value (F)9.2.3 Annual Value (A) and Present Value (P)9.3 Decision Making Using Interest Formula9.3.1 Present Value, Future Value, and Annual Value Comparison9.3.1.1 Present Value Equivalence (PE) Criterion9.3.1.2 Future Value Equivalence (FE) Criterion9.3.1.3 Annual Value Equivalence (AE) Criterion9.3.2 Rate of Return9.4 Break-Even Analysis9.4.1 Cost Volume Break-Even Analysis9.4.2 Rent-or-Buy Break-Even Analysis9.5 Summary
III: Systems Management and Control Methods
Chapter 10: Systems Management and Control
10.1 Systems Management Planning10.1.1 Engineering Design Project Management and Design Teams10.2 Systems Engineering Management Plan (SEMP)10.2.1 Cover Page10.2.2 Table of Contents10.2.3 Scope of Project10.2.4 Applicable Documents10.2.5 Systems Engineering Process10.2.6 Transitioning Critical Technologies10.2.7 Systems Integration Efforts10.2.8 Additional Activities10.2.9 Appendices10.2.10 Systems Engineering Master Scheduling10.3 Systems Control Models10.3.1 Critical Path Method (CPM)10.3.2 Program Evaluation and Review Technique (PERT)10.4 Summary
Bibliography
Appendix I: Introduction to Probability and Statistics
I.1 Basic Probability ConceptsI.1.1 Experiment, Sample, Sample Space and Universe/PopulationI.1.1.1 ExperimentI.1.1.2 Sample, Sample Space, and EventI.1.1.3 ProbabilityI.2 Random Variables and Distribution FunctionI.2.1 Continuous Random VariablesI.2.1.1 Expected Value and Variance of the Random VariableI.3 Some Commonly Used Probability FunctionsI.3.1 Discrete Random VariablesI.3.1.1 Bernoulli Random VariableI.3.1.2 Binomial Random VariableI.3.1.3 Poisson Random VariableI.3.2 Continuous Random VariablesI.3.2.1 Uniform Random VariableI.3.2.2 Exponential Random VariablesI.3.2.3 Normal Random VariableI.3.2.4 Lognormal Random VariableI.3.2.5 Weibull Random Variable
Appendix II: Cumulative Normal Distribution Table
Appendix III: Interest Factor Tables

Content preview from Systems Engineering

Chapter 5

System Technical Performance Measures

In previous chapters, we have described the systems design processes and some basic models that are utilized within the design process, including the functional analysis and functional allocation models. Models play a significant role in systems design, and rely on variables and parameters to produce valid results. Taking the functional analysis model as an example, for each of the functions in the functional flow block diagram (FFBD), there are performance or constraints parameters that regulate the function to serve the overall system mission. These design-dependent parameters (DDPs) are usually expressed in quantitative format, which are also called technical performance measures (TPMs).

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Systems Engineering

by Dahai Liu

System Technical Performance Measures

Become an O’Reilly member and get unlimited access to this title plus top books and audiobooks from O’Reilly and nearly 200 top publishers, thousands of courses curated by job role, 150+ live events each month,
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