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Little’s Law, named after John D. C. Little and his 1960 queuing proof, characterizes the dynamic relationship between work-in-process inventory (WIP), throughput rate, and lead time within a reasonably stable system. The “system” can be that of a process, cell, or line and can extend to one or more value streams. Little's Law, like all core lean principles, is universal and applies to all industries.
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If the system has fixed capacity, then lead time and WIP are proportional; meaning that if there is an increase or decrease in WIP, there is a commensurate effect on lead time, and vice versa. Throughput rate represents the average output of the system per unit of time and may be increased by improving bottleneck utilization or bottleneck rate. Lead time is the average time span for each unit to move completely though the system, including all process time and queue time, from its initial introduction to its final completion and release from the system. The “unit” here can be an assembly, an insurance claim, a patient, or some other component.
The math for Little’s Law follows:
WIP = Rt × Tl
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Comments
laws or lows?
Little's law, as any law, can only be but practical. Especially when approaching patients' waiting time: have you ever met a patient undergoing a NMR check shaking and crying for fear before the check itself? If not, ask Mr. Statistics.
WIP vs Little's Law
I have a global process where I calculated the WIP and found it much higher than what is defined by Little's Law. My understanding is that this is because of old inventory we are carrying through, thereby adding to the average WIP.
I want your inputs on the factors that influence WIP. I listed following
- Lead Time
- Throughput
- FIFO
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