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T.Hussain � Witness
This report is a concise discussion of the tabulated results on the previous page.
The parts table shows the number of each type of crisp assembled, shipped, scrapped and rejected. It also shows that the average time taken to process a plain packet of crisps is longest whilst the average time taken to process a packet of cheesy crisps is shortest.
The Labor table shows the times that the Joe and Fred are busy or idle. It is evident that Fred is either a harder worker or his workload is considerably greater than Joe’s. Joe’s busy time is only %0.4! It also shows that Fred carries out much more work and the time taken to carry out that work is also longer.
The Buffer table shows that as parts move from B1 to B4, the parts held are reducing, however, the parts held at B5 and B6 are greater than the Buffer before them, this is due to a Bottleneck, which is Machine OP0.
We can also see from the Machine table that OP0 is idle for too long, the time taken for inventory to reach it is a lengthy process, but then also OP0 has to wait for a certain number of each of packet of crisp before it can begin processing family packs, Fred and Joe can help reduce this idle time by helping offloading tasks from the Buffers.
The conveyor length could also be reduced so parts can be processed at a faster rate, therefore increasing Output, without increasing labour time.
OP0 needs to wait for a certain number of non-bottleneck parts (different flavoured crisps) to arrive before it can make a family pack and ship any orders. I found this was a bottleneck after running the model for longer than the time suggested in the assignment (180mins/ hours). The inventory kept building up but the OP0 machine did not have the resources to process this inventory, which led to excess inventory piling up before the bottleneck, resulting in a very poor flow inventory throughout the model. I also noticed how the number of family packs was increasing steadily as more time was allowed, in other words the time taken to process a family pack became shorter each time, but this was only for a short period. After 180 mins, the output was only 1, but after allowing another 180 mins, the Output was 4! Watching the model run for approximately 15 hours, it became evident that the management of resources was very poor, especially when relating resources, i.e. excess inventory before the bottleneck (OP0). This may have been avoided with better flow of inventory throughout the model but the most obvious answer seems to be to share the workload of the bottleneck with Fred and Joe. Although Fred was busier than Joe, he was only busy for %1. of the time, which is not very much at all. They could take some responsibility for doing the same job as the OP0 manually, and therefore reduce inventory, increase Output and also decrease operating expense.
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