Review of Reducing Cycle Time, Part 1
In Reducing Cycle Time Part 1, I introduced you to four important concepts: cycle time, processing time, throughput, and work-in-process inventory (WIP). I presented a simple four-step process, with processing times for each work station. Then I calculated how long it would take to complete all 10 pieces (batch size) through the process. I finished the last post by mentioning that I would explain what would happen if the factory were to change its batch size from 10 parts to four, as in the figure below.
Changing the batch size
In today’s post, we will answer the question, “What would happen if the factory decided to change its batch size from 10 parts to 4?” Much of what I will present in this series of posts is taken from my second book, The Ultimate Improvement Cycle—Maximizing Profits through the Integration of Lean, Six Sigma and the Theory of Constraints.
If the factory were to decide to change its batch size from 10 to 4, what would be the impact on cycle time and throughput? Each part would still require 1 minute of processing time at work station A, so all four parts would take four minutes in total to pass through station A. Likewise, 4 minutes would be required to process the batch of four parts through stations B, C and D, respectively. Again, ignoring transport time, it would require a total of 16 minutes of cycle time to process the batch of 4 parts through this process. The throughput would be 4 parts every 16 minutes, or 0.25 parts per minute, or 15 parts per hour. So the throughput would not change, but the cycle time would be significantly less.
This same exercise can be repeated for any batch size as seen in the table below and the results will remain the same. No matter what the batch size (WIP), the throughput always remains the same.
Let’s look at how batch size impacts cycle time. Because the parts are transferred from station to station in batches, rather than one piece at a time, the cycle time for the batches grows as a function of batch size. This style of production and production control is characteristic of the mass production mindset. It is often referred to as “batch and queue” or “batch and push” production. This represents the worst possible way to process material through a factory! In this type of production, the level of WIP (batch size) has a pronounced effect on cycle time, but absolutely no effect on throughput! For all of your production managers who insist that it is faster and more efficient to process material in large batches, I hope this simple exercise demonstrates otherwise:
Batch Performance vs. WIP, C/T and T
In 1961, John Little, an institute professor at the Massachusetts Institute of Technology, published a mathematical proof known as Little’s Law, which states that throughput (T) is always equal to WIP divided by cycle time (C/T), or stated mathematically as follows:
Throughput = WIP/Cycle Time
T = WIP/C/T
Coming in the next post
In the next post, I will explore Little’s Law in greater depth.
Until next time.
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