THE IN-CLASS MANUFACTURING GAME

 

Salwa Ammar & Ronald Wright

Department of Business Administration

Le Moyne College

Syracuse, NY 13214

 

wright@mail.lemoyne.edu ammar@mail.lemoyne.edu

 

This game was designed to integrate levels of production planning and show the relationship between them. The planning topics covered by the game are aggregate planning, inventory theory, lot sizing, productions scheduling and materials requirement planning. The theory of each topic has been covered individually. The In-Class Manufacturing Game provides students with the opportunity to engage in production planning at all these levels, to see how decisions at one level interact with those at other levels, and to experience the challenges involved in making a production operation run efficiently.

The latest version of the game is a computer simulation created using Visual Basic in Excel. A free version of the software and copies of the game packet are available to college faculty by contacting Salwa Ammar or Ron Wright.

At the start of the game students are provided a complete game packet containing all necessary information and logs for recording relevant information during the playing of the game.

The game involves the production and selling of a product line with three models over a twelve to twenty-four period horizon. Each model requires two parts (blue, pink, green or yellow index cards) and labor (white index cards) in three different combinations. The game is played in two stages, a planning stage followed by the production of the products. Planning requires an aggregate plan, a master production schedule and a material requirements plan. Implementation includes production, attempts to meet a random sales demand, and the calculation of costs and revenues for each period. The game is won by the team that generates the highest profit. Teams are comprised of between four and six players.

The planning is a key phase of the game. Teams must first prepare an aggregate production plan for an "average" model (rather than for the actual three) . The aggregate planning horizon covers four quarters. The base number of labor hours is determined by each team but must be kept constant throughout the game. Deviations from the base are handled by overtime. Participants are told the production costs for the average product (labor and parts), inventory costs , and a forecast demand. The creation of the aggregate plan requires the selection of a production planning strategy involving trade-offs among work force size, overtime costs, and holding costs. Teams will consider some combination of a chase strategy, matching production to product demand, a stable work force but making use of overtime, or a level production strategy. Many competitors will use linear programming to determine a minimum cost production strategy.

The planning up to this point has been on a quarterly basis. Each quarter is now broken down into 6 (bi-weekly) periods. The next, and most difficult, plan is the master production schedule which indicates how many of each of the three models will be built each period. Students first recognize that they must balance setup costs as you change from producing each model with the holding costs for held inventory. Most students will employ some EOQ formula at this step. In addition since random sales demands will be announced at the end of each period, the production must be planned so that an adequate inventory of each part is maintained at all times. The best plans will identify some level of safety stock to cover the uncertainty in the sales. Lost sales are very expensive and next to excessive overtime is the biggest contributor to poor overall results. The difference between long term planning based on averages and short term detailed planning becomes very clear at this point.

Once the master production schedule is complete, the remaining planning activity is the preparation of the material requirement plan. Parts must be ordered for each product so that they are available when needed. Lead times are from 1 to 2 periods. In this case, inventory and order costs must be balanced. Some students will again use EOQ formulas even though the demand for parts is not uniform. Others will try part period balancing. For the better students, who avoided overtime and prevented lost sales, correctly dealing with inventory versus set-up and ordering costs will provide that last edge which determines a winner.

The entire planning stage can take from an hour and a half to nearly three hours. In our MBA course we allow teams an entire three hour class to work out the details of their plans and to discuss how they intend to implement them in the next phase of the game.

The production stage of the game can be played by actually ordering parts, acquiring labor, physically producing the item and making sales while keeping track of finances, writing checks for expenses, and tracking inventories. This physical activity provides students with the opportunity to collectively experience many of the difficulties of trying to maintain an operation successfully over an extended period of time. The interactions with other people, patient or frustrated, reinforce the concepts that are being taught in the classroom. Actually placing orders, producing product, counting inventory, and calculating costs bring to life abstract concepts. However, in our MBA course we use a computerized version of the game. It allows us to handle more teams at once and to put more emphasis on modifying plans in response to changing demands. The game begins with each team defining their starting inventory (parts and products) and base labor levels. Then at the beginning of each period teams place orders for parts (to be filled after lead times) and indicate production levels all of which are entered into the computerized game.

Demands are then announced, and teams are informed of their sales and ending inventories for that period. In addition the cumulative net profits are posted for all to see and the next period begins. If teams schedule production where they do not have adequate parts or labor, production is allowed but the missing resources are supplied with very large expediting penalties.

In addition to tracking their inventories to see if actual levels are close to planned levels, teams are encouraged to track sales to see if they are occurring as expected. Here they use forecasting techniques learned earlier in the course. The randomly generated demands in each period do follow the forecast (on average) for the aggregate product. However, for the actual models we often generate demands above and/or below the forecast. Alert teams will pick this up and modify their production schedule and consequently their material requirements plans.

Excitement builds as the game nears the end. Some teams will be out of the running but most will be close enough to be hopeful up until the last period. Minimizing overtime, maintaining sufficient inventory to cover sales, and avoiding expediting penalties makes a team competitive. Winners are often determined by the effective control of inventory costs.

Since all activities for each team were recorded during the game, a final analysis is immediately available. It shows a complete breakdown of all costs and revenue and allows teams to see where they did poorly or well. In fact we usually review these results at the end of the first quarter to allow teams to make adjustments (where possible).

 

 

 

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