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Problem Solving for Engineers

David G. Carmichael
Format
Book
Published
Boca Raton : Taylor & Francis, [2013]
Language
English
ISBN
9781466570610 (pbk.), 146657061X (pbk.)
Summary
"This book takes a systematic approach to problem definition, generation of alternative solutions, analysis, and selection of the preferred solution. The book introduces some fundamental terms needed to think systematically and undertake systematic problem solving. It covers both individual and group problem solving. Selection of the preferred solution involves decision making, and fundamental concepts of decision making are introduced, including decision making in the presence of multiple criteria and uncertainty. The treatment embodies decision making for sustainability, with its blend of economics, social and environmental considerations. It also identifies and embodies the specific problem solving of management and planning"--
Contents
  • Machine generated contents note: 1.Systems Methodology
  • 1.1.Introduction
  • 1.2.Terminology
  • 1.2.1.Abuse of Terminology
  • 1.2.2.Probabilistic, Deterministic
  • 1.2.3.Dynamic, Static
  • 1.2.4.Discrete, Continuous
  • 1.3.Origin
  • 1.4.System
  • 1.4.1.Relation between Parts
  • 1.5.Fundamental Variables
  • 1.5.1.Output, State
  • 1.5.2.Input, Control
  • 1.5.3.Disturbance
  • 1.6.Subsystems
  • 1.7.Environment
  • 1.8.System Boundary
  • 1.8.1.Open and Closed Systems
  • 1.9.System and Behavior Characterization
  • 1.9.1.Transient and Steady States
  • 1.9.2.Equilibrium
  • 1.9.3.Equifinality
  • 1.9.4.Stability
  • 2.Models and Modeling
  • 2.1.Introduction
  • 2.1.1.Terminology
  • 2.2.Formalism
  • 2.3.Hierarchical Multilevel Systems
  • 2.3.1.States, Controls, and Outputs
  • 2.3.2.Single Level
  • 2.4.Staged Systems
  • 2.4.1.Project Phases
  • 2.5.Model Development
  • 2.5.1.Scientific Method
  • 2.5.1.1.Nonrigorous and Management Models
  • 2.5.2.False Causality
  • 2.5.3.Adages, Truisms
  • -- Contents note continued: 2.6.Classification
  • 2.7.System Model Terminology
  • 2.7.1.Terminology
  • 2.7.2.Automatic Control
  • 2.7.3.Fundamental Configurations
  • 3.Some Common System Models
  • 3.1.Introduction
  • 3.2.Block Diagrams
  • 3.2.1.Junctions
  • 3.2.2.Series Subsystems
  • 3.2.3.Parallel Subsystems
  • 3.2.4.Feedback
  • 3.3.Black Box
  • 3.4.State Equation Models
  • 3.4.1.Differential Equation Models
  • 3.4.2.Difference Equation Models
  • 3.4.3.Partial Differential Equation Models
  • 3.4.4.Algebraic (Nondifference) Equation Models
  • 3.5.Other Forms
  • 3.5.1.Networks
  • 3.5.2.Queuing Models
  • 3.5.3.Trees
  • 3.5.4.Simulation
  • 4.Fundamental Configurations Relating to Systems
  • 4.1.Introduction
  • 4.2.Analysis
  • 4.2.1.Simulation
  • 4.2.2.Prediction, Forecasting
  • 4.2.3.Stability
  • 4.2.4.Sensitivity
  • 4.2.5.Economic Appraisal
  • 4.2.6.Critical Path Method (CPM)
  • 4.2.7.Reliability
  • 4.2.8.Queuing Theory
  • 4.2.9.Fault Trees, Event Trees
  • -- Contents note continued: 4.2.10.Other Forms of Analysis
  • 4.2.11.Garbage In-Garbage Out
  • 4.2.12.Modeling and Analysis
  • 4.3.Synthesis
  • 4.3.1.Confusion in Terminology Usage
  • 4.3.2.Conversion to an Iterative Analysis Form
  • 4.3.3.On-Line/Off-Line
  • 4.4.Investigation
  • 4.4.1.State Estimation
  • 4.4.2.Natural/Artificial Input
  • 4.4.3.Roots
  • 4.4.4.On-Line/Off-Line
  • 4.5.Controllability and Observability
  • 4.5.1.Controllability
  • 4.5.2.Observability
  • 5.The Synthesis Configuration
  • 5.1.Introduction
  • 5.1.1.Objective
  • 5.1.2.Constraints
  • 5.1.3.Variables
  • 5.1.4.Decision Support
  • 5.2.Conversion to Iterative Analysis
  • 5.2.1.Steps
  • 5.2.2.Planning
  • 5.2.3.Systems Engineering
  • 5.2.4.Direct Synthesis
  • 5.2.5.Theory of Optimal Control Systems
  • 5.3.Optimal Form of Synthesis
  • 5.3.1.(Optimal) Synthesis Components
  • 5.3.2.Constraints
  • 5.3.3.Objective
  • 5.3.4.Probabilistic Systems
  • 5.3.5.Multiple Objectives
  • 5.3.6.Alternative Terminology
  • -- Contents note continued: 5.4.Design Examples
  • 5.4.1.Structural Design
  • 5.4.2.Earthmoving Operation
  • 5.5.Optimization Techniques
  • 5.5.1."Gut Feel" Considerations
  • 5.5.2.Numerical Approaches
  • 5.5.3.Calculus
  • 5.5.4.Pontryagin's Maximum Principle
  • 5.5.5.Dynamic Programming
  • 5.5.6.Mathematical Programming
  • 5.6.Project Planning
  • 5.6.1.As Synthesis
  • 5.6.2.As Iterative Analysis
  • 5.6.3.Project and End-Product
  • 5.6.4.Conventional Thinking on Planning
  • 5.6.5.Planning Function
  • 5.6.6.Planning Components
  • 5.6.7.Project "Control"
  • 5.6.8.Financial Planning
  • 5.6.9.Human Resource Planning
  • 5.6.10.Resource Planning
  • 5.6.11.Strategic Planning
  • 5.7.Management
  • 5.7.1.General Management
  • 5.7.2.Project Management
  • 5.7.2.1."Time" Management
  • 5.8.Risk Management
  • 5.8.1.Risk Management Process
  • 5.8.2.Definition
  • 5.8.3.Objectives and Constraints Statement
  • 5.8.4.Alternatives Generation
  • 5.8.5.Analysis
  • 5.8.6.Evaluation
  • -- Contents note continued: 5.8.7.Iteration Feedback
  • 5.9.Work Study
  • 5.9.1.Outline
  • 5.9.2.Method Study
  • 5.9.3.Work Measurement
  • 5.9.4.Reengineering
  • 5.10.Value Management
  • 5.10.1.Process
  • 5.10.2.Distinguishing Features
  • 5.11.Constructability
  • 6.The Investigation Configuration
  • 6.1.Introduction
  • 6.1.1.State Estimation
  • 6.1.2.Natural/Artificial Input
  • 6.1.3.Roots
  • 6.1.4.On-Line/Off-Line
  • 6.2.Black and Gray Boxes
  • 6.2.1.Parameter Estimation
  • 6.3.System Response/Output
  • 6.3.1.Linearity
  • 6.3.2.Linear Differential Equation Models
  • 6.4.Least Squares Approach
  • 6.4.1.Static System Models
  • 6.4.2.Data Grouped
  • 6.4.2.1.Generalization
  • 6.4.3.Weighted Least Squares
  • 6.4.4.Sequential Least Squares
  • 6.4.4.1.Multiple Parameter Case
  • 6.4.5.Nonlinear Regression
  • 6.4.6.Multiple Linear Regression
  • 6.4.7.Correlation
  • 6.5.Forecast Modeling
  • 6.5.1.Introduction
  • 6.5.1.1.Modeling without Historical Data
  • 6.5.2.Patterns
  • 6.5.2.1.Noise
  • -- Contents note continued: 6.5.2.2.Stationarity
  • 6.5.2.3.Dependence
  • 6.5.3.Forecast Error
  • 6.5.3.1.Definitions
  • 6.5.3.2.Mean Absolute Deviation
  • 6.5.3.3.Bias
  • 6.5.3.4.Mean Absolute Percentage Error
  • 6.5.3.5.Mean Squared Error
  • 6.5.3.6.Comment
  • 6.5.4.Models
  • 6.5.4.1.Choice of Model
  • 6.5.5.Expert Judgment
  • 6.5.6.Delphi Approach
  • 6.5.7.Market Research
  • 6.5.8.Mathematical Models
  • 6.5.8.1."Naive" Model
  • 6.5.8.2.Moving Average Models
  • 6.5.8.3.Exponential Smoothing Models
  • 6.6.Dynamic Systems
  • 6.6.1.Continuous Time Case
  • 6.6.2.Discrete Time Case
  • 6.6.3.Kalman Filter
  • 7.Systematic General Problem Solving
  • 7.1.Introduction
  • 7.1.1.What Is a Problem and What Is a Solution?
  • 7.1.2.Synthesis via Iterative Analysis
  • 7.1.3.Abbreviated Version
  • 7.2.Definition
  • 7.2.1.General
  • 7.2.2.Proper Characterization of the State
  • 7.3.Objectives and Constraints Statement
  • 7.3.1.Objectives
  • 7.3.2.Setting Objectives
  • 7.3.3.Constraints
  • -- Contents note continued: 7.3.4.Boundary Conditions
  • 7.3.5.Needs
  • 7.4.Alternatives Generation
  • 7.4.1.Environment
  • 7.4.2.Assumptions
  • 7.4.3.Causes
  • 7.5.Analysis and Evaluation
  • 7.5.1.Uncertainties
  • 7.6.Selection
  • 8.Creativity
  • 8.1.Introduction
  • 8.2.Creative Process
  • 8.2.1.Logic
  • 8.2.2.Idea Linking
  • 8.2.3.Problem Solving
  • 8.2.4.Free Association
  • 8.3.Measuring Creativity
  • 8.3.1.Traits
  • 8.4.Types of Creativity
  • 8.4.1.Something New
  • 8.4.2.Combination
  • 8.4.3.Extension
  • 8.5.Stimulating Creativity
  • 8.5.1.Idea Generation
  • 8.5.2.Taking an Idea Census
  • 8.5.3.Systems Engineering Approaches
  • 8.5.4.Pure Creativity
  • 8.5.5.Brainstorming and Similar
  • 8.5.6.Other Techniques
  • 8.6.Creativity and Organizations
  • 8.6.1.Climate
  • 9.General Problem Solving with Groups
  • 9.1.Introduction
  • 9.1.1.Mediation
  • 9.1.2.Value Management
  • 9.2.Participants
  • 9.2.1.Facilitator
  • 9.2.2.Recorder
  • 9.2.3.Group Members
  • 9.3.Facilitation
  • -- Contents note continued: 9.3.1.Facilitator's Styles
  • 9.3.2.Facilitator's Activities
  • 9.3.2.1.Looking after the Process
  • 9.3.2.2.Handling the People
  • 9.3.2.3.Looking after the Surroundings
  • 9.3.2.4.Agenda
  • 9.3.3.Facilitator's Skills
  • 9.4.Problem-Solving Steps
  • 9.5.Groups versus Individuals
  • 9.5.1.Building Consensus
  • 10.Decision Making with Multiple Objectives
  • 10.1.Introduction
  • 10.1.1.Triple Bottom Line
  • 10.2.Approaches and Examples
  • 10.2.1.Approaches to Dealing with Multiple Objectives
  • 10.2.2.Typical Applications
  • 10.2.3.Selection of Plant and Equipment
  • 10.2.4.Tender Evaluation and Assessment
  • 10.2.5.Project Selection/End-Product Selection
  • 10.2.6.Personal Applications
  • 10.2.6.1.Vehicle Selection
  • 10.2.6.2.Clothing Selection
  • 10.2.6.3.Partner Selection
  • 10.2.7.Employee Recruitment
  • 10.2.7.1.Needs and Wants
  • 10.2.8.Noninferior Solutions
  • 10.3.Collective Decision Making
  • 10.3.1.Social Welfare Function
  • -- Contents note continued: 10.3.2.Public Involvement
  • 11.Optimization
  • 11.1.Introduction
  • 11.1.1.Design
  • 11.1.2.Outline
  • 11.1.3.Optimization Techniques
  • 11.1.4.Packages
  • 11.2.Conventional Design
  • 11.2.1.Example
  • 11.2.2.Quantitative Formulation of Design
  • 11.2.3.Conventional Design Approach
  • 11.2.4.Alternative Computations
  • 11.2.5.Formulation in Terms of T
  • 11.3.Components of Optimization
  • 11.3.1.Relationship to the Design Process
  • 11.3.2.Alternative Terminology
  • 11.3.3.Possible Approaches
  • 11.3.4.Variables
  • 11.3.5.Admissible Regions
  • 11.4.Standard Forms
  • 11.4.1.Standard Form SF1
  • 11.4.2.Standard Form SF2
  • 11.4.3.Standard Form SF3
  • 11.4.4.Conversions between Standard Forms
  • 11.4.4.1.Negative Variables
  • 11.4.4.2.Maximization
  • 11.4.4.3.Greater Than Inequalities
  • 11.4.4.4.Equalities
  • 11.4.4.5.Absolute Values
  • 11.4.4.6.Inequalities
  • 11.4.5.Algorithms
  • 11.5.Elementary Optimization
  • 11.5.1.Some Results of Calculus
  • -- Contents note continued: 11.5.2.Equality Constraints
  • 11.5.3.Lagrange Multipliers
  • 11.5.4.Inequality Constraints
  • 11.6.Linear Optimization
  • 11.6.1.Example Linear Cases
  • 11.6.1.1.Production Planning
  • 11.6.1.2.Product Mix
  • 11.6.1.3.Transportation
  • 11.6.1.4.Assignment
  • 11.6.1.5.Production Scheduling
  • 11.6.1.6.Blending
  • 11.6.2.LP Form
  • 11.6.3.Multiple Objective Linear Programming
  • 11.7.Nonlinear Programming
  • 11.7.1.Unconstrained Case
  • 11.7.1.1.Single Variable
  • 11.7.1.2.Interval Elimination Methods
  • 11.7.1.3.Function Approximation Methods
  • 11.7.1.4.Multiple Variables
  • 11.7.1.5.Gradient Method
  • 11.7.1.6.Newton's Method
  • 11.7.2.Constrained Case
  • 11.7.2.1.Kuhn-Tucker Conditions
  • 11.7.2.2.Quadratic Programming
  • 11.7.2.3.Penalty Methods
  • 11.8.Other Optimization Forms
  • 12.Decision Approaches and Tools
  • 12.1.Introduction
  • 12.1.1.Terminology
  • 12.2.Underlying Framework
  • 12.3.Ranking Payoffs
  • 12.3.1.Example
  • -- Contents note continued: 12.3.1.1.Noncertainty Type (i)
  • 12.3.1.2.Noncertainty Type (ii)
  • 12.4.Decisions with Competition or Conflict
  • 12.4.1.Game Examples
  • 12.5.Decision Trees
  • 12.5.1.Determining EMV
  • 12.6.Bayes Theorem and Additional Information
  • 12.7.Utility
  • 12.7.1.Methods of Utility Function Determination
  • 12.7.1.1.Certainty Equivalent Method
  • 12.7.1.2.Example of Utility Function Determination
  • 12.7.1.3.Human Behavior
  • 12.7.2.Approximation for Utility Functions
  • Appendix A Sensitivity
  • Appendix B Surveys
  • B.1.Research
  • B.2.General Comment on Surveys
  • B.3.Questions
  • B.4.Some Suggestions
  • B.5.Survey Type
  • B.5.1.Personal Interviews
  • B.5.2.Telephone Interviews
  • B.5.3.Mail/Email Surveys
  • B.5.4.Panels
  • Appendix C Sampling
  • C.1.Random Sampling
  • C.2.Stratified Sampling
  • C.3.Other Sampling
  • C.4.Non-Reply
  • Appendix D Measurement and Scales
  • D.1.Nominal Scale
  • D.1.1.Multiple-Choice Questions
  • D.2.Ordinal Scale
  • -- Contents note continued: D.2.1.Forced Ranking
  • D.2.2.Paired Comparison
  • D.2.3.Semantic Scale
  • D.3.Interval Scale
  • D.3.1.Bipolar Adjective
  • D.3.2.Other Approaches
  • D.4.Ratio Scale
  • D.4.1.Direct Quantification
  • D.4.2.Constant Sum Scale
  • D.5.Comments.
Description
xxiii, 415 pages : illustrations ; 25 cm
Notes
Includes bibliographical references (pages 403-405) and index.
Technical Details
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