A complex array of advanced manufacturing technologies is routinely employed in manufacturing plants, including advanced quality systems, statistical process control, automation, robotics, lean and agile manufacturing, and just-in-time processing. The impact of these techniques on the quality and reliability of consumer products is impressive; the impact on productivity and profitability of the manufacturers is unproven.

Recent statistics on total factor productivity, which takes into account the impact of the capital employed, suggest that the manufacturing industry is heading toward capital deepening and smaller margins, rather than toward a more prosperous future. Our research confirms that cost dynamics is a critical factor in the long-term viability of a business. Even with the best process control techniques, variation due to common causes renders manufacturing systems profitable sometimes, but not all the time!

One way to study the dynamics of product cost is through simulation and comparison of the simulation with actual performance. CAMM's manufacturing economics research team uses system dynamics (SD), discrete-event (DE) or hybrid software depending on the nature of the problem.

In dynamic modeling of product cost, the end objective defines a "precision spectrum." At one end, we have the "30,000-foot view," with long-term time horizons and less detailed modeling of the process, where systems dynamics applications like iThink are typically employed. At the other end, we have the "plant floor" view, with extremely detailed representations of all aspects of the process in question, where we would use Simul8 and Arena.

GoldSim


GoldSim is what we would consider a hybrid-modeling package; we have found it to be quite capable in the modeling of continuous systems and at the same time to be easily applied to the simulation of discrete events. In our case, it has quickly become our software of choice for systems dynamics modeling, and although it is not an Arena or Simul8, it is also an excellent tool for "near plant floor" questions. Our understanding is that this software was not designed for business analysis or for industrial engineering applications; its roots are in the environmental arena of complex interrelations between time-delayed effects and multiple originating causes. GoldSim is nonetheless an effective tool for strategic business analysis. This is in keeping with recent perceptions that business is its own "environment" and not a collection of separate functional operations.

The learning curve for a user of GoldSim is relatively steep, and can be traversed with relative ease, thanks to a clear description of the individual model elements and very good pop-up menus. The recent addition of tutorials and on-line help has been especially helpful for new users, and both nicely compliment the excellent printed documentation and example models. Less obvious are the more subtle uses of delays and discrete events to simulate the more complex interactions of resources and information. These features, designed for more advanced users, add major capabilities to this software and are not commonly available in other products that we have seen.

GoldSim does not have capability to identify entities and entity attributes; this necessitates fairly complex logic statements to accurately handle the flow of products through shared resources. In cases where there are a significant number of different products flowing through the system, we generally turn to pure discrete-event software.

Other features of GoldSim make it a good tool for our research on cost dynamics. The capability of easy read-write to and from spreadsheets is a major asset, and it solves one of the problems in introducing dynamic software to industrial managers. Product managers and R&D portfolio managers are familiar with business analysis done in spreadsheets, but consider dynamic software not worth the complexity of dealing with unfriendly interfaces.

The "control panel" common to SD software and easily created in most DE software is not highly developed in GoldSim, but we suggest that energy spent in this direction would not be well rewarded. We have found "control panels" and "flight simulators" singularly unpopular with mangers, who regard sliders and moving graphs with suspicion, because of the lack of transparency in the underlying logic.

As we become more familiar with the software, we have developed a "wish list" of features that we would like to see developed in GoldSim. It is our impression from discussions with the software developers that they are interested in taking user feedback and building new and effective capabilities into an expanding suite of tools.

We have tested GoldSim in teaching a manufacturing business strategy course with fourth-year engineering undergraduates, and the response has been so positive that we have included GoldSim models in the interactive CD tutorials of our textbook, "Manufacturing in Real-Time" [1].

A GoldSim Economic Model


This is one of the tutorials mentioned earlier and is designed to study the variation of cost in a simple manufacturing system producing hand-made pottery cups. Figure 1, which is the upper level of the simulation, shows the different stages of production as well as the flow of information into working inventories and cost calculators. This level gives a clear view of what is being studied and pop-up comments appear on each element and help to elaborate on its function. The product stream of making a pottery cup involves continuous and discrete operations, batching and unbatching, control of inventories and lot sizes, as well as economic calculations. The ability to combine discrete events with continuous flow governed by a running clock makes simulation of all these aspects fairly easy. In addition, it is possible to simulate price and market demand changes over a period of time by the use of conditional containers and correlated stochastic input variables.



Figure 1: GoldSim can model both discrete and continuous events as demonstrated by the product stream of making a cup.

Clicking on the plus sign of each container reveals the workings of each stage. In Figure 2 we have expanded the high temperature firing stage, which illustrates the handling of a discrete event (kiln firing), triggered by information which prioritizes the use of resources and tracks their utilization. Note that all of the process and economic inputs in this stage and right through the model are statistical distributions and not single numbers.



Figure 2: Kiln firing illustrates the software's handing of a discrete event.

Expanding the second level container on the logic for loading the kiln (Figure 3) shows the complexity of the logic associated with sharing resources and prioritizing tasks. Developing and modeling this logic is not an easy task in GoldSim, and this particular example demonstrates this shortcoming.



Figure 3: The logic for loading the kiln is complex, as illustrated here.

The outputs can be shown with the use of a control panel (Figure 4), which is quickly built from user-friendly menus, and the statistical results are viewable by clicking on a button.



Figure 4: A quickly built control panel shows the outputs.

Some of the outputs demonstrate the variation in business conditions and the relationships between "time in system" (indicated by shipping frequency), cost and price. Figures 5a and 5b summarize the financial performance of the business with net operating profit before tax (NOPAT) and economic value added (EVA). These key business indicators will vary with inputs from the control panel sliders and allow a thorough analysis of business conditions. GoldSim does not have a built-in optimizer. However, data is easily exported for post-processing.



Figure 5a: Financial performance: net operating profit after tax (NOPAT)



Figure 5b: Financial performance: economic value added.



Figure 6: Time is money: Output of turn rates.

GoldSim is an excellent bridge between the worlds of system dynamics and discrete-event simulation, providing a means of including otherwise difficult scenario descriptions within strategic models. Overall, we feel that GoldSim offers a tool that is expanding in functionality; one that addresses the needs of the community of users who apply dynamic simulation to operations research and management science.

Product Summary GoldSim is distributed by the GoldSim Technology Group of Golder Associates 18300 NE Union Hill Road, Suite 200,Redmond, WA 98052-3333 USA Phone: 425-883-0777 Fax: 425-882-5498 Web site: www.goldsim.com E-mail: software@goldsim.com Pricing Information There are three versions of GoldSim: Professional, Research and Academic. The Professional version retails for $3,950. The Research version retails for $950. Both include a one-year subscription to upgrades and basic technical support, as well as an hour of live Web-based training. The Research version (which has the same functionality as the Professional version) is only available to university researchers. GoldSim Academic (limited to models with 500 objects) is made available for free to students and instructors for use in teaching and non-funded research projects. Simulations created in both versions can be shared with others using the free GoldSim Player, which allows those without a GoldSim Professional or Academic license to view model logic, modify variables in a "dashboard" type interface, and run the simulation. System Requirements • Windows 98, ME, NT 4 (Service Pack 4 or higher), 2000 or XP • Administrative Privileges on the system during the installation process • Microsoft Internet Explorer 4.01 (SP2) or higher • Pentium-class PC (300 MHz or higher recommended) • 32 megabytes of RAM (64 MB recommended) • Disk Space required: 50 MB of free space in the target directory and 15 MB of free space in Common Files folder. During the installation a minimum of 80 MB is required.

Vendor Comments Editor's note: It is the policy of OR/MS Today to allow developers of reviewed software an opportunity to clarify and/or comment on the review article. Following are comments from Rick Kossik, principal, GoldSim Technology Group. We thank Gian Frontini and Andrew Burns for their review. We would like to mention a few other key features of GoldSim that were not specifically addressed in the review that may be of interest. Although many of our users build models similar in size to the one discussed in this review (with perhaps several hundred objects), GoldSim can readily handle models with 10,000 elements or more. In addition to the ability to build hierarchical models using containers (which can be nested to any degree), GoldSim also provides a number of other features to facilitate the construction, maintenance, and presentation of very large models. These include: 1) the ability to localize subsystems in your model so that variable names can be repeated without causing conflicts, 2) the ability to make subsystems of your model (i.e., containers) conditional, so they can be dynamically turned on and off, 3) built-in configuration management (change tracking) tools, and 4) advanced navigation tools. GoldSim was designed from the outset as a probabilistic simulator. As such, it has a powerful Monte Carlo simulation engine. In addition to providing advanced sampling methods (e.g., importance sampling), it allows Monte Carlo simulations to be distributed over a network (utilizing a free, run-time version). GoldSim was designed to be extensible. In addition to allowing the user to link dynamically to spreadsheets, you can also link to other programs (compiled as Dynamic Link Libraries) and import and export from ODBC-compliant databases. Most importantly, GoldSim was specifically designed to facilitate the incorporation of additional modules (program extensions) to enable the program to address specialized problems. These modules either add new elements with specialized functionality, or new features which augment the way models can be run or viewed. This allows GoldSim to tackle problems that other general-purpose simulators simply cannot attempt. The Contaminant Transport Module allows complex mass and heat transport equations to be simulated. The Reliability Module facilitates simulation of the reliability and performance of complex engineering systems. The Spatially Distributed Module (currently under development) allows you to couple models to a spatial grid (with our goal to eventually link directly Geographic Information Systems). Other modules (e.g., Financial, Manufacturing, Optimization) are planned for future releases. As the authors correctly point out, we have a very active development schedule and actively respond to user feedback. For example, in response to user requests, we are currently implementing additional discrete event capabilities (e.g., entity attributes). We typically produce two major releases each year.

1. Frontini, Gian F. and Kennedy, Scott L., 2003, "Manufacturing in Real-Time: Managers, Engineers and an Age of Smart Machines," Boston: Butterworth-Heinemann.

Andrew Burns is a master's degree candidate at the Centre for Automotive Materials and Manufacturing, Queen's University. His thesis involves dynamic simulation, and he is an advanced user of the GoldSim software.

Table of Contents

OR/MS Today Home Page


OR/MS Today copyright © 2003 by the Institute for Operations Research and the Management Sciences. All rights reserved.


Lionheart Publishing, Inc.
506 Roswell Rd., Suite 220, Marietta, GA 30060 USA
Phone: 770-431-0867 | Fax: 770-432-6969
E-mail: lpi@lionhrtpub.com
URL: http://www.lionhrtpub.com


Web Site © Copyright 2003 by Lionheart Publishing, Inc. All rights reserved.