| SDI INDUSTRY PRO:
SIMULATION FOR ENTERPRISE-WIDE PROBLEM SOLVING
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|---|---|---|
| Andrew J.
Siprelle David J. Parsons Richard A. Phelps Simulation Dynamics, Inc. 416 High Street Maryville, Tennessee 37804-5836, U.S.A. |
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| ABSTRACT | ||
| SDI Industry Pro is a versatile, high-level simulation toolset for solving problems of whole enterprises. It adds important capabilities to an existing simulation package, Extend™, which provides a robust simulation architecture and a wealth of existing building blocks. SDI Industry Pro provides the ability to build multi-level models that address everything from manufacturing lines to entire plants, and supply/distribution chains. | ||
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| "MODEL, THEN
BUILD": A MODERN APPROACH TO SYSTEMS DEVELOPMENT USING CSIM18 |
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|---|---|---|
| Herb
Schwetman Mesquite Software, Inc. PO Box 26306 Austin, TX 78755, U.S.A. |
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| ABSTRACT | ||
| Developing a behavioral model of a system prior to implementing that system provides significant benefits. In some cases, errors in the design can be detected and corrected prior to implementation. In other cases, having a means for predicting the performance of the system prior to its deployment may aid in the design, implementation and configuration of the system. This paper presents a case for developing simulation models of systems early in the design and implementation process. A number of examples illustrate the benefits which can accrue. | ||
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| NEW ADVANCES FOR WEDDING
OPTIMIZATION AND SIMULATION |
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|---|---|---|
| Fred Glover James P. Kelly Manuel Laguna School of Business, CB 419 University of Colorado Boulder, CO 80309, U.S.A. |
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| ABSTRACT | ||
| Many real world problems in optimization
are too complex to be given tractable mathematical formulations. Multiple
nonlinearities, combinatorial relationships and uncertainties often render
challenging practical problems inaccessible to modeling except by
resorting to simulation - an outcome that poses grave difficulties for
classical optimization methods. In such situations, recourse is commonly
made to itemizing a series of scenarios in the hope that at least one will
give an acceptable solution. Consequently, a long standing goal in both
the optimization and simulation communities has been to create a way to
guide a series of simulations to produce high quality solutions, in the
absence of tractable mathematical structures. Applications include the goals of finding:
Recent innovations for integrating metaheuristics, classical optimization and artificial intelligence have produced a practical software system, called OptQuest, that is capable of guiding a series of simulations to uncover optimal or near optimal solution scenarios. The advances represented by this new system open new doors for simulation as well as extending the areas to which optimization can be applied. Within the brief span since it has come into existence, OptQuest has been used in several thousand real world applications that combine simulation and optimization, and has also been used to determine optimal parameters for other computer based decision tools, to increase their effectiveness. | ||
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| EXPERTFIT: TOTAL SUPPORT
FOR SIMULATION INPUT MODELING |
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|---|---|---|
| Averill M.
Law Michael G. McComas Averill M. Law and Associates, Inc. P.O. Box 40996 Tucson, Arizona 85717 |
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| ABSTRACT | ||
| In this paper, we discuss the critical role of simulation input modeling in a successful simulation study. Two pitfalls in simulation input modeling are then presented and we explain how any analyst, regardless of their knowledge of statistics, can easily avoid these pitfalls through the use of the ExpertFit distribution-fitting software. We use a set of real-world data to demonstrate how the software automatically specifies and ranks probability distributions, and then assists the analyst in deciding whether the "best" candidate distribution actually provides a good representation of the data. If no distribution provides a good fit, then ExpertFit can define an empirical distribution. In either case, the selected distribution is put into the proper format for direct input to the analyst's simulation software. We then consider the case of selecting a distribution in the absence of data. As an example, we show how ExpertFit can be used to specify time-to-failure and repair-time distributions for a machine that is subject to random downtimes. | ||
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| ALPHA/SIM SIMULATION
SOFTWARE TUTORIAL |
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|---|---|---|
| Kendra E.
Moore Jack C. Chiang Scott D. Hammer ALPHATECH, Inc. 50 Mall Road Burlington, MA 01803-4562, U.S.A. |
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| ABSTRACT | ||
| ALPHA/Sim is a general-purpose, discrete-event simulation tool. ALPHA/Sim allows a user to graphi-cally build a simulation model, enter input data via integrated forms, execute the simulation model, and view the simulation results, within a single graphical environment. In this paper, we introduce ALPHA/Sim and de-scribe how to use ALPHA/Sim to build, simulate, and analyze a simple manufacturing system. In addition, we briefly describe some advanced features and list some sample applications. | ||
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| INTEGRATING THE CAD
MODEL WITH DYNAMIC SIMULATION: SIMULATION DATA EXCHANGE
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|---|---|---|
| Shreekanth
Moorthy Engineering Animation, Inc. 24800 Northwestern Highway Southfield, MI, U.S.A. |
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| ABSTRACT | ||
| Engineering Animation, Inc. (EAI) has
developed a number of intelligent CAD objects for facilities design. These
objects allow the facility designer to design and modify the facility
layout with minimal effort and tedious drafting
duplication. Facility Layouts that are designed by the facilities group often have to be dynamically simulated to prove the concept and to determine if the required throughput (jobs per hour) can be achieved. Traditionally this requires the simulation engineer to duplicate the CAD drawing in the simulation environment before being able to model it. This is also not a one-time duplication of work as the facility layout can go through numerous revisions before the final equipment configuration is determined. FactoryCAD® layout objects are embedded with simulation relevant data such as Time to Fail, Time to Repair, Cycle times, Scrap rates, Speeds, et cetera. An intelligent extraction routine then exports object details such as type of object (machine, conveyor, buffer, etc.), object location, and other physical parameters, along with all simulation relevant data that had been previously embedded into the objects from the layout into a standardized ASCII text file. This will eliminate the need to recreate physical and even some run control information in the dynamic simulation package. It is proposed that the most effective data transfer would be to create a common data format (Simulation Data Exchange - SDX) that can serve as an input to the automatic generation of discrete event simulation models. The simulation model generates animation data that is subsequently available for dynamic viewing and analysis in the FactoryVIEW™ environment. | ||
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| AN OVERVIEW OF FULLY
INTEGRATED DIGITAL MANUFACTURING TECHNOLOGY
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|---|---|---|
| Scott
Freedman Deneb Robotics, Inc. 5500 New King Street Troy, Michigan 48098-2615, U.S.A. |
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| ABSTRACT | ||
| Typically, the Winter Simulation Conference has generally focused on Discrete Event Simulation and Capacity Modeling. This paper will discuss integration of several of the engineering simulation systems involved in the design and manufacturing of capital intensive products. The purpose of this paper is to foster discussion on the benefits of an integrated data environment for design through production. | ||
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| SIMULATION
INTEROPERABILITY USING MICRO SAINT SIMULATION SOFTWARE |
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|---|---|---|
| Wendy K.
Bloechle K. Ronald Laughery, Jr. Micro Analysis and Design, Inc. 4900 Pearl East Circle Boulder, Colorado 80301, U.S.A. |
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| ABSTRACT | ||
| For the past fifteen years, Micro Saint
simulation software has been helping people answer questions on how to
make their businesses more profitable and productive. Recently, customers
have requested that Micro Saint have the capability to communicate and
exchange information with other programs. In response to this request, COM
Services was added to the most recent release of Micro Saint.
This paper will focus on the new features of Micro Saint 3.1 and specifically COM Services. | ||
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| AN INTEGRATED TOOLKIT
FOR ENTERPRISE MODELING AND ANALYSIS |
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|---|---|---|
| Dursun
Delen Perakath C. Benjamin Madhav Erraguntla Knowledge Based Systems, Inc. (KBSI) College Station, TX 77840, U.S.A. |
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| ABSTRACT | ||
| A fully integrated modeling and analysis toolkit, which facilitates multi-perspective knowledge capturing, sharing and reusing, is necessary for today's enterprises to meet the challenges of the ever more competitive global marketplace. In this paper we present a suit of software tools, designed and developed by Knowledge Based Systems, Inc., that can generate integrated solutions to complicated enterprise analysis including business process reengineering, activity based costing, and training. We start by providing a high level conceptual framework in which the individual tools with their roles and interrelations are presented. We then introduce each tool that make up the enterprise modeling and analysis toolkit in detail. The tutorial focuses on the ease and the user friendliness of (1) capturing domain knowledge into interchangeable multi-perspective models, (2) automatically generating and executing stochastic and deterministic analysis models from these multi-perspective models, and (3) publishing enterprise modeling and analysis results on the web. | ||
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| MICRO-GPSS ON THE WEB
AND FOR WINDOWS A TOOL FOR INTRODUCTION TO SIMULATION IN HIGH SCHOOLS
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|---|---|---|
| Henry Herper
Institute for Simulation and Graphics Otto-von-Guericke University D-39016 Magdeburg, GERMANY |
Ingolf
Stàhl Department of Managerial Economics Stockholm School of Economics S-11383 Stockholm, SWEDEN | |
| ABSTRACT | ||
| There is a demand in European high schools for learning discrete-event simulation. The best system for this appears to be micro-GPSS. Up to now, micro-GPSS has lacked a Graphical User Interface for the build up of models. In this paper, two projects for such a GUI system are presented: WebGPSS, where the GUI is developed as a Java-Applet and the system runs over the Web, and WinGPSS, developed in Delphi to allow for a complete interface with other Window programs. | ||
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| NETWORK SIMULATIONS WITH
OPNET |
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|---|---|---|
| Xinjie
Chang ITTC, EECS University of Kansas, USA |
K. R. Subramaniang
Network Technology Research Center School of EEE Nanyang Technological University SINGAPORE 639798 | |
| ABSTRACT | ||
| Several computer network simulators are compared. One of the most powerful software simulation package-OPNET is introduced in detail. The implementation details of the network models in OPNET are given. Some simulation examples are also illustrated. | ||
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