Reducing Cycle Time, Part 5
Review of Reducing Cycle Time, Part 4
In Part 4 of this series, I discussed Little’s Law and its implications for cycle time and throughput when comparing batch production versus one-piece flow. One-piece flow refers to the concept of moving one work piece at a time between individual work stations, and it has several distinct benefits including keeping WIP to low levels and encouraging work balance and improved quality.
The impacts of changing WIP value on cycle times, holding costs, throughput and revenue
Much of what I am presenting in this series is taken from my second book, The Ultimate Improvement Cycle—Maximizing Profits through the Integration of Lean, Six Sigma and the Theory of Constraints. In Part 5, I will continue to examine Little’s Law and use it to help answer the question posed in Part 4, “What would happen if we increased WIP to two instead of one?” Once again, we begin measuring as soon as the first part enters work station A. We know that this first part will take one minute before it is passed to station B. At the same time, the second part is introduced to station A. These two parts follow each other through the four-station line, so both remain in the process for four minutes in total.
Batch Performance vs. WIP, C/T and T
Batch Size (WIP) |
Cycle Time (Minutes) |
Throughput (Parts/Minute) |
Throughput (Parts/Hour) |
---|---|---|---|
1 |
4 |
0.25 |
15 |
2 |
4 |
0.50 |
30 |
3 |
4 |
0.75 |
45 |
4 |
4 |
1.0 |
60 |
5 |
5 |
1.0 |
60 |
6 |
6 |
1.0 |
60 |
7 |
7 |
1.0 |
60 |
8 |
8 |
1.0 |
60 |
9 |
9 |
1.0 |
60 |
10 |
10 |
1.0 |
60 |
Therefore, this system produces two parts every four minutes, or 0.50 parts per minute (30 parts per hour). But what happens when we increase the WIP even more? The above table contains all WIP values from one to 10 and, as you can see, there is an interesting phenomena or nuance that takes place in this process when the level of WIP reaches five parts. If we make the assumption that the process is full (one at each station), and each part is ready to be processed, then when the fifth part is introduced to work station A, it must wait until the station has finished processing the fourth part and it moves to station B. Therefore, the fifth part remains in the system for five minutes. Each time a part is completed, the next part is introduced at station A and waits one minute before it can proceed. Look at the column for cycle time. As long as the system has no more than four parts in it, the cycle time remains constant at four minutes. But as soon as the fifth part becomes part of the system, the cycle time begins to increase by one minute for each increase of one part as WIP.
This phenomenon demonstrates that increasing WIP levels doesn’t result in a corresponding increase in cycle time until the process is full or until its critical WIP level has been reached. For this example, the critical WIP level is four parts. If WIP is increased beyond this critical WIP, parts simply stack up and wait to be processed, causing the cycle time to increase. Equally interesting, however, is that reducing WIP levels below the critical WIP (i.e. in this example one, two, or three parts) results in a corresponding decrease in throughput! As you can see in in the table above, when WIP is at its critical level of four (i.e. the system is full), the throughput is at its maximum value of one part per minute or 60 parts per hour. But when the WIP level is reduced to three, throughput drops from one part per minute (60 parts per hour) to 0.75 parts per minute (45 parts per hour).
What we’ve learned here is that too much WIP results in longer cycle times and increased holding costs, while too little WIP results in decreased throughput and lost revenue. This means that there is an optimum amount of WIP (i.e. critical WIP) that should be in a system. Even though there are many “experts” who believe in the concept of “zero inventory,” we now know that WIP should never realistically be zero!
What happens with cycle time, throughput, and WIP in an unbalanced line?
We have just discussed what happens in a balanced line, but what about an unbalanced line? What happens with cycle time, throughput, and WIP? Consider the four-step process in the figure above. In this process, we see that Step A has a processing time of one minute, Step B’s P/T is two minutes, Step C’s P/T is three minutes and Step D’s P/T is one minute. Clearly this is an unbalanced line because the processing times are not all the same. The assumptions we make here are that no variation exists and only one machine exists at each process step. Here, we see that the capacity of each process step is obtained by dividing the processing time in minutes/part into 60 minutes/hour. The capacity of the line is dictated by the bottleneck step, which in this process is Step C at 20 parts per hour. Applying Little's Law to this process results in a critical WIP level needed to maximize throughput while minimizing cycle time as follows:
Critical WIP = T x C/T
or
W_{0} = r_{ b} T_{o}
Where: W_{0} is the critical WIP, r_{b} is maximum throughput, and T_{0} is minimum cycle time W_{0} = 20 parts/hour x 7/60 hour = 20 parts/hr x 0.116667 hr = 2.3333 parts
This extension of Little’s Law tells us that if we want to achieve maximum throughput at minimum cycle time, then our critical WIP is 2.3333 parts, or three parts. Any number of parts above three will lengthen the cycle time and any number of parts below three will negatively impact throughput. Since we are interested in maximizing revenue and on-time delivery, Little’s Law will help us achieve this. The table below is a summary of what we have just discussed.
Step Number |
Number of Machines |
Processing Time (Minutes) |
Step Capacity (Parts per Hour) |
---|---|---|---|
A |
1 |
1 |
60 |
B |
1 |
2 |
30 |
C |
1 |
3 |
20 |
D |
1 |
1 |
60 |
When should we use one-piece flow?
As we have just seen, the most efficient form of manufacturing from a flow perspective is single-piece or one-piece flow. But there are times when one-piece flow is not appropriate or not even possible, so common sense must play a role in the decision to use it. For example, suppose the next step in a process is bead blasting or heat treatment of parts. Would it make sense to run the bead blaster or a heat treat oven with a single part or with a small batch? From a manufacturing efficiency perspective, a small batch probably makes more sense. We always want to minimize the non-value-added activities in a manufacturing process that includes travel time. If one-piece flow is not possible and transfer batches are needed, then one way to keep the transfer batch size small is through the use of cellular manufacturing. Cellular manufacturing positions all work stations needed to produce a family of parts in close physical proximity with one another. Because material handling is minimized, it is much easier to move parts between stations in small batches.
Coming in the next post
In my next post, I will begin a new discussion on continuous improvement. Until next time. Bob Sproull
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