# OM and 'Vegas Night'

Introductory operations management courses traditionally cover basic concepts on operations strategy, process design and quality management. The instructor then progresses to the more advanced tools of inventory management, flow control and scheduling. One method by which I successfully make this transition in my classes is to use a variant of the "matchstick game" simulation described in "The Goal" [1].

Overview of the Simulation

The basic purpose of this simulation is to help students better understand the impact and interaction of statistical fluctuations and dependent events on the stylized process flow shown in Figure 1, which consists of several (typically five to six) separate, defect-free operations with queues (inventory buffers) between them. Event dependency enters from the requirement that the "units" must proceed through the operations in a sequential fashion. Statistical fluctuations are introduced through the use of dice rolls, which determine the number of units to be processed by a particular operation during a single time period.

Figure 1: Stylized process flow used in the simulation.

Although any type of marker can be used to represent the units, I have my students use poker chips since they allow for changes in the "material" lot by changing the color of the chips. Between the poker chips and the dice, my students often refer to the simulation as "Vegas Night."

Most users follow a "balanced line" approach in which each operation has the same average capacity per time period, with all teams operating under identical conditions [2]. Others modify this through the use of altered dice  each set of which averages a given number of units per roll but with different levels of variability [3]. The "Vegas Night" approach uses standard dice but varies the process design from team to team as shown in Figure 2 (modifying an exercise used in the Advanced Production and Quality Management Course at the Defense Systems Management College). The numbers (1 or 2) associated with each operation refer to the number of dice to be rolled to determine the capacity of that operation. Not all the lines are balanced, and, in one case, the number of operations is increased to represent a more complex process design. For the lines illustrated in Figure 2, I have found that teams of four to six students work well, with one student assigned as the accountant/scorekeeper.

Figure 2: "Design capacities" of the five manufacturing lines used in the simulation.

Conducting the Simulation

Discussion of the rules and initial analysis: Explaining the rules [2] takes only a few minutes and allows the students to do a little a priori analysis. Specifically, I ask them to estimate the number of units they would expect each line to complete over a 10-period run under steady-state conditions for use in our subsequent analysis.

Warming up the lines: To warm up the lines, some users begin with several units of work in process (WIP) in each queue [2]. "Vegas Night" starts with a "dry" line; however, the students run 10 warm-up periods to get the lines to their "steady-state" conditions. (This also ensures that students understand the rules.) After this warm-up, any "delivered" units are returned to the "raw material" pile, but all WIP is left in the queues.

The actual simulation: When students start the simulation "for real," each team receives a record sheet on which the accountant/scorekeeper tracks the available and utilized capacities and queues associated with each operation [4]. It is best to track at least 20 periods, with 10 periods as an absolute minimum. Alternately, one can track the number of periods required to complete a specified number of units [3].

A "wrench" in the works: About midway through the simulation, I change the color of the poker chips being processed by each line. Students are informed that the company has a new raw material supplier whose product has a latent defect that will only be detected upon delivery to the customer. The students are to continue processing the units on a first-in-first-out basis until the first unit(s) of defective material is (are) processed by the final operation. At that point, the line is to stop and record the number of defective units in WIP in order to estimate the line's "exposure" to the quality problem. If necessary, the students can finish the simulation using the "defective" WIP.

This exercise produces a range of reactions and ideas from students. Their comments can be used to initiate discussions of key principles of process design and flow control mechanisms. In general, such activities allow for a wealth of opportunities to introduce theoretical concepts in a manner that is engaging and effective. In the April issue I will describe the specific concepts I introduce through discussion of the "Vegas Night" results.

References

- Goldratt, E., and J. Cox, "The Goal  A Process of Ongoing Improvement," 2nd revised edition, Great Barrington, Massachusetts: North River Press, 1992.
- Ammar, S., and R. Wright, "Experiential Learning Activities in Operations Management," International Transactions in Operations Research, Vol. 6, No. 2, March 1999, pp. 183-197. Also, see http://webserver.lemoyne.edu/~wright/goldratt.htm
- Tommelein, I., D. Riley, and G. Howell, "Parade Game: Impact of Work Flow Variability on Succeeding Trade Performance," Proceedings of Sixth Annual Conference of the International Group for Lean Construction (IGLC-6), August 1998, pp. 14.
- A copy of this record sheet can be downloaded at http://domin.dom.edu/faculty/ajohnson/goldratt.htm

Editor's Note:

"Issues in Education" is a regular column sponsored by INFORM-ED, the INFORMS Forum on Education. The column provides educators with practical, useful and thoughtful ideas as they relate to issues in OR/MS education. Educators interested in contributing to the column should contact the column editor, Robert Nydick of Villanova University, at: robert.nydick@villanova.edu

Arvid C. Johnson (ajohnson@email.dom.edu) is an associate professor of management in the Graduate School of Business and Information Systems at Dominican University in River Forest, Ill.