Case Study on STONEHAVEN INC. QUESTIONS:
Part A: For this part of the analysis, consider each department in the Gdnask factory "in isolation" - that is, when doing the calculations, imagine for the moment that the rest of the production system has no impact on the department you are considering. For the purposes of these calculations, material handling times may be assumed to be negligible, and you can ignore variability in processing times. Please be sure to state your assumptions.
1. For the typical 100-pair batch, what is the daily capacity and flow time within each of the following departments?
a. Cutting
b. Stitching
c. Lasting
2. If the batch size were reduced to 10 pairs, what would be the daily capacity and flow time within each of the following departments?
a. Cutting
b. Stitching
c. Lasting
Part B: Now consider the factory as a system, and take into account interactions between the departments. Please be sure to state your assumptions.
3. Assuming production is done in 100-pair batches, what is the factory's daily capacity?
4. What is the total flow time for a 100-pair batch? Part C: 5. How would you go about deciding on the appropriate batch size for the Stonehaven factory? What factors would you consider? How do they interrelate? 6. Focus only on your highest priorities for improving the production process at the Stonehaven's Gdansk factory (be specific). Explain why they are important. What actions do you recommend?
Cutting Department Computation
It is assumed that the batch consists of 100 pairs. There are evidently 3 operations that are taking place in parallel and four die changes are required for each of the operations.
Time for cutting shoe leather = 4*(5.25 + 100*0.05) = 41 minutes
Time for cut linings = 4*(5 + 100*0.05) = 40 minutes
Time for cut insole = 4*(4.00 + 100*0.04) = 32 minutes
The constraint on the capacity from the above processes would be in the form of cutting shoe leather which consumes the highest amount of time.
Hence, capacity = 480/41 = 11.7 batches
As one batch contains 100 pairs, hence capacity = 11.7*100 = 1170 shoe pairs per shift
Further, the cycle time would stand at 41 minutes since the processes are taking place in parallel.
Switching Department Computation
It is assumed that the batch consists of 10 pairs. The relevant data is summarised below.
Step 1: Prefit in which process, there are four workers and the total task time is 50 minutes
Hence operation cycle time (Step 1) = 500/4 = 125 minutes
Step 2: Joining in which process, there are three workers and the total task time is 30 minutes
Hence operation cycle time (Step 2) = 300/3 = 100 minutes
Step 3: Ornament in which process, there are two workers and the total task time is 25 minutes
Hence, operation cycle time (Step 3) = 250/2 = 125 minutes
It is apparent from the above that the cycle time is 125 minutes.
Hence, capacity = 480/125 = 3.84 batches or 3.84*100 = 384 shoes in every shift
Further, manufacturing lead time = Work in process * Cycle Time (As per Little’s Law)
For work in process, it is apparent that there are nine workers which produce in 2 batches (taking into consideration the buffer), which implies that total batches are 18.
Hence, manufacturing lead time = 18*125 = 2250 minutes
Lasting Department Computation
It is assumed that the batch consists of 100 pairs. The various processes involved and the taken in these is indicated below.
• Staple Sole (0.7 minutes)
• Seat Lasts (0.6 minutes)
• Rough Sole (1.0 minutes)
• Cement Sole (0.9 minutes)
• Inspect and Pack (0.3 minutes)
It is apparent that the constraint from the above processes is Rough Sole since it consumes the maximum amount of time from the given processes.
Thus, the conveyer belt needs to have a speed of 1 minute for every operation.
Hence, the first pair of shoes comes out after 5 minutes as for each operation 1 minute is allocated. Further, after every one minute a new pair would keep off coming.
Manufacturing Lead time of batch (100 pairs) = 100+4 = 104 minutes
Assuming that only one batch can be processed at once, capacity = 480/104 = 4.62 batches or 462 shoes per shift