MEDEFINITIONSEXERCISESOverviewBy analyzing simple sequential processes in detail, this exercise enables you to investigate how variability in processing times affects operational performance. The exercise begins with a two$-$workstation process. It then illustrates the effects of variability on production level, throughput time, and utilization. It then extends the analysis to a longer process to illustrate how the impact of variability on operational performance is moderated by a processs length. The exercise also illustrates how buffers affect operational performance.As you go through the tutorial, you will answer a series of questions. You will need to watch short videos in which simulated models are run to answer most of these questions. You will use the results from the Process Metrics for these models in your responses. Please note, there is no sound or interactivity with these videos.In all the videos, the models are already operating at a steady state when they begin. The models then run for a simulated period of $30$ minutes at a slower speed; this part of the videos takes about one minute. During this segment of the videos, watch the process closely to see how factors like variation in processing time affect Process Metrics like Average Throughput Time, Cycle Time, Average Throughput Rate Per Hour, and Utilization. Finally, the model speeds up and runs for a simulated period of eight hours; this part of the video takes about $10$ seconds.Once you have responded to all of the questions, you will then be able to export your responses to a PDF to submit to your instructor. Please note, you will not be able to export until all of the questions have been answered.The content in this tutorial was adapted from Roy Shapiros ExtendSim$$ Simulation Exercises in Process Analysis $($A$)$ and $($B$),$ HBS Nos. $694-039$ and $694-040($Boston: Harvard Business School Publishing, $2011).$ DEFINITIONSCycle time is the average time between successive units being completed by a task or resource. It is measured as a time period per unit. The reciprocal of cycle time is output rate.Takt time is the cycle time at which a process would need to be paced in order to meet customer demand. Takt time can be calculated by taking the time available to produce a certain product and dividing it by customer demand for that product.Processing time is the amount of time it takes a workstation to process a unit. It is measured as a time period.Throughput time is the amount of time each unit $($or customer, in a service$)$ spends in a process start to finish.Output is the number of units processed.Output rate is the number of units processed per time period $($in this exercise, usually $480$ minutes, or eight hours$).$ It is measured in number of units per time period. The reciprocal of output rate is cycle time.Buffers provide storage. Buffer capacity is the maximum number of units a buffer can accommodate at any given time. It is measured in number of units.Capacity is the theoretical maximum output rate of a process, measured in number of units per time period.Utilization of a workstation is the fraction of time that the workstation is actively used to create output or is blocked. That is$,$ utilization equals the amount of time the workstation is occupied divided by the total time it is available. It is measured as a percentage.A workstation is blocked when it cannot release a unit it has finished processing because the next process or buffer is full. A blocked workstation cannot begin processing another unit until it releases the unit it is currently holding.A workstation is starved when it is idle and waiting to receive a unit to work on$.$Uniform distribution refers to a probability distribution where each value within a minimum to maximum range is equally probable. PART ATwo$-$workstation line without variationConsider the following two$-$workstation process:WORKSTATION $1$Processing time $=1$ minuteWORKSTATION $2$Processing time $=1$ minuteIn this scenario, there is no uncertainty about the processing time of the two workstations. That is$,$ each workstation takes exactly one minute to perform its tasks before sending the unit on$.$ Click start to play the video below, and then use the Process Metrics data to answer questions $1,2,$ and $3.$Please note, there is no sound with these videos$\mathrm{.}1.$ What is the cycle time for this line?$500/500$ characters remaining$2.$ What is the lines output during a $480-$minute $(8-$hour$)$ period?$500/500$ characters remaining$3.$ What is the utilization of each workstation during the $480-$minute period?$500/500$ characters remaining PART BTwo$-$workstation line with variationWORKSTATION $1$Processing time $=$ U$(0\mathrm{.}5,1\mathrm{.}5)$WORKSTATION $2$Processing time $=$ U$(0\mathrm{.}5,1\mathrm{.}5)$Now suppose the processing time for each workstation averages one minute, but varies along a uniform distribution ranging from $0\mathrm{.}5$ to $1\mathrm{.}5$ minutes $($represented by U$(0\mathrm{.}5,1\mathrm{.}5))\mathrm{.}4.$ Qualitatively, how do you expect your answers to the three previous questions to change for this process?$500/500$ characters remainingClick the start button to play the video and watch closely to illustrate how the process changes for this uniform distribution. Then answer question$5.$ Why do the operating performance measures have the effect noted in Question $4?500/500$ characters remaining PART CThe magnitude of variationNow that you have some insight into how variability in processing time affects operational performance, lets see what happens when there is more or less variability. The following line has more variability, with the processing time for each workstation ranging from zero to two minutes on a uniform distribution $($thus$,$ average processing time for each workstation remains one minute$).$ Click start to play the video and observe how the increase in variation affects operational performance.The following line has less variability, with processing time ranging from $0\mathrm{.}75$ to $1\mathrm{.}25$ minutes on a uniform distribution $($thus average processing time for each workstation remains one minute$).$ Click start to play the video and observe how the decrease in variation affects operational performance$\mathrm{.}6.$ Compared to the results in Part B$,$ how do increases or decreases in variation affect the lines output and each workstations utilization? Why?$500/500$ characters remaining PART DFour$-$workstation line with variationNow that you have seen how variability affects a two$-$workstation line, lets see what happens in a more realistic line that has more processing steps. Consider a line that has four workstations with processing times ranging from $0\mathrm{.}5$ to $1\mathrm{.}5$ minutes on a uniform distribution $($thus averaging one minute$).$ Consider how you expect the line output and workstation utilization to differ relative to a two$-$workstation line with these workstations $($the line in Part B$)$ and why. After thinking about these questions, click start to play the video and observe how variability affects the line output and workstations utilization of this four$-$workstation line$\mathrm{.}7.$ Compare the results for the two$-$workstation line from Part B to this four$-$workstation line. From the videos, note how they differ in terms of blocking and starving, as well as the resulting line output. Hypothesize how the number of workstations might moderate $($a$)$ the relationship between variability and workstations utilization, and $($b$)$ the relationship between variability and line output$\mathrm{.}500/500$ characters remaining PART EBuffersTo illustrate how buffers affect the operational performance of a process with variability, we return to the scenario from Part D: a four$-$workstation process where the processing time of each workstation varies along a uniform distribution from $0\mathrm{.}5$ to $1\mathrm{.}5$ minutes. In this instance, however, a buffer that can hold one unit of work$-$in$-$process inventory is placed between the four workstations. From your work in Part B$,$ review the workstation utilization and line output for the $480-$minute period. How do you anticipate the buffer will affect the utilization of each workstation and the line output? After thinking about these questions, click start to play the video and observe the line output and workstations utilization$\mathrm{.}8.$ Based on these results, how do line output, throughput time, and workstations utilization differ from those for the process in Part B $($which is otherwise the same$)$ when we add a one$-$unit buffer? Why?