Decision based design /
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Language: | English |
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Boca Raton, FL :
CRC Press,
[2014]
Boca Raton, FL : c2014 |
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082 | 0 | 0 | |a 620/.0042 |2 23 |
100 | 1 | |a Pandey, Vijitashwa | |
100 | 1 | |a Pandey, Vijitashwa, |e author | |
245 | 1 | 0 | |a Decision based design / |c Vijitashwa Pandey |
264 | 1 | |a Boca Raton, FL : |b CRC Press, |c [2014] | |
264 | 1 | |a Boca Raton, FL : |b CRC Press, |c c2014 | |
264 | 4 | |c ©2014 | |
300 | |a xv, 268 pages : |b illustrations ; |c 25 cm | ||
300 | |a xv, 268 pages ; |c 25 cm | ||
336 | |a text |2 rdacontent | ||
336 | |a text |b txt |2 rdacontent | ||
337 | |a unmediated |2 rdamedia | ||
337 | |a unmediated |b n |2 rdamedia | ||
338 | |a volume |2 rdacarrier | ||
338 | |a volume |b nc |2 rdacarrier | ||
504 | |a Includes bibliographical references (pages 257-260) and index | ||
504 | |a Includes bibliographical references and index | ||
505 | 0 | 0 | |g 1 |t Decision Based Design: Introduction -- |g 1.1. |t Is Design a Decision? -- |g 1.1.1. |t Manufacturer Makes Decisions -- |g 1.2. |t Some Examples of Design Decisions -- |g 1.3. |t Roadblocks to Engineers Thinking about Product Development -- |g 1.4. |t Decision Based Design and Product Development -- |g 1.5. |t Why Study Decision Based Design? -- |g 1.6. |t What This Book Does Not Cover -- |g 1.7. |t For Students, Practitioners, and Researchers -- |t Problems and Exercises -- |g 2. |t Engineering Design -- |g 2.1. |t Engineering Design toward a Product, System, or Service -- |g 2.1.1. |t Decision Analysis and Engineering Design -- |g 2.1.2. |t Arrow of Causality: Design in a Company Setting -- |g 2.2. |t Design Methodology -- |g 2.2.1. |t Fermi Method -- |g 2.2.2. |t Product Platform and Product Placement -- |g 2.2.3. |t Engineering Design Is Iterative -- |g 2.2.4. |t Mathematics and Design -- |g 2.2.5. |t Optimization in Engineering Design -- |g 2.2.5.1. |t Optimal Design Formulations -- |g 2.2.6. |t What Drives Engineering Design Research? -- |g 2.2.7. |t Identifying the Scope of Design -- |g 2.2.8. |t Fundamental Objectives vs. Means Objectives -- |g 2.2.9. |t Decision Makers and Consensus -- |g 2.2.10. |t Some Thoughts on Manufacturing -- |g 2.3. |t Uncertainty in Design -- |g 2.3.1. |t Notation -- |t Problems and Exercises -- |g 3. |t Decision Analysis with Multiple Attributes -- |g 3.1. |t Decision Making under Uncertainty -- |g 3.2. |t Good Decisions and the Role of Uncertainty -- |g 3.2.1. |t Five Rules of Actional Thought -- |g 3.2.1.1. |t Order Rule -- |g 3.2.1.2. |t Probability Rule -- |g 3.2.1.3. |t Equivalence Rule -- |g 3.2.1.4. |t Substitution Rule -- |g 3.2.1.5. |t Choice Rule -- |g 3.2.2. |t Role of a Facilitator -- |g 3.3. |t Expected Utility Criterion to Make Decisions -- |g 3.3.1. |t Problem Framing -- |g 3.3.2. |t Utility Functions and Value Functions -- |g 3.4. |t Utility Functions and Incorporating Uncertainty in Decisions -- |g 3.4.1. |t Risk Attitude -- |g 3.4.2. |t Single-Attribute Utility Function -- |g 3.4.2.1. |t Linear Utility Function -- |g 3.4.2.2. |t Exponential Utility Function -- |g 3.5. |t Decision Tree -- |g 3.5.1. |t Sensitivity Analysis -- |g 3.6. |t Certainty Equivalent of a Decision -- |g 3.6.1. |t Delta Property -- |g 3.7. |t Value of Information -- |g 3.7.1. |t Value of Information for Risk-Neutral Decision Makers -- |g 3.7.2. |t Value of Information Using Utility Functions and Continuous Distributions -- |g 3.7.2.1. |t Discrete Outcomes -- |g 3.7.2.2. |t Continuous Outcomes -- |g 3.7.3. |t Value of Information and Reduction of Uncertainty -- |g 3.7.4. |t What If the Information Is Incorrect? -- |g 3.8. |t Eliciting Single-Attribute Utility Functions -- |g 3.8.1. |t Range of Negotiability -- |g 3.8.2. |t Certainty Equivalent Method -- |g 3.8.3. |t Using Probabilities -- |g 3.8.4. |t McCord and de Neufville Procedure -- |g 3.9. |t Stochastic and Deterministic Dominance -- |g 3.10. |t Multiattribute Decision Making -- |g 3.10.1. |t Trade-Offs -- |g 3.10.1.1. |t Trade-Off Behavior -- |g 3.10.2. |t Pareto Front -- |g 3.10.3. |t Limitations of Pareto Fronts -- |g 3.10.4. |t Different Multiattribute Functions -- |g 3.10.5. |t Independence Conditions for Combining Single-Attribute Functions into a Multiattribute Utility Function -- |g 3.10.5.1. |t Preferential Independence -- |g 3.10.5.2. |t Utility Independence -- |g 3.10.5.3. |t Additive Independence -- |g 3.10.5.4. |t Independence Conditions, Correlation, and Ranges of Negotiability -- |g 3.10.5.5. |t Why Do We Test for Independence Conditions? The Multiplicative Form -- |g 3.10.6. |t Assessing Multiattribute Functions -- |g 3.10.7. |t Utility over Value Functions -- |g 3.10.8. |t Attribute Dominance Utility and Multiattribute Utility Copulas -- |g 3.11. |t Biases in Decision Making -- |t Problems and Exercises -- |g 4. |t Reliability Engineering -- |g 4.1. |t Performance as a Function of Time -- |g 4.1.1. |t Reliability and Decision Based Design -- |g 4.2. |t Reliability Engineering Concepts -- |g 4.2.1. |t Reliability Function -- |g 4.2.2. |t Failure Rate and Infant Mortality -- |g 4.2.3. |t Performance or Limit State Function -- |g 4.2.4. |t Weibull Distribution -- |g 4.3. |t Failure Modes and System Reliability -- |g 4.3.1. |t Block Diagram Representation -- |g 4.3.2. |t Fault Tree Analysis -- |g 4.4. |t Reliability of Repairable Systems -- |g 4.4.1. |t Effective Age of Repaired Systems -- |g 4.5. |t Reliability-Cost Trade-Offs -- |g 4.6. |t Notes on Decision Based Design -- |t Problems and Exercises -- |g 5. |t Design Optimization -- |g 5.1. |t Modeling an Engineering System -- |g 5.1.1. |t How to Decide What to Optimize? -- |g 5.1.2. |t Constraints -- |g 5.1.2.1. |t Further Classification of Constraints -- |g 5.2. |t Classification of Optimization Problems -- |g 5.2.1. |t Linear Programs -- |g 5.2.1.1. |t Simplex Method -- |g 5.2.1.2. |t Interior Point Methods -- |g 5.2.2. |t Integer Programming -- |g 5.2.3. |t Convex and Nonconvex Programming -- |g 5.2.4. |t Mixed Problems -- |g 5.2.5. |t Multiattribute Problems -- |g 5.3. |t Optimization Methods -- |g 5.3.1. |t Classical Optimization -- |g 5.3.1.1. |t Role of Convexity in Optimization -- |g 5.3.1.2. |t Utility Maximization as a Convex Optimization Problem -- |g 5.3.2. |t KKT Conditions -- |g 5.3.3. |t Numerical Optimization Algorithms -- |g 5.3.3.1. |t Finite Differencing for Finding Derivative Values -- |g 5.3.4. |t Heuristics -- |g 5.3.4.1. |t Random Search -- |g 5.3.4.2. |t Genetic Algorithms -- |g 5.3.4.3. |t Ant Colony Optimization -- |g 5.3.4.4. |t Simulated Annealing -- |g 5.4. |t Multiobjective Optimization -- |g 5.4.1. |t Optimizing Convex Combination of Attributes -- |g 5.4.2. |t Nondominated Sorting -- |t Problems and Exercises -- |g 6. |t Simulation Methods in Engineering Design -- |g 6.1. |t Introduction -- |g 6.1.1. |t Need for Simulating Engineering Systems -- |g 6.2. |t Simulation Approach -- |g 6.2.1. |t Monte Carlo Simulation -- |g 6.2.2. |t Identifying Sources of Uncertainty -- |g 6.2.3. |t Modeling the Uncertainty in Random Variables -- |g 6.2.3.1. |t Moment Matching Method -- |g 6.2.3.2. |t Incorporating Expert Judgments -- |g 6.2.3.3. |t Maximum Entropy Method -- |g 6.3. |t Simulating Random Variables -- |g 6.3.1. |t CDF Inverse Method -- |g 6.3.2. |t Box-Muller Method for Generating Normally Distributed Random Numbers -- |g 6.3.3. |t Generating Dependent Random Variables -- |g 6.3.3.1. |t Rejection Sampling -- |g 6.3.3.2. |t CDF Inverse Method for Jointly Distributed Variables -- |g 6.3.3.3. |t Generating Dependent Normally Distributed Random Variables -- |g 6.4. |t Copulas -- |g 6.4.1. |t Sklar's Theorem -- |g 6.4.2. |t Constructing Copulas -- |g 6.5. |t Note on Statistical Dependence and Independence Conditions for Multiattribute Utility Function Assessments -- |t Problems and Exercises -- |g 7. |t Product Development and Systems Engineering -- |g 7.1. |t What Is Product Development? What Is Systems Engineering? -- |g 7.1.1. |t Industrial Design -- |g 7.2. |t More Roadblocks to Engineers Thinking about Product Development -- |g 7.3. |t Steps in Product Development -- |g 7.3.1. |t Customer Needs Assessment -- |g 7.3.1.1. |t Survey and Data Collection -- |g 7.3.1.2. |t Conjoint Analysis -- |g 7.3.1.3. |t Compatibility with Decision Analysis -- |g 7.3.1.4. |t Stated Preferences vs. |
505 | 0 | 0 | |t Revealed Preferences -- |g 7.3.1.5 |t Quality Function Deployment -- |g 7.3.2. |t Creativity in Engineering Design -- |g 7.3.2.1. |t Learning Creativity -- |g 7.3.3. |t Functional Diagrams -- |g 7.3.4. |t Brainstorming for Concept Generation -- |g 7.3.5. |t Chemical Scrubber Design Example -- |g 7.3.6. |t More on Concept Evaluation -- |g 7.4. |t Some Concepts in Product Development -- |g 7.4.1. |t Axiomatic Design -- |g 7.4.1.1. |t Maintaining Independence of Functional Requirements -- |g 7.4.1.2. |t Minimizing Information Content -- |g 7.4.1.3. |t Conflict between Axioms -- |g 7.4.2. |t Role of Metrics -- |g 7.4.3. |t Product Architecture -- |g 7.4.4. |t Softer Engineering Requirements -- |g 7.4.5. |t Product Pricing: Cost-Plus and Target Costing -- |g 7.4.6. |t Logistics -- |g 7.4.7. |t Market Size Assessment -- |g 7.4.8. |t Mass Customization -- |g 7.5. |t Design for X -- |g 7.5.1. |t Design for Manufacture -- |g 7.5.2. |t Design for Assembly and Disassembly -- |g 7.5.3. |t Design for Modularity -- |g 7.5.4. |t Design for Environment -- |g 7.5.5. |t Design for Reliability and Service -- |g 7.6. |t Technology Adoption -- |g 7.6.1. |t Managing Advanced Technology -- |g 7.6.1.1. |t Managing Technology in a Small Company -- |g 7.6.1.2. |t Managing Technology in a Large Company -- |g 7.7. |t Design Structure Matrix and Design Churn -- |g 7.7.1. |t Partitioning and Clustering a DSM -- |g 7.7.2. |t Work Transformation Matrix -- |g 7.7.3. |t Design Churn -- |g 7.8. |t Product Development and Decision Analysis -- |t Problems and Exercises -- |g 8. |t Demand Modeling -- |g 8.1. |t Introduction -- |g 8.2. |t Considering Demand in Engineering Design -- |g 8.2.1. |t Demand Determines Feasibility -- |g 8.2.2. |t Demand Determines Optimality -- |g 8.2.3. |t Trade-Off between Accuracy and Ease of Assessment -- |g 8.2.4. |t Getting the Heuristics Out of the Way -- |g 8.2.4.1. |t Dominance -- |g 8.2.4.2. |t Simple Reasoning to Deduce Market Size -- |g 8.2.5. |t Demand Curve and Price Elasticity -- |g 8.3. |t Demand Models -- |g 8.3.1. |t Logit Model -- |g 8.3.1.1. |t Choice Set -- |g 8.3.1.2. |t Properties of the Logit Model -- |g 8.3.1.3. |t Assessing Parameters of the Value Functions in the Logit Model -- |g 8.3.2. |t Nested Logit Models -- |g 8.3.3. |t Limitations of the Logit Models -- |g 8.4. |t Using Copulas -- |g 8.5. |t What Role Does Decision Analysis Play in Demand Modeling? -- |g 8.6. |t Alternative Marketing Strategies -- |g 8.6.1. |t Leasing Scenario -- |g 8.6.2. |t Razor and Blade Model -- |g 8.7. |t Demand Evolution and Net Present Value -- |g 8.7.1. |t Product Diffusion -- |t Problems and Exercises -- |g 9. |t Decision Based Design: Closure -- |g 9.1. |t Putting It All Together -- |g 9.2. |t Decision Based Design -- |g 9.2.1. |t Decision Analysis Fundamentals -- |g 9.2.2. |t Product Development -- |g 9.2.3. |t Role of Optimization -- |g 9.2.4. |t Uncertainty Modeling and Simulation -- |g 9.2.5. |t Product Attributes -- |g 9.2.6. |t Demand Modeling -- |g 9.3. |t Closure. |
650 | 0 | |a Decision making | |
650 | 0 | |a Engineering design | |
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