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论老子

道,领导也。领导必需要不断呼唤,教导下属以及以身作则。下属的过和错皆因领导懒惰。

 
 
 

日志

 
 

Chapter 22: Inaccurate cycle time  

2012-06-24 11:50:07|  分类: Buffer Mentality |  标签: |举报 |字号 订阅

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Around mid-March 2008, Siew Jie suggested to me, we should start to collect the operational baseline data. Among them, one of the most important data is the process cycle time. The production capacity is usually determined by the process cycle time. If the cycle time is one hour per unit, the capacity is 8 units per an 8-hour shift or 24 units per day.

I asked him, “How do you collect the cycle time? Show me how you collect it?”

Siew Jie was a little puzzled. In his mind, certainly he thought I know what cycle time is and how to collect this piece of data and how to use it to establish the production capacity.

But in my mind, the accuracy of the cycle time is dependent on how it was collected. Cycle times can be collected in numerous ways and I have seen many of them were collected in the wrong way. These cycle times were much longer than the ideal cycle time. Slack time that elongates the ideal cycle time was not effectively removed from the data or the way the data was collected had already incorporated this amount of slack time that made it impossible to segregate later in the cycle time analysis.

Therefore, the production capacity determined by using this slack cycle time is far too low compared to the actual production capacity of the process. The determination of the production capacity based on a slack cycle time amounts to allocating provision of extra time as buffer. This is buffer mentality.

Two hours later Siew Jie came back to me with the following Excel spreadsheet. I reviewed it. On the left, he wrote down the name of the processes that he wants the cycle time to be collected. He indicated clearly he wants the start-time and end-time for each of these processes. The time interval between the end-time of the upstream process minus the start-time of the downstream process is the waiting time a unit sits as WIP before it is picked up and processed by the downstream process. This is a smart way to collect cycle time that nets off the waiting time.

In my mind, this is good enough to use these cycle times to analyze which is the bottle-neck of the series of processes. Usually, the bottle-neck is the determining factor for the production capacity of a production cell. A production cell essentially consists several pieces of equipment placed together either in a U-shape or a straight line.

Though back in my mind, the cycle time collected in this way is not what I wanted. It still contains a considerable high percentage of buffer or slack time in it. Let’s not debate over this right now and I shall discuss about it in detail during the later half of this chapter. 

I said, “Okay, you go ahead to work with the facilitators to collect the data.”


Figure 22-1: Cycle time data collection sheet

Chapter 22: Inaccurate cycle time - 浪里行舟 - 论老子
 

A week later, Siew Jie showed me an analysis of the cycle time. At the far right column, the waiting time in-between two processes is clearly computed as the difference between the end-time of the preceding process and the start-time of the downstream process.

Whereas, the net difference between the end-time and start-time of the same process is the cycle time.

The production lead time is equal to the sum of the cycle time of all the processes plus the sum of all the waiting time in-between two processes. In this example, the waiting at 13.42 hours divided by the total production lead time at 46 hours equals to 29%.     

 

Figure 22-2: Analysis of cycle time 

Chapter 22: Inaccurate cycle time - 浪里行舟 - 论老子
 

I asked, “What is the production capacity of this cell?”

Siew Jie thought hard. It is obvious the burn-in time at 26.5 hours could be the most likely bottle-neck. But he asked Asep who was with him to collect the data, “How many slots are there in the burn-in chamber?”

Asep replied, “There are 20 slots in the burn-in chamber. The average cycle time for the burn-in process is 1.325 hours (26.5 hours divided by 20 slots).”

Siew Jie made a quick mental calculation and replied, “The bottle-neck process is the assembly process. Its cycle time at 2.75 hours is the longest. The next longest cycle time is the final test process at 2.08 hours. The rest of the processes are much shorter. The production capacity is therefore, 2.75 hours per unit.”   

I did not dispute his mental calculations. I probed further and asked, “Are you sure the production capacity is 2.75 per unit?”

Siew Jie paused for a few minutes and replied, “Yes, the capacity is 2.75 hours per unit. That is about 3 units of output per 8-hour shift. (8 hour-shift divided by 2.75 hours per unit equals to 2.9 units.)

I asked, “Asep, how many operators are there in this production cell?”

Asep replied, “There are 2 final assembly operators and one test operator.”

I threw open this question, “With two final assembly operators, what should the cycle time for the final assembly process be?”

Siew Jie realized that with two final assembly operators, the cycle time is halved. Quickly he answered, “It is 1.375 hours per unit. I should have checked the number of final assembly operators assigned to this production cell.

The cycle time is inversely proportional to the number of final assembly operators. It is similar in concept to the number of parallel slots in the burn-in chamber.”

“Are you sure the cycle time for this cell is 1.375 hours per unit?” I prodded him to think harder.

“No. No. No. Give me a few minutes to think it over,” said Siew Jie.

I threw the same question to Asep, “Asep, what do you think the bottle-neck should be? It is the cycle time of the bottle-neck that determines the production capacity. Which is the bottle-neck?”

“2.08 hours per unit. The bottle-neck is now at the final test process. Am I right?” replied Asep.

“Yes, Asep, it should be 2.08 hours per unit. The cycle time of the final assembly process at 1.375 hours per unit is no longer the bottle-neck,” said Siew Jie.

“Good, both of you have understood very well that adding parallel stations or manpower can quickly reduce the cycle time of a bottle-neck process. But is this all that you must watch out for to determine the capacity of a production cell?

Note. I am not interested in the capacity of each individual process. I am only interested in the capacity of the bottle-neck process. What is the true bottle-neck for this production cell?”

“Final test,” said Asep.

“Correct. It is the final test,” Siew Jie reinforced Asep’s finding.

“No. Think carefully. Which is the bottle-neck?” I said.

Five minutes passed. Both Asep and Siew Jie stared at me blankly.

I knew they do not know the answer. I explained, “The capacity of a production system is dependent on two factors. They are: equipment and manpower.

If it is an oil refinery, the manpower usually is not taken into the equation to compute the production capacity since te operation of this plant is fully automatic.

If it is a hand-rolled cigar factory, the equipment is usually not taken into the equation to compute the production capacity because the output of cigars is directly dependent on the speed of the workers and not on the equipment.

Now, what do you think the capacity of this cell is?”

Siew Jie and Asep looked into each other eyes. Siew Jie exclaimed, “This is something that I was not taught in the lean expert workshop. All I had learnt was to determine the cycle time of the bottle-neck process and use it as the limiting production capacity.”

“Now, do you realize it is not as easy as that to determine the limiting capacity? In certain situation, one of the equipment is the limiting capacity. In some other situations, manpower is the limiting capacity. So, let’s do a quick computation, what is the capacity of this production cell,” I asked both of them.

Asep and Siew Jie discussed among themselves for several minutes. Siew Jie said, “If we were to ignore the burn-in process, the capacity should be 3.33 hours per unit. This is the sum of cycle times for the CT test, final test, audit and box-up. (This is the sum of 0.75 + 2.08 + 0.17 + 0.33 hours).”

“Asep, do you agree with Siew Jie,” I asked.

“I agreed with him,” said Asep, “What can it be if you do not agree?”

“Do you want to know my answer now?” I asked.

“Of course, we want to learn of your answer,” said Asep.

“Frankly speaking, I do not know the answer,” I said.

Asep was quite stunned. He said, “Come on, you certainly know the answer? You are a lean production grand master. You are my sinseh[1]. I have always looked up upon you to coach me all about lean production system.”

I explained, “Asep, I may have to disappoint you. I am about to coach you on something that perhaps, you will never learn from any lean expert workshop. This is all about basic industrial engineering. I told you a good practitioner of lean production system must have a very strong foundation in industrial engineering.

Let’s take the example of the final test process. The cycle time is 2.08 hours per unit. First and foremost, I would like to know the answer to this question. Does the test operator need to be seated in front of the final test equipment for the entire cycle of 2.08 hours?”

Asep recalled for a minute and replied, “No. He does not have to be glued to the final test station. He does walk about and let the final test equipment runs by itself to complete a specific test cycle. When a test cycle is completed, he quickly comes back to the final test station, makes a record of the test values produced by this test and he subsequently calls up another function and let it continue to run by itself to complete the test cycle. This process is repeated several times over the 2.08 hours.”

“That means he actually spends a fraction of the 2.08 hours that took a unit to complete its full final test cycle. How much time did he actually spend attending to the final test equipment? This is what I called, touch time. Do you know that?” I asked Asep.

“No. This is something not that I know of. In the first place, I did not know of such a concept called, touch time. Well, I can think of how to collect the touch time” replied Asep.

“Let’s leave this topic on how to determine the touch time. There is a better way to take care of touch time. May I ask you one important piece of information? What is the capacity number that the production planner is using to determine the loading of the production schedule? Perhaps, Jeffry, the planner has the answer,” I asked Asep.

Asep replied, “Give me 2 minutes. I have the data in my personal computer.” He headed straight to his desk which is just outside my office.

Three minutes later, Asep came back and said, “The capacity is measured in units per 8-hour shift. It is 4 units per shift. That is 2 hours per unit.”

I explained, “If we were to use the final assembly process as the bottle-neck cycle time, the capacity should be 1.375 hours per unit. If we were to use the cycle of the final test process as the bottle-neck, the capacity should be 2.08 hours per unit.

Let’s assume the total touch time for these 4 processes; CT test, final test, audit and box-up as less than 1.375 hours per unit, the final assembly process would remain as the bottle-neck process. Let’s us assume the capacity as 1.375 hours per unit. Compare this number to the 2 hour per units used by Jeffry, the production planner in the production scheduling process. That is about 0.625 hours of buffer per unit. That amounts to 45% buffer (0.625 hour divided by 1.375 hours).

This is buffer mentality. I cannot put the blame on the operations manager or the production planner to have built-in 45% buffer into the production line. They simply do not have a good grasp of where the bottle-neck is and what is the cycle time of this bottle-neck process.”

Siew Jie exclaimed, “Eric, you are very sharp and a very experienced, hands-on lean master. After hearing your explanations, I realized there is so much more to learn about how to determine the cycle time of a production cell versus an individual process, the complex interaction of man-to-machine in determining the cycle time of human interaction or touch time, how to select which is the bottle-neck process and lastly computing the production capacity.”

“Well, whatever you have learnt today, you will not appreciate it unless you pick up a project and start to work on determining the capacity of a production cell. I give you a hint.

At the end of your data collection and analysis, you think you would have ascertained the final capacity of the production cell. But I can tell you now you will not get the right answer for two reasons.

One, unless you set up the production cell to operate on a one-piece-flow system, you will never be able to get a fairly accurate estimate of the human touch time.

Two, the determination of the capacity of the production cell is not static. When you change the number of operators deployed in the production cell, the capacity will change. You may have to re-do the whole exercise to determine the new capacity that is based on a new set of operator-to -machine ratio.”

“Wow! Eric, it is really difficult to determine the production capacity of a production cell then. The production cell that we used in this discussion has only 5 processes. Some of the other production cells have up to 14 processes. I can imagine the complexity and difficulty in determining the production capacity of each cell.”

I summed up our discussion for the day, “This Bintan factory has 19 production cells. Do you know how much buffer there is built-in into these 19 production cells? I can only make a wild guess.

If you were to follow through with what I have taught you just now, you can easily triple the factory capacity without adding a single piece of equipment. Three times increased in the factory’s productivity is a very conservative number.

But the question is how to bring the true capacity of all the production cells up to very close to their theoretical capacity. It is more than just understanding this concept. It must be coupled with the implementation of the one-piece-flow system.

Lastly, I should share with you how to determine plural capacities for the same production cell by deploying varying number of operators. Indeed! It is very complex. Only the experts with a strong grasp of industrial engineering who understand slack cycle time equals to buffer mentality can do that data collection and analysis correctly.” 

 


 



[1] In the Japanese language, sinseh means the great teacher.

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