• enable "learners/players" to quickly navigate through a complex manufacturing
• enterprise, from molecular-level descriptions of manufacturing processes, to global-level,
• market-driven decision making,
• allow variables to be controlled by the players, or by an "omniscient" moderator,
• enable players to understand the ramifications of their actions, at a variety of levels,
• enable communication between players,
• promote team-building and teamwork,
• partition data access, defined at the time of log-in, with access zones depending on the
• role of the "player",
• allow multiple players to log-on, synchronized with respect to the factory simulation
• engines, from geographically distributed computer sites,
  be modular in architecture, such that models at any level can be easily replaced by other
• models and/or other simulation packages,
• be able to run simulations at selected timescales, and selected frequencies of interaction,
• record and display actions and results of player "moves",
• utilize multimedia.

• a teaching tool for academic settings,
• assessing the skill and understanding levels of new employees interviewing for a job at a company,
• training company employees on the skills of their job and the relationship of their job to those of others in the business, and
• a strategic planning tool for management officers within a company.

• starts the main MES,
• connects the data flowing into and out of the various factory models (representing
• competing companies, each with domestic and perhaps, foreign operations), to other
• model regions and players,
• controls the data commanded and demanded by the various players,
• partitions the data flow according to the access rules established for a given simulation
  ("game"),
• handles net-level communications (instructions) between players,
• synchronizes the various disparate simulation sub models.
  

• starting local MES functions and simulations, as a player logs onto a simulation,
• partitioning data locally,
• downloading a particular player's set-up file from the main server.

• Moderator: A moderator, although not a "competing" player, can passively watch the activity of all participants, or the moderator can set and/or change global variables. For example, the moderator, in the absence of a "consumer" model, can set the initial size of world markets (actual industrial sales), and generate forecasts for future industry sales. Individual company sales are then determined as a fraction of total industry sales, based on a computed market share for that company.
• Government Official: A government (represented by either a single player or a team of officials) can be operative for each country in which manufacturing enterprises or other factors of production (such as raw materials) reside. The government officials set tax rates, tariff rates, regulatory policies, and money supplies, to name a few. These variables in turn influence such factors as growth rate, inflation rates, and federal interest rates.
• CEO: The Chief Executive Officer (CEO) must make estimated sales forecasts for their company, and decide how much of the forecast demand for a given period (e.g., one month, or quarterly) should be met by domestic production and by foreign production sources. These decisions are influenced by the cost of production at home and foreign sites, quality of production at different sites, transportation costs, reliability of suppliers, and exchange rates. The CEO then conveys these production needs to their factory managers, who in turn must manipulate equipment and labor quantities within their factories to meet the estimated production (sales) demands. The CEO is also responsible for determining marketing outlays, and necessary product quality.
• Factory Manager: A Factory Manager (FM) may receive operating instructions of production goals from the Company's Chief Executive Officer (CEO). The CEO may shift the emphasis toward higher production rate and/or lower cost depending upon current and foreseen market conditions. It is the job of the FM, upon getting production needs from the CEO, to determine how these needs will be met: regular or overtime production, subcontracting, addition of capital equipment, etc. The FM is thus in charge of factory layout and operation. In addition, global economic conditions may change in the course of the simulation and directly affect the FM's decision framework. The prices of raw materials, or the cost of labor, or the mandatory surcharge for overtime pay, may change. The factory manager, in anticipation of future product demand, can accumulate inventory, but at an incurred holding cost.
• In a simulation using the Battery Factory (see details below), a player can assume the role of Factory Manager (FM), who makes decisions that affect both the production rate and the cost efficiency of the Factory. Specifically, the FM decides when to order raw materials and what inventory levels to maintain. The FM also determines the number of workers assigned to various phases of the manufacturing process, as well as the operating hours per day, the number of rest periods, when defect rates need to be counteracted, etc. The FM can also control the training period for new workers, trading off increased labor costs for improved worker efficiency. One goal of the FM can be to optimize production in terms of greatest weekly output and lowest average cost per item, given the Company's current business objectives.
• Quality Manager: The primary function of the Quality Manager (QM) is to implement the quality level specified by the CEO. A given quality specification incurs certain enforcement costs (for inspection, scrap, rework, returns and replacement). Typically, higher quality requirements incur higher per-unit costs. But these costs can be mitigated by more spending on product and process improvement (PPI).
• Other Roles: The MES is designed to accommodate other player roles, as needed for any given simulation. For example, teams of engineers and technicians within a factory, responsible for the maintenance, operation and quality control of a suite of equipment, can be defined. Or, advocacy groups, interested in environmental issues, can be defined as an influence on the public market sector (through advertising), the corporate sector (through green design), and/or the government sector (through lobbying). Or, since the MES is intended to also be used in a corporate setting for training/upgrading/tasking manufacturing personnel, players could take on the role of trainer (media maker and distributor), or recruiter.

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• Factory Model: A "Battery Factory" (BF) simulation has been developed as a case study of an actual prototype manufacturing process for a re-chargeable fuel cell that runs on methanol. This factory was chosen because it has elements typical of modern electronics manufacturing processes (including vacuum-based, thin-film depositions), and it allows the use of real data (such as actual raw materials). A key element of the fuel cell is an electrode configured on a plastic membrane. The fabrication of the electrode is done by lamination of several layers of conducting metals on the plastic membrane by means of a "sputtering" process. The sputtering takes place in a vacuum chamber where an ion beam vaporizes a piece of solid metal, and deposits a thin-film of the metal on the plastic surface. A stencil is used to pattern the metal film.
  
  The BF thus covers a broad spectrum of the manufacturing enterprise, from physical-process levels, to assembly-line levels, to single-facility management, to company management, to global and international issues such as outsourcing.
• Finance Model: The factory models intrinsically flow data into the corporate financial models, from which the CEO makes decisions. Some of the computed financial variables include gross profits, total sales, cost of sales, labor costs, manufacturing costs, depreciation costs, interest expenses, and bank balances. These variables can further be used to compute performance indices, including operating profit margins, fixed-asset turnover ratios, and inventory turnover ratios. R&D Management Model: A research and development (R&D) project lifecycle model has been integrated into the MES (the R&D model, and its ExtendTM implementation, have been developed by eight members of the LANL Technical Staff). The R&D model includes a ranking algorithm which computes a relative measure of project value, as a function of both merit and cost. With those predictors, R&D management (which might include the CEO) can then decide on a strategy for corporate R&D investments, given a limited budget.

The GUI for the MES enables a player to easily capture and cluster the graphs which they feel are most crucial for measuring the success of their role, or their team, depending on their incentives and motivations.

The authors thank,

• Robert Hockaday, President, Energy Related Devices, Los Alamos, New Mexico, for factory and physics models,
• Anne De Piante Henriksen and Ann Melinda Jensen, for "The R&D Project Lifecycle
• Model and Portfolio Analysis Tool", Draft Paper, Los Alamos National Laboratory, LA-UR-95-4333 (Nov. 95),
• Rebecca Phillips, Willard Wadt, Philip Goldstone and Allen Hartford, members of the Los Alamos National Laboratory Technical Staff, for contributions to the "R&D Management model",
• David Vick and David Rogers, of dynaVu Inc., for development of the dynaVu GUI application,
• Sarang Gupta, staff, for UNIX versions of simulator programming,
• Tom Claus, temp staff, for tkl/tk programming,
• Lisa Ice, UNM CS graduate student, for NT support programming,
• Dan Talso, UNM ME/MEP graduate student, for occasional support programming,
• Vasu Kengeri, CS graduate student, for support programming,
• Chi-Leung Chu, Management student, for programming analysis,
• numerous company representatives for discussions on computer based training needs and issues, and applications of the MES therein.