Process simulation using WITNESS : including lean and Six-sigma applications

Content: About the Companion Website xvii    Preface xix    Acknowledgments xxiii    1 Concepts of Simulation Modeling 1    1.1 Overview 1    1.2 System Modeling 2    1.2.1 System Concept 2    1.2.2 Modeling Concept 4    1.2.3 Types of Models 5    1.3 Simulation Modeling 11    1.3.1 Simulation Defined 11    1.3.2 Simulation Taxonomy 12    1.4 The Role of Simulation 15    1.4.1 Simulation Justified 15    1.4.2 Simulation Applications 16    1.4.3 Simulation Precautions 17    1.5 Simulation Methodology 20    1.5.1 Identify Problem/Opportunity 20    1.5.2 Develop Solution/Improvement Alternatives 21    1.5.3 Evaluate Solution Alternatives 21    1.5.4 Select the Best Alternative 22    1.5.5 Implement the Selected Alternative 22    1.6 Steps in a Simulation Study 22    1.6.1 Problem Formulation 23    1.6.2 Setting Study Objectives 23    1.6.3 Conceptual Modeling 25    1.6.4 Data Collection 26    1.6.5 Model Building 27    1.6.6 Model Verification 30    1.6.7 Model Validation 30    1.6.8 Model Analysis 31    1.6.9 Study Documentation 32    1.7 Simulation Software 34    1.7.1 WITNESS(R) Simulation Software 35    1.8 Summary 36    Questions and Exercises 37    Bibliography 38    2 World-Views of Simulation 41    2.1 Overview 41    2.2 System Modeling with DES 42    2.2.1 System Structure 42    2.2.2 System Layout 43    2.2.3 System Data 43    2.2.4 System Logic 44    2.2.5 System Statistics 45    2.3 Elements of Discrete Event Simulation (DES) 45    2.3.1 System Entities (EN) 45    2.3.2 System State (S) 46    2.3.3 State Variables (VR) 46    2.3.4 System Events (E) 47    2.3.5 System Activities (A) 48    2.3.6 System Resources (R) 48    2.3.7 System Delay (D) 50    2.3.8 System Logic (L) 50    2.4 DES Functionality 51    2.4.1 Discrete-Event Mechanism 52    2.4.2 Time-Advancement Mechanism 54    2.4.3 Random Sampling Mechanism 55    2.4.4 Statistical Accumulation Mechanism 58    2.4.5 Animation Mechanism 59    2.5 Example of DES Mechanisms 60    2.6 Monte Carlo Simulation (MCS) 65    2.7 Continuous Simulation 68    2.7.1 WITNESS(R) for Continuous Simulation 69    2.7.2 Hybrid Simulation 69    2.8 WITNESS(R) World-views of Simulation 70    2.8.1 Attribute 72    2.8.2 Buffer 72    2.8.3 Carrier 72    2.8.4 Conveyor 73    2.8.5 Fluid 73    2.8.6 Labor 74    2.8.7 Machine 74    2.8.8 Part 75    2.8.9 Path 75    2.8.10 Pipe 75    2.8.11 Processor 75    2.8.12 Sections 75    2.8.13 Station 76    2.8.14 Tank 76    2.8.15 Track 76    2.8.16 Vehicle 76    2.9 Summary 77    Questions and Exercises 78    Bibliography 80    3 WITNESS(R) Environment 83    3.1 Overview 83    3.2 The WITNESS(R) Environment 83    3.3 Menus 85    3.3.1 General Menu Operation 86    3.4 Tool Bars 86    3.4.1 Standard Tool Bar 86    3.4.2 Views Toolbar 87    3.4.3 Element Tool Bar 89    3.4.4 Model Tool Bar, 92    3.4.5 Assistant Toolbar, 92    3.4.6 Run Toolbar, 93    3.4.7 Reporting Toolbar, 95    3.4.8 Display Edit Toolbar, 96    3.4.9 Creating a New Toolbar, 99    3.5 Dialog Boxes and Property Sheets 100    3.5.1 Entry/Field Types 100    3.6 Windows 102    3.7 Layers 103    3.8 The WITNESS(R) Editor 103    3.8.1 Editor Features 103    3.8.2 Manipulating a Window 105    3.9 Window Operations 105    3.9.1 Windows Options 105    3.9.2 The Interact Box 106    3.9.3 The Clock (Time) 107    3.9.4 The Analog Clock 107    3.9.5 Copying, Cutting, and Pasting 107    3.9.6 Copy and Cut Element   s Display or Detail Features 108    3.10 The Help Facility 108    3.11 The Basic Elements 109    Questions and Exercises 109    Bibliography 110    4 Basic WITNESS(R) Modeling Techniques 111    4.1 Overview 111    4.2 Step-by-Step Model Building 111    4.3 Modeling a Simple Manufacturing Process 112    4.3.1 Define: Specifying Elements of the Manufacturing    Process Simulation Model 114    4.3.2 Detail: Adding Specifications for Elements to the Model 114    4.3.3 Display: Modifying the Appearance of Elements in the Layout Window 118    4.4 Modeling a Service Process 126    4.4.1 Service Model Example 126    4.5 WITNESS(R) Code 141    4.6 An Extended Example 141    Questions and Exercises 143    Bibliography 146    5 Modeling Material Handling Systems 149    5.1 Overview 149    5.2 Material Handling Systems 149    5.3 Material Handling Systems in WITNESS(R) 150    5.4 Modeling Conveyors 152    5.5 Modeling Paths for Labor and Parts Transit 156    5.6 Modeling Vehicles and Tracks 161    5.7 Modeling Power-&-Free Systems 167    Questions and Exercises 176    Bibliography 176    6 Basic Probability and Statistics for Simulation 179    6.1 Overview 179    6.2 Random Variables (RVs) 179    6.2.1 Examples of Discrete Random Variables 180    6.2.2 Examples of Continuous Random Variables 181    6.3 Point Estimation 182    6.4 Confidence Intervals for the Population Mean 182    6.5 Confidence Intervals for the Population Variance and Standard Deviation 184    6.6 Sample Size Determination when Estimating Population Mean 185    6.7 Theoretical Probability Distributions 186    6.7.1 The Uniform Distribution 187    6.7.2 The Normal Distribution 187    6.7.3 The Exponential Distribution 190    6.7.4 The Erlang Distribution 190    6.7.5 The Gamma Distribution 192    6.7.6 The Weibull Distribution 193    6.7.7 Triangular Distribution 193    Questions and Exercises 197    Bibliography 198    7 Simulation Input Modeling 199    7.1 Overview 199    7.2 Determining Data Requirements 200    7.3 Methods of Data Collection 202    7.4 Representing Collected Data 211    7.5 Validating Collected Data 213    7.5.1 Filtering the Data from Outliers and Wrong Measures 215    7.5.2 Testing the Data for Independence 215    7.5.3 Testing if Data are Identically Distributed 218    7.6 Fitting Probability Distributions to Collected Data 219    7.6.1 Using Empirical Distributions 225    7.7 WITNESS(R) Input Modeling 226    7.7.1 WITNESS(R) RNG 227    7.7.2 Incorporating Collected Data in WITNESS(R) 229    7.7.3 Using Databases with WITNESS(R) 233    7.8 Practical Aspects of Input Modeling 234    7.8.1 Example of Input Modeling: Auto Service Center 236    7.8.2 Example of Input Modeling: ER Simulation 243    7.9 Summary 249    Questions and Exercises 249    Bibliography 252    8 Simulation Output Analysis 253    8.1 Overview 253    8.2 Terminating Versus Steady-State Simulation 254    8.2.1 Terminating Simulation 254    8.2.2 Steady-State Simulation 257    8.3 Determining Simulation Run Controls 259    8.3.1 Determining Warm-Up Period 260    8.3.2 Determining Simulation Run Length 263    8.3.3 Determining the Number of Simulation Runs 266    8.4 Variability in Simulation Outputs 267    8.4.1 Variance Reduction Techniques 269    8.5 Simulation Output Analysis 270    8.5.1 Statistical Analysis of Simulation Outputs 272    8.5.2 Experimental Design 285    8.6 Example: Output Analyses of a Clinic Simulation 291    8.7 WITNESS(R) Modules for Simulation Output Analysis 296    8.7.1 WITNESS(R) Outputs and Charts 296    8.7.2 WITNESS(R) Costing 297    8.7.3 WITNESS(R) Scenario Manager 299    8.7.4 WITNESS(R) Documentor 299    8.7.5 WITNESS(R) Optimizer 300    8.8 Summary 300    Questions and Exercises 301    Bibliography 303    9 Model Verification and Validation Techniques 305    9.1 Overview 305    9.2 Model Verification Techniques 306    9.2.1 Verifying Model Inputs 308    9.2.2 Verifying Model Logic 309    9.2.3 Verifying Model Outputs 314    9.3 Model Validation Techniques 314    9.3.1 Validating Model Inputs 316    9.3.2 Validating Model Behavior 318    9.3.3 Validating Model Outputs 319    9.4 Verifying WITNESS(R) Models 320    9.5 Summary 330    Question and Exercise 330    Bibliography 332    10 Simulation Project Management 331    10.1 Overview 331    10.2 Define the Problem 332    10.2.1 Define the Objectives of the Study 332    10.2.2 List the Specific Issues to Be Addressed 334    10.2.3 Determine the Boundary or Domain of the Study 334    10.2.4 Determine the Level of Detail or Proper Abstraction Level 334    10.2.5 Determine if a Simulation Model is Actually Needed 335    10.2.6 Estimate the Required Resources Needed to Do the Study 335    10.2.7 Perform a Cost-Benefit Analysis 335    10.2.8 Create a Planning Chart of the Proposed Project 336    10.2.9 Write a Formal Proposal 336    10.3 Design the Study 337    10.3.1 Estimate the Life Cycle of the Model 338    10.3.2 List Broad Assumptions 338    10.3.3 Estimate the Number of Models Required 338    10.3.4 Determine the Animation Requirements 338    10.3.5 Select the Tool 339    10.3.6 Determine the Level of Data Available and What Data is Needed 339    10.3.7 Determine the Human Requirements and Skill Levels 339    10.3.8 Determine the Audience (Levels of Management) 340    10.3.9 Identify the Deliverables 340    10.3.10 Determine the Priority of the Study in Relationship to Other Studies 340    10.3.11 Set Milestone Dates 341    10.3.12 Write the Project Functional Specifications 341    10.4 Design the Conceptual Model 341    10.4.1 Decide on Continuous, Discrete, or Combined Modeling 342    10.4.2 Determine the Elements that Drive the System 342    10.4.3 Determine the Entities that Should Represent the System Elements 343    10.4.4 Determine the Level of Detail Needed to Describe the System Components 343    10.4.5 Determine the Graphics Requirements of the Model 343    10.4.6 Identify the Areas That Utilize Special Control Logic 344    10.4.7 Determine How to Collect Statistics in the Model and Communicate Results to the Customer 344    10.5 Formulate Inputs, Assumptions, and Process Definition 344    10.5.1 Specify the Operating Philosophy of the System 345    10.5.2 Describe the Physical Constraints of the System 345    10.5.3 Describe the Creation and Termination of Dynamic Elements 345    10.5.4 Describe the Process in Detail 345    10.5.5 Obtain the Operation Specifications 346    10.5.6 Obtain the Material Handling Specifications 346    10.5.7 List All the Assumptions 346    10.5.8 Analyze the Input Data 346    10.5.9 Specify the Runtime Parameters 347    10.5.10 Write the Detailed Project Functional Specifications 347    10.5.11 Validate the Conceptual Model 347    10.6 Build, Verify, and Validate the Model 348    10.7 Experiment with the Model 348    10.8 Documentation and Presentation 349    10.8.1 Project Book 350    10.8.2 Documentation of Model Input, Code, and Output 350    10.8.3 Project Functional Specifications 350    10.8.4 User Manual 350    10.8.5 Maintenance Manual 351    10.8.6 Discussion and Explanation of Model Results 351    10.8.7 Recommendations for Further Areas of Study 351    10.8.8 Final Project Report and Presentation 351    10.9 Define the Model Life Cycle 352    10.9.1 Construct User-Friendly Model Input and Output Interfaces 353    10.9.2 Determine Model and Training Responsibility 353    10.9.3 Establish Data Integrity and Collection Procedures 354    10.9.4 Perform Field Data Validation Tests 354    10.10 Summary 354    Bibliography 354    11 Manufacturing Simulation Case Studies 357    11.1 Overview 357    11.2 Hybrid Simulation of Titanium Manufacturing Process 358    11.2.1 Model Description 358    11.2.2 Model Assumptions 360    11.2.3 Process Logic 360    11.2.4 Start-up Conditions and Model Run Length 361    11.2.5 Model Input Data 361    11.2.6 Model Outputs 363    11.2.7 The WITNESS(R) Model 363    11.2.8 Model Verification and Validation 366    11.2.9 Model Experiments 367    11.2.10 Project Results and Conclusions 371    11.3 Paint Capacity Study of an Aviation Company 373    11.3.1 Paint Shop Layout 373    11.3.2 Study Assumptions 373    11.3.3 Data Collection 375    11.3.4 The WITNESS(R) Model 375    11.3.5 Study Results 375    11.3.6 Throughput Improvement Opportunities 375    11.4 Simulation of a Seamless Pipe Facility 376    11.4.1 Study Objectives Include 377    11.4.2 System Description 379    11.4.3 Input Parameters 379    11.4.4 Schedule Data 381    11.4.5 The WITNESS(R) Model 381    11.4.6 Base Model   Worst-Case Schedule 381    11.4.7 Results Summary 387    11.4.8 Observations Summary 389    11.4.9 Conclusions 393    11.5 Summary 393    Bibliography 393    12 Service Simulation Case Studies 395    12.1 Overview 395    12.2 Elements of Service Systems 396    12.2.1 System Entities 396    12.2.2 Service Providers 396    12.2.3 Customer Service 397    12.2.4 Staff and Human Resources 397    12.2.5 Facility Layout and Physical Structure 397    12.2.6 Operating Policies 398    12.3 Characteristics of Service Systems 398    12.4 Modeling Service Systems 399    12.4.1 Modeling Considerations 399    12.4.2 Model Elements 401    12.4.3 Model Control Factors 401    12.4.4 Model Performance Measures 402    12.5 Applications of Service System Simulation 402    12.5.1 Examples of Service Systems Simulation 403    12.6 Case Studies on Service Systems Simulation 404    12.6.1 Car Wash 404    12.6.2 Harbor Traffic Simulation 406    12.6.3 Bank Simulation Example 409    12.6.4 Clinic Simulation Example 411    12.6.5 Public Service Office Simulation 417    12.7 Summary 423    Bibliography 423    13 Simulation-Based Optimization Methods 425    13.1 Overview 425    13.2 Optimization Approaches in Simulation Studies 426    13.3 Simulation-Based Optimization 427    13.4 WITNESS(R) Experimenter 429    13.4.1 Comparison of Multiple Alternatives with WITNESS(R) Experimenter 429    13.4.2 More Advanced Use of the Experimenter 435    13.5 Optimization within the WITNESS(R) Experimenter 440    13.5.1 Productivity-Cost Tradeoffs Explored with the Experimenter 444    13.6 Summary 447    Questions and Exercises 447    Bibliography 448    14 Simulation for Lean Systems 449    14.1 Overview 449    14.2 Basics of Lean Systems 450    14.2.1 Lean Principles 450    14.2.2 Lean Techniques 453    14.2.3 Value Stream Mapping 454    14.3 Simulation-Based Lean Systems 457    14.3.1 Lean Simulation Example 459    14.4 Lean Using WITNESS(R) 477    14.5 Summary 485    Question and Exercises 485    Bibliography 487    15 Simulation for Six Sigma 489    15.1 Overview 489    15.2 Six Sigma Quality 490    15.2.1 Six Sigma Capability 493    15.2.2 Determining Process Sigma Rating 494    15.3 Six Sigma Methods 496    15.3.1 DMAIC Process 497    15.3.2 Design for Six Sigma (DFSS) 499    15.4 WITNESS(R) for Six Sigma 501    15.4.1 Sigma Ratings in WITNESS(R) 504    15.5 Simulation-Based Six Sigma 520    15.5.1 Simulation-Based DMAIC 520    15.5.2 Simulation-Based DFSS 526    15.5.3 Lean Six Sigma (LSS) 537    15.6 Summary 545    Questions and Exercises 546    Bibliography 547    Appendix 549    Index 553