Chung Simulation Modeling Handbook

A Practical Approach
Erscheinungsjahr 2003
ISBN: 978-1-135-51360-3
Verlag: Taylor & Francis
Format: EPUB
Kopierschutz: Adobe DRM (»Systemvoraussetzungen)

E-Book, Englisch, 608 Seiten

Reihe: INDUSTRIAL AND MANUFACTURING ENGINEERING SERIES

The use of simulation modeling and analysis is becoming increasingly more popular as a technique for improving or investigating process performance. This book is a practical, easy-to-follow reference that offers up-to-date information and step-by-step procedures for conducting simulation studies. It provides sample simulation project support material, including checklists, data-collection forms, and sample simulation project reports and publications to facilitate practitioners' efforts in conducting simulation modeling and analysis projects.

Simulation Modeling Handbook: A Practical Approach has two major advantages over other treatments. First, it is independent of any particular simulation software, allowing readers to use any commercial package or programming language. Second, it was written to insulate practitioners from unnecessary simulation theory that does not focus on their average, practical needs.

As the popularity of simulation studies continues to grow, the planning and execution of these projects, more and more engineering and management professionals will be called upon to perform these tasks. With its simple, no-nonsense approach and focus on application rather than theory, this comprehensive and easy-to-understand guide is the ideal vehicle for acquiring the background and skills needed to undertake effective simulation projects.

Features

- Presents step-by-step procedures for conducting successful simulation modeling and analysis

- Addresses every phase of performing simulations, from formulating the problem to presenting study results and recommendations

- Uses approaches applicable regardless of the specific simulation or software used

- Includes a summary of the major simulation software packages and discusses the pros and cons of using general purpose programming languages

Zielgruppe

Practicing industrial and manufacturing engineers involved in manufacturing, service, and transportation-related industries; Professors and research associates involved in industrial engineering, transportation engineering, industrial engineering technology, and decision and information sciences

Autoren/Hrsg.

Chung, Christopher A.

Fachgebiete

• Mathematik | Informatik EDV | Informatik Professionelle Anwendung Computersimulation & Modelle, 3-D Graphik

Inhaltsverzeichnis

INTRODUCTION

Simulation Modeling and Analysis
Other Types of Simulation Models
Purposes of Simulation
Advantages to Simulation
Disadvantages to Simulation
Other Considerations
Famous Simulation Quotes
Basic Simulation Concepts
Additional Basic Simulation Issues
Summary

PROBLEM FORMULATION

Formal Problem Statement
Orientation
Project Objectives
Summary

PROJECT PLANNING

Project Management Concepts
Simulation Project Manager Functions
Developing the Simulation Project Plan
Compressing Projects
Example Gantt Chart
Advanced Project Management Concepts
Project Management Software Packages
Summary

SYSTEM DEFINITION

System Classifications
High-Level Flow Chart Basics
Components and Events to Model
Data to Be Included in the Model
Output Data
Summary

INPUT DATA COLLECTION AND ANALYSIS

Sources for Input Data
Collecting Input Data
Deterministic versus Probabilistic Data
Discrete versus Continuous Data
Common Input Data Distributions
Less Common Distributions
Offset Combination Distributions
Analyzing Input Data
How Much Data Needs to Be Collected
What Happens if I Cannot Fit the Input Data?
Software Implementations for Data Fitting
Summary

MODEL TRANSLATION

Simulation Program Selection
Model Translation Section Content
Program Organization
Summary

VERIFICATION

Divide-and-Conquer Approach
Animation
Advancing the Simulation Clock by Event by Event
Writing to an Output File
Summary

VALIDATION

Assumptions
Simplifications
Oversights
Limitations
Need for Validation
Two Types of Validation
Face Validity
Statistical Validity
Validation Data Analysis Process
When a Model Cannot Be Statistically Validated and What to Do About It
Summary

EXPERIMENTAL DESIGN

Factors and Levels
Two Alternative Experimental Designs
One-Factor Experimental Designs
Two-Factor Experimental Designs
Multifactor Experimental Designs
2^k Experimental Designs
Experimental Alternative Factor Interactions
Refining the Experimental Alternatives
Summary

ANALYSIS

Terminating System Analysis
Non-Terminating System Analysis
Summary

PROJECT REPORTS AND PRESENTATIONS

Written Report Guidelines
Executive Summary
Equations
Importing Screen Captures
Presentation Guidelines
Presentation Media
Electronic Presentation Software Issues
Actual Presentation
Summary

TRAINING SIMULATORS

Problem Formulation
Project Planning
System Definition
Input Data Collection
Model Translation
Verification
Validation
Implementation
Summary

EXAMPLES

ARENA USER'S MINIMANUAL

SIMULATION USING AUTOMOD AND AUTOSTAT

SIMPAK USER'S MINIMANUAL

APPENDIXES