Principle (Process Variability): For a fixed throughput level, inventory and flow time at a station are increasing in the process variability at the station.
The intuition behind this principle is that the more variability there is in the process times at a station, the longer work will have to wait in queue (given a fixed throughput level). Hence, by Little's law , inventory will also be larger.
Process variability is measured in terms of the coefficient of variability of the effective process times. Effective process time is the time from when a job reaches the head of the queue until it is ready to depart the station. So, it includes not only the raw process time, but also any detractors (machine down time, setup time, operator induced outages, etc.) As a result, the coefficient of variation of effective process time is made up of natural variability (i.e., the variability of the raw processing time at the station, which is usually quite low) and a variety of inflation factors (e.g.,. setups, downtimes, outages, operator unavailability, material unavailability, batching and so on). Even when the natural variability of the station is low, the inflation factors can make effective processing time variability be very high. Since it is variability in effective process times that determines operational behavior, attacking the variability caused by the various inflation factors can be an important strategy for system improvement.
The following figure illustrates the qualitative effect of increasing
the coefficient of variation of effective process times on the resulting
flow time and WIP.
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