Question 1: How many units would you expect to be able to produce over 100 time periods? Click the "Run" tab and, using the default values for "Run-In Time," "Run Length," and "Repetitions," run the simulation. Tabulate the average utilization at each machine based on the five repetitions, and tabulate the mean and standard deviation of the out- put of the system (these data are in the "Machine" worksheet).

This exercise, which uses LineSim.xls, is an oppor- tunity to study the impact that variability in processing time has on the capacity of a simple serial production system. Much more com- plex systems could be studied, but our hope is that by studying this simple system, you will gain insight that can be applied to more complex systems. The system we are studying is similar to the two-stage assembly line discussed in this technical note; here we look at a three-stage assembly line. In practice, assembly lines have many more work- stations, but completing an exercise with more workstations would take considerably longer. If you do not believe that your results can be generalized to a larger system, feel free to expand your study. For this study we use the Serial Line Simulator (LineSim.xls) that is included on this book's DVD-ROM, This Microsoft Excel spreadsheet simulates a simple serial production line. We are indebted to John McClain at the Johnson Graduate School of Management, Cornell University, for allowing us to use his innova tive spreadsheet. GOAL OF THIS EXERCISE Our goal in this exercise is that you leam firsthand how variability can impact the performance of multistage production systems. A common approach used to reduce the impact of variability is through some type of buffering mechanism. To be more specific, in our system variability exists in the amount of time that it takes to perform work at a workstation. In analyzing the system we use the average time to complete each unit, so sometimes it takes longer and sometimes less time. It probably seldom takes exactly the aver- age time.