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Simulation with Arena 6th edition [Kõva köide]

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  • Formaat: Hardback, 656 pages, kõrgus x laius x paksus: 239x191x31 mm, kaal: 1152 g, 704 Illustrations
  • Ilmumisaeg: 16-May-2014
  • Kirjastus: McGraw Hill Higher Education
  • ISBN-10: 0073401315
  • ISBN-13: 9780073401317
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Simulation with Arena 6th editionSuurem pilt
  • Formaat: Hardback, 656 pages, kõrgus x laius x paksus: 239x191x31 mm, kaal: 1152 g, 704 Illustrations
  • Ilmumisaeg: 16-May-2014
  • Kirjastus: McGraw Hill Higher Education
  • ISBN-10: 0073401315
  • ISBN-13: 9780073401317
Teised raamatud teemal:
Püsilink: https://www.kriso.ee/db/9780073401317.html
Märksõnad:
Provides a comprehensive treatment of simulation using industry-standard Arena software. This title features statistical design and analysis of simulation experiments that is integrated with the modeling chapters, reflecting the importance of mathematical modeling of these activities. Simulation with Arena provides a comprehensive treatment of simulation using industry-standard Arena software. The text starts by having the reader develop simple high-level models, and then progresses to advanced modeling and analysis. Statistical design and analysis of simulation experiments is integrated with the modeling chapters, reflecting the importance of mathematical modeling of these activities.An informal, tutorial writing style is used to aid the beginner in fully understanding the ideas and topics presented. The academic version of Arena and example files are available through the books website.McGraw-Hill is proud to offer Connect with the sixth edition of Keltons,Simulation with Arena. This innovative and powerful system helps your students learn more efficiently and gives you the ability to customize your homework problems simply and easily. Track individual student performance - by question, assignment, or in relation to the class overall with detailed grade reports. ConnectPlus provides students with all the advantages ofConnect, plus 24/7 access to an eBook.Keltons Simulation with Arena, sixth edition, includes the power ofMcGraw-Hills LearnSmart a proven adaptive learning system that helps students learn faster, study more efficiently, and retain more knowledge through a series of adaptive questions. This innovative study tool pinpoints concepts the student does not understand and maps out a personalized plan for success.
Chapter 1 What Is Simulation? 1(14)
1.1 Modeling
1(4)
1.1.1 What's Being Modeled?
2(1)
1.1.2 How About Just Playing with the System?
3(1)
1.1.3 Sometimes You Can't (or Shouldn't) Play with the System
3(1)
1.1.4 Physical Models
4(1)
1.1.5 Logical (or Mathematical) Models
4(1)
1.1.6 What Do You Do with a Logical Model?
4(1)
1.2 Computer Simulation
5(3)
1.2.1 Popularity and Advantages
5(1)
1.2.2 The Bad News
6(1)
1.2.3 Different Kinds of Simulations
7(1)
1.3 oHow Simulations Get Done
8(4)
1.3.1 By Hand
8(2)
1.3.2 Programming in General-Purpose Languages
10(1)
1,3.3 Simulation Languages
10(1)
1.3.4 High-Level Simulators
10(1)
1.3.5 Where Arena Fits In
11(1)
1.4 When Simulations Are Used
12(3)
1.4.1 The Early Years
12(1)
1.4.2 The Formative Years
12(1)
1.4.3 The Recent Past
13(1)
1.4.4 The Present
13(1)
1.4.5 The Future
14(1)
Chapter 2 Fundamental Simulation Concepts 15(38)
2.1 An Example
15(3)
2.1.1 The System
15(2)
2.1.2 Goals of the Study
17(1)
2.2 Analysis Options
18(2)
2.2.1 Educated Guessing
18(1)
2.2.2 Queueing Theory
19(1)
2.2.3 Mechanistic Simulation
20(1)
2.3 Pieces of a Simulation Model
20(5)
2.3.1 Entities
20(1)
2.3.2 Attributes
21(1)
2.3.3 (Global) Variables
21(1)
2.3.4 Resources
22(1)
2.3.5 Queues
22(1)
2.3.6 Statistical Accumulators
23(1)
2.3.7 Events
23(1)
2.3.8 Simulation Clock
24(1)
2.3.9 Starting and Stopping
24(1)
2.4 Event-Driven Hand Simulation
25(7)
2.4.1 Outline of the Action
25(1)
2.4.2 Keeping Track of Things
26(2)
2.4.3 Carrying It Out
28(4)
2.4.4 Finishing Up
32(1)
2.5 Event- and Process-Oriented Simulation
32(2)
2.6 Randomness in Simulation
34(3)
2.6.1 Random Input, Random Output
34(1)
2.6.2 Replicating the Example
35(1)
2.6.3 Comparing Alternatives
36(1)
2.7 Simulating with Spreadsheets
37(10)
2.7.1 A News Vendor Problem
37(6)
2.7.2 A Single-Server Queue
43(4)
2.7.3 Extensions and Limitations
47(1)
2.8 Overview of a Simulation Study
47(1)
2.9 Exercises
48(5)
Chapter 3 A Guided Tour Through Arena 53(68)
3.1 Starting Up
53(2)
3.2 Exploring the Arena Window
55(7)
3.2.1 Opening a Model
55(1)
3.2.2 Basic Interaction and Pieces of the Arena Window
56(2)
3.2.3 Panning, Zooming, Viewing, and Aligning in the Flowchart View
58(2)
3.2.4 Modules
60(1)
3.2.5 Internal Model Documentation
61(1)
3.3 Browsing Through an Existing Model: Model 3-1
62(17)
3.3.1 The Create Flowchart Module
62(1)
3.3.2 The Entity Data Module
63(1)
3.3.3 The Process Flowchart Module
64(2)
3.3.4 The Resource Data Module
66(1)
3.3.5 The Queue Data Module
67(1)
3.3.6 Animating Resources and Queues
67(1)
3.3.7 The Dispose Flowchart Module
67(1)
3.3.8 Connecting Flowchart Modules
68(1)
3.3.9 Dynamic Plots
69(2)
3.3.10 Dressing Things Up
71(1)
3.3.11 Setting the Run Conditions
72(1)
3.3.12 Running It
73(1)
3.3.13 Viewing the Reports
74(5)
3.4 Building Model 3-1 Yourself
79(11)
3.4.1 New Model Window and Basic Process Panel
80(1)
3.4.2 Place and Connect the Flowchart Modules
81(1)
3.4.3 The Create Flowchart Module
81(1)
3.4.4 Displays
82(1)
3.4.5 The Entity Data Module
83(1)
3.4.6 The Process Flowchart Module
83(1)
3.4.7 The Resource and Queue Data Modules
84(1)
3.4.8 Resource Animation
84(1)
3.4.9 The Dispose Flowchart Module
85(1)
3.4.10 Dynamic Plots
85(3)
3.4.11 Window Dressing
88(1)
3.4.12 The Run > Setup Dialog Boxes
89(1)
3.4.13 Establishing Named Views
89(1)
3.5 Case Study: Specialized Serial Processing vs. Generalized Parallel Processing
90(8)
3.5.1 Model 3-2: Serial Processing - Specialized Separated Work
90(3)
3.5.2 Model 3-3: Parallel Processing.: Generalized Integrated Work
93(2)
3.5.3 Models 3-4 and 3-5: The Effect of Task-Time Variability
95(3)
3.6 More on Menus, Toolbars, Drawing, and Printing
98(10)
3.6.1 Menus
98(5)
3.6.2 Toolbars
103(3)
3.6.3 Drawing
106(1)
3.6.4 Printing
107(1)
3.7 Help!
108(1)
3.8 More on Running Models
109(1)
3.9 Summary and Forecast
110(1)
3.10 Exercises
110(11)
Chapter 4 Modeling Basic Operations and Inputs 121(86)
4.1 Model 4-1: An Electronic Assembly and Test System
121(17)
4.1.1 Developing a Modeling Approach
122(1)
4.1.2 Building the Model
123(11)
4.1.3 Running the Model
134(2)
4.1.4 Viewing the Results
136(2)
4.2 Model 4-2: The Enhanced Electronic Assembly and Test System
138(15)
4.2.1 Expanding Resource Representation: Schedules and States
139(1)
4.2.2 Resource Schedules
140(4)
4.2.3 Resource Failures
144(2)
4.2.4 Frequencies
146(3)
4.2.5 Results of Model 4-2
149(4)
4.3 Model 4-3: Enhancing the Animation
153(9)
4.3.1 Changing Animation Queues
154(2)
4.3.2 Changing Entity Pictures
156(2)
4.3.3 Adding Resource Pictures
158(2)
4.3.4 Adding Variables and Plots
160(2)
4.4 Model 4-4: The Electronic Assembly and Test System with Part Transfers
162(9)
4.4.1 Some New Arena Concepts: Stations and Transfers
162(2)
4.4.2 Adding the Route Logic
164(3)
4.4.3 Altering the Animation
167(4)
4.5 Finding and Fixing Errors
171(7)
4.6 Input Analysis: Specifying Model Parameters and Distributions
178(16)
4.6.1 Deterministic vs. Random Inputs
179(1)
4.6.2 Collecting Data
180(1)
4.6.3 Using Data
181(1)
4.6.4 Fitting Input Distributions via the Input Analyzer
182(8)
4.6.5 No Data?
190(3)
4.6.6 Nonstationary Arrival Processes
193(1)
4.6.7 Multivariate and Correlated Input Data
194(1)
4.7 Summary and Forecast
194(1)
4.8 Exercises
194(13)
Chapter 5 Modeling Detailed Operations 207(72)
5.1 Model 5-1: A Simple Call Center System
208(1)
5.2 New Modeling Issues
209(3)
5.2.1 Customer Rejections and Balking
209(1)
5.2.2 Three-Way Decisions
210(1)
5.2.3 Variables and Expressions
210(1)
5.2.4 Storages
211(1)
5.2.5 Terminating or Steady State
211(1)
5.3 Modeling Approach
212(2)
5.4 Building the Model
214(23)
5.4.1 Create Arrivals and Direct to Service
214(6)
5.4.2 Arrival Cutoff Logic
220(2)
5.4.3 Technical Support Calls
222(3)
5.4.4 Sales Calls
225(1)
5.4.5 Order-Status Calls
226(6)
5.4.6 System Exit and Run Setup
232(2)
5.4.7 Animation
234(3)
5.5 Model 5-2: The Enhanced Call Center System
237(13)
5.5.1 The New Problem Description
237(2)
5.5.2 New Concepts
239(2)
5.5.3 Defining the Data
241(4)
5.5.4 Modifying the Model
245(5)
5.6 Model 5-3: The Enhanced Call Center with More Output Performance Measures
250(7)
5.7 Model 5-4: An (s, S) Inventory Simulation
257(13)
5.7.1 System Description
257(2)
5.7.2 Simulation Model
259(11)
5.8 Summary and Forecast
270(1)
5.9 Exercises
271(8)
Chapter 6 Statistical Analysis of Output from Terminating Simulations 279(32)
6.1 Time Frame of Simulations
280(1)
6.2 Strategy for Data Collection and Analysis
280(2)
6.3 Confidence Intervals for Terminating Systems
282(5)
6.4 Comparing Two Scenarios
287(4)
6.5 Evaluating Many Scenarios with the Process Analyzer (PAN)
291(5)
6.6 Searching for an Optimal Scenario with OptQuest
296(6)
6.7 Periodic Statistics
302(1)
6.8 Summary and Forecast
303(1)
6.9 Exercises
303(8)
Chapter 7 Intermediate Modeling and Steady-State Statistical Analysis 311(34)
7.1 Model 7-1: A Small Manufacturing System
311(19)
7.1.1 New Arena Concepts
312(2)
7.1.2 The Modeling Approach
314(1)
7.1.3 The Data Modules
315(2)
7.1.4 The Logic Modules
317(7)
7.1.5 Animation
324(2)
7.1.6 Verification
326(4)
7.2 Statistical Analysis of Output from Steady-State Simulations
330(9)
7.2.1 Warm-up and Run Length
330(4)
7.2.2 Truncated Replications
334(1)
7.2.3 Batching in a Single Run
335(3)
7.2.4 What To Do?
338(1)
7.2.5 Other Methods and Goals for Steady-State Statistical Analysis
339(1)
7.3 Summary and Forecast
339(1)
7.4 Exercises
339(6)
Chapter 8 Entity Transfer 345(34)
8.1 Types of Entity Transfers
345(2)
8.2 Model 8-1: The Small Manufacturing System with Resource-Constrained Transfers
347(4)
8.3 The Small Manufacturing System with Transporters
351(14)
8.3.1 Model 8-2: The Modified Model 8-1 for Transporters
352(7)
8.3.2 Model 8-3: Refining the Animation for Transporters
359(6)
8.4 Conveyors
365(9)
8.4.1 Model 8-4: The Small Manufacturing System with Nonaccumulating Convenyors
368(5)
8.4.2 Model 8-5: The Small Manufacturing System with Accumulating Conveyors
373(1)
8.5 Summary and Forecast
374(1)
8.6 Exercises
374(5)
Chapter 9 A Sampler of Further Modeling Issues and Techniques 379(44)
9.1 Modeling Conveyors Using the Advanced Transfer Panel
379(6)
9.1.1 Model 9-1: Finite Buffers at Stations
380(4)
9.1.2 Model 9-2: Parts Stay on Conveyor During Processing
384(1)
9.2 More on Transporters
385(1)
9.3 Entity Reneging
386(9)
9.3.1 Entity Balking and Reneging
386(1)
9.3.2 Model 9-3: A Service Model with Balking and Reneging
387(8)
9.4 Holding and Batching Entities
395(7)
9.4.1 Modeling Options
395(1)
9.4.2 Model 9-4: A Batching Process Example
396(6)
9.5 Overlapping Resources
402(11)
9.5.1 System Description
402(2)
9.5.2 Model 9-5: A Tightly Coupled Production System
404(6)
9.5.3 Model 9-6: Adding Part-Status Statistics
410(3)
9.6 A Few Miscellaneous Modeling Issues
413(3)
9.6.1 Guided Transporters
414(1)
9.6.2 Parallel Queues
414(1)
9.6.3 Decision Logic
415(1)
9.7 Exercises
416(7)
Chapter 10 Arena Integration and Customization 423(56)
10.1 Model 10-1: Reading and Writing Data Files
423(19)
10.1.1 Model 10-2: Reading Entity Arrivals from a Text File
425(4)
10.1.2 Model 10-3 and Model 10-4: Reading and Writing Access and Excel Files
429(7)
10.1.3 Advanced Reading and Writing
436(4)
10.1.4 Model 10-5: Reading in String Data
440(2)
10.1.5 Direct Read of Variables and Expressions
442(1)
10.2 VBA in Arena
442(12)
10.2.1 Overview of ActiveX Automation and VBA
442(2)
10.2.2 Built-In Arena VBA Events
444(4)
10.2.3 Arena's Object Model
448(3)
10.2.4 Arena's Macro Recorder
451(3)
10.3 Model 10-6: Presenting Arrival Choices to the User
454(11)
10.3.1 Modifying the Creation Logic
455(1)
10.3.2 Designing the VBA UserForm
456(2)
10.3.3 Displaying the Form and Setting Model Data
458(7)
10.4 Model 10-7: Recording and Charting Model Results in Microsoft Excel
465(7)
10.4.1 Setting Up Excel at the Beginning of the Run
466(3)
10.4.2 Storing Individual Call Data Using the VBA Module
469(2)
10.4.3 Charting the Results and Cleaning Up at the End of the Run
471(1)
10.5 Arena Template Building Capabilities
472(1)
10.6 Arena Visual Designer
473(4)
10.6.1 Overview of Visual Designer
473(2)
10.6.2 Dashboards
475(1)
10.6.3 3D Scenes
475(2)
10.7 Summary and Forecast
477(1)
10.8 Exercises
477(2)
Chapter 11 Continuous and Combined Discrete/Continuous Models 479(40)
11.1 Modeling Simple Discrete/Continuous Systems
480(7)
11.1.1 Model 11-1: A Simple Continuous System
480(3)
11.1.2 Model 11-2: Interfacing Continuous and Discrete Logic
483(4)
11.2 A Coal-Loading Operation
487(18)
11.2.1 System Description
488(1)
11.2.2 Modeling Approach
489(2)
11.2.3 Model 11-3: Coal Loading with Continuous Approach
491(10)
11.2.4 Model 11-4: Coal Loading with Flow Process
501(4)
11.3 Continuous State-Change Systems
505(9)
11.3.1 Model 11-5: A Soaking-Pit Furnace
505(1)
11.3.2 Modeling Continuously Changing Rates
506(1)
11.3.3 Arena's Approach for Solving Differential Equations
507(1)
11.3.4 Building the Model
508(4)
11.3.5 Defining the Differential Equations Using VBA
512(2)
11.4 Summary and Forecast
514(1)
11.5 Exercises
514(5)
Chapter 12 Further Statistical Issues 519(30)
12.1 Random-Number Generation
519(6)
12.2 Generating Random Variates
525(4)
12.2.1 Discrete
525(2)
12.2.2 Continuous
527(2)
12.3 Nonstationary Poisson Processes
529(1)
12.4 Variance Reduction
530(8)
12.4.1 Common Random Numbers
531(6)
12.4.2 Other Methods
537(1)
12.5 Sequential Sampling
538(7)
12.5.1 Terminating Models
539(4)
12.5.2 Steady-State Models
543(2)
12.6 Designing and Executing Simulation Experiments
545(1)
12.7 Exercises
546(3)
Chapter 13 Conducting Simulation Studies 549(18)
13.1 A Successful Simulation Study
549(3)
13.2 Problem Formulation
552(1)
13.3 Solution Methodology
553(1)
13.4 System and Simulation Specification
554(4)
13.5 Model Formulation and Construction
558(2)
13.6 Verification and Validation
560(3)
13.7 Experimentation and Analysis
563(1)
13.8 Presenting and Preserving the Results
564(1)
13.9 Disseminating the Model
565(2)
Appendix A: A Functional Specification for The Washington Post 567(12)
A.1 Introduction
567(2)
A.1.1 Document Organization
567(1)
A.1.2 Simulation Objectives
567(1)
A.1.3 Purpose of the Functional Specification
568(1)
A.1.4 Use of the Model
568(1)
A.1.5 Hardware and Software Requirements
568(1)
A.2 System Description and Modeling Approach
569(6)
A.2.1 Model Timeline
569(1)
A.2.2 Presses
569(2)
A.2.3 Product Types
571(1)
A.2.4 Press Packaging Lines
571(1)
A.2.5 Tray System
571(1)
A.2.6 Truck Arrivals
572(1)
A.2.7 Docks
573(1)
A.2.8 Palletizers
573(1)
A.2.9 Manual Insertion Process
574(1)
A.3 Anination
575(1)
A.4 Summary of Input and Output
575(2)
A.4.1 Model Input
575(1)
A.4.2 Model Output
576(1)
A.5 Project Deliverables
577(1)
A.5.1 Simulation Model Documentation
577(1)
A.5.2 User's Manual
577(1)
A.5.3 Model Validation
577(1)
A.5.4 Animation
578(1)
A.6 Acceptance
578(1)
Appendix B: A Refresher on Probability and Statistics 579(18)
B.1 Probability Basics
579(2)
B.2 Random Variables
581(8)
B.2.1 Basics
581(1)
B.2.2 Discrete
582(2)
B.2.3 Continuous
584(2)
B.2.4 Joint Distributions, Covariance, Correlation, and Independence
586(3)
B.3 Sampling and Sampling Distributions
589(2)
B.4 Point Estimation
591(1)
B.5 Confidence Intervals
591(2)
B.6 Hypothesis Tests
593(2)
B.7 Exercises
595(2)
Appendix C: Arena's Probability Distributions 597(16)
C.1 Beta
599(1)
C.2 Continuous
600(2)
C.3 Discrete
602(1)
C.4 Erlang
603(1)
C.5 Exponential
604(1)
C.6 Gamma
605(1)
C.7 Johnson
606(1)
C.8 Lognormal
607(1)
C.9 Normal
608(1)
C.10 Poisson
609(1)
C.11 Triangular
610(1)
C.12 Uniform
611(1)
C.13 Weibull
612(1)
Appendix D: Academic Software Installation Instructions 613(2)
D.1 Authorization to Copy Software
613(1)
D.2 Installing the Arena Software
613(1)
D.3 System Requirements
614(1)
References 615(4)
Index 619