2012-06-24 12:25:05| 分类： Buffer Mentality | 标签： |举报 |字号大中小 订阅

John recently completed his four months lean expert workshop. He was here in Bintan to complete his course assignment. He noticed I did not mention anything about takt time.

During the four month period, he had seen how the takt time was used to drive down the planning for all the resources required including the design of the production system. To him the takt time is the most important fundamental piece of information. Without which, the computation for the need of resources is not possible.

John asked, “Eric, you have not talked about the takt time. As you know, it is the single most important piece of data in setting up a lean production system.”

I threw a question back to John, “How do you define takt time?”

John explained, “The total time available divided by the demand. For example, 16 hours a day assuming a 2-shift operations divided by 960 units demand for the day, the take time is 1 minute per unit. At a production rate of 1 minute per unit, it takes 16 hours to complete all 960 units of demand for the day. It is as simple as that.”

I asked, “Is it as simple as that?”

“Yes,” replied John.

I said, “Well, in all mathematical computations, there is an underlying assumption which most lecturers or teachers often forget to mention. In your lean expert or master workshop, the basic assumption is, the takt time does not change.

If the takt time changes, don’t you think all the computations that you have made will have to be re-calculated. And the entire production system will be totally changed. Do you agree with me?”

“I fully agree with you on this point,” said John.

I explained, “The takt time is the quotient of two numbers. That is, a numerator divided by a denominator.

The numerator is the total available time. Assume the total available time can dance around a large variation ranging from 46% to 85% of the total available calendar time[1].

Why must you stick to a fix number of available time? As far as I know most production operations can dance nimbly around these two numbers, ranging from 46% to 85% of total available calendar time. This variation[2] is large by any standard.”

“True,” John said, “I did not question what is in the numerator.”

“The denominator is even more interesting,” I explained, “What is demand? Is the demand number coming from a single product or a combination of demands from a long list of products?

Toyota Motors Corporation or as a matter of fact, all car manufacturers make almost similar product or car model on the same production facility. Therefore, it can be considered the demand is coming from essentially the same family of products.

Back in Honeywell, the demand does not come from a single group of products. Take for example the ground proximity device production line, there are 6 product families and within each family there are several different models.

What I am interested in is the total amount of time required to produce one units of each model.

Let’s look at the assembly cycle time alone. The shortest assembly cycle time is 0.48 hours per unit of product. The longest cycle time is 1.32 hours per unit of product that requires a heater blanket.”

“Why are you looking at the total amount of time required to produce a unit of product?” asked John.

“In the numerator, the unit of measure is hours. It is the hours available for you to use to produce the products. Therefore, the denominator must be hours too. It cannot be other thing else. Otherwise, it is not apple-to-apple,” I explained.

“But the takt time is not defined in this way. It is defined as hours per unit. This is going to throw away all that I had studied in my last four months,” lamented John.

I continued, “In the Toyota plant, a car is a car. Despite its different final configuration, essentially it takes about the same amount of time to assembly one car. For this reason, nobody pay attention to the use of takt time as hours per unit.

But if you were to critically go back to basics, the numerator is time available. It must be compared to the total demand which must be expressed in total amount of time required. When these two unit of measures is in a common unit, namely; time, for example hours, we can meaningfully make a decision whether there is sufficient available time in the numerator to complete the production of the demand of all the products as shown in the denominator.”

“I couldn’t agree to you more than this,” said John.

“Let’s look at the standard time of the assembly process for each of the ground proximity devices. To produce a unit of MK5 requires 0.57 hours. To produce a MK5 but comes with a heater blanket requires 1.23 hours. Assume there is only one assembly operator assigned to this production line, she can produce 14 units of MK 5 in an 8-hour shift. She can only produce 6 units of MK 5 that comes with a heater blanket.

What is the takt time for this ground proximity device line? Should it be 0.57 hours per unit or 1.23 hours per unit?” I asked.

“If on a particular day, it produces only MK 5, the takt time is 0.57 hours per unit. On another day, if it produces only MK5 with heater blanket, the takt time is reduced to 1.23 hours per unit. This is easy,” replied John.

I added, “What if the demand for the day is a mixture of Mk 5 and Mk5 with heater blanket? The takt time is anything between these two numbers; that is, ranging from 0.57 to 1.23 hours per unit.

To make things worse, there are 4 different total cycle times required to produce all the 23 different types of ground proximity device. See Figure 10-1 below.

**Figure 10-1: Different cycle time for products of the same family**

The product mixes changes everyday. Which takt time do you want to use? Forget about the other resources, the mere number of assembly operators to be assigned for the day could not be ascertained with relative ease with the use of a single takt time number.

A takt time that was used could ask for the deployment of a single assembly operator. But if the day’s demand happened to produce solely products that come with heater blanket, definitely there is a need for more than 1 assembly operator.

To make things more complicated, all the ground proximity devices must go through a 48-hour burn-in process. Inside each burn-in chamber, there are special sockets where the units can be plugged in to run the burn-in test.

For two of the models, there is only one socket. For another fur models, there are four sockets. The remaining of the models has a total of 20 sockets.”

“Indeed it is true. The real live situation is more complicated than a pure assembly process. Our products go through an assembly process, pre-test, burn-in test, post-burn-in test and final test and etc. It is much more complicated than making a car,” said John.

I continued, “Let’s go back to the very first process of production planning. Assume the production planner is very diligent. Today, she plans for tomorrow’s production schedule. She receives a variety of orders with delivery due-date 4 days from now. She has two priorities in her mind.

First, she must load in all the orders due to be delivered 4 days from now. Second, she has to maximize the day’s output in order not to waste any of the available production capacity.

Under the situation of varying demands for different products that has such a high variation in the total cycle time, the use of takt time to determine the total number of units to be loaded for tomorrow’s production schedule is erroneously wrong. There are two possibilities.

One, the total amount of time required may far exceed the total time available. There will be missed production. The on-time delivery performance will be less than 100%.

Two, the total amount of time required may be less than the total time available. The on-time delivery performance will be 100%. But the assembly operators will stop work much earlier than shift ends. This is wasted resources.”

John nodded his head, “I fully agreed with you.”

“If you go back to the chapter 1, ‘Misused of average’,” I explained, “You will realize that the use of an average takt time is going to be a big problem. Either you missed the on-time delivery or you are going to waste precious resources.

Do you understand why I did not mention anything about takt time for the past 4 days? This is because when someone uses of the statistical average to estimate something, he forgot behind the theory of statistical average that the variation could be very large.

It is a bell curve.

One, if it is a sharp bell curve the final error as a result of the actual data deviating from the average could be small because the spread of the sample data used to determined the statistical average is not too far away from the statistical mean.

Two, if it is a flat bottom bell curve, the final error could be very large. In this example, the standard time of the ground proximity devices is very wide. It ranges from 0.48 hours per unit to 1.32 hours per units.

I cannot push aside the kind of error that ultimate results in less than 100% on-time delivery performance or lost of precious resources. Most operations or production managers always tell me, ‘Since you already know the statistical error as a result of using the statistical average, it is an obvious trade-off situation. Either you get 100% on-time deliver performance or optimum productivity. You cannot have both. Of course, most of us will sacrifice productivity and opt for 100% on-time delivery.’

But deep in my heart, I know all CEO wants both. Achieve 100% on-time performance everyday and yet, the productivity is optimum. How to achieve these two seemingly contradicting objectives?

The answer is simple. Just ignore the use of statistical average.

First, use the actual standard time of each product or model in the computation of the time required to produce the said model.

Second, key in the actual quantity of each of the product models that you plan to produce for the day or shift.

Third, let the macros functions of the Excel spreadsheet automatically compute the amount of time required to produce the planned units.

Fourth, let the macros function automatically sums up all the time required to produce all the products you have planned for the day or shift.

Fifth, if the planned production efficiency is equal to 100%, your day’s production plan is done. If the planned production efficiency is less than 100%, add more quantity to be produced for the day. If it is more than 100%, decide whether you will call for the production manager to plan for over time among the employees. Or you may want to smoothen out by delaying the production of certain quantity to the next day’s schedule.

With the help of a well-designed spreadsheet with the minimally required macros functions, production planning is a breeze. There is no need for the use of a statistical average among the standard time of the few product groups or models. In other words, it serves no real purpose to use the takt time (computed as the average of several products to be built) in the production planning process.”

**Figure 10-2: Key in the quantity you want to produce for the day**

**Figure 10-3: The macros automatically compute the time required**

In Figure 10-3, the bottom row gives you immediately feedback whether you have achieved a production planning efficiency that is equal to 100% or not.

**Figure 10-4: The aim is to achieve a close to 100% planned efficiency.**

John reviewed the Excel spreadsheet thoroughly. He saw that there is really no magic to this way of carrying out the production planning function. He said, “Eric, I fully agree with you there is no need to use a statistical average of the standard time. Or for that matter the need to use a takt time as well. But what I don’t really see is this Excel spreadsheet is so simple. It is a no-brainer to develop this spreadsheet with all the macros thrown in.”

I said, “John, if a production planner were to produce a planning spreadsheet as simple as this, I can sleep with a peaceful mind. The problem is most production planners do not use such a simple spreadsheet. Somehow or somewhat, there are a lot more things built into the planning spreadsheet, with several average numbers thrown in.

Someone asked Shoichiro Toyoda, the CEO of Toyota Corporation what is the magic behind the Toyota Production System. Mr. Toyoda replied, ‘The philosophy behind the Toyota Production System is, ‘Simple’.’

Now what do you think I am doing over here?

‘Simple’. I just want to keep things simple. This spreadsheet is in its most simple format if you bother to make a survey among the production planners of all the companies in the world.”

“Okay, I agreed with you totally, Eric,” said John, “But in real life, thing does change over time. How do you re-compute and review the resources required to meet the new demand or reduction in demand?

Isn’t it very tedious to re-compute all these calculations?”

“You have to re-do all the computations. You have to review your resources. You may have to move some resources out from this production cell or add in additional resources. The question of who to be removed or at which process or work station to add in more resources, it is going to be a challenge again.

But do you really have a choice? You just have to repeat the entire exercise.

Precisely, you are expected to redo the entire exercise, it is all the more important to keep your spreadsheet simple. Do not over analyzed things. Do not use too many average values. Each time you use a statistical average, you are assuming something. You may not be aware of how the average values pile in the errors or variations to your work.

In production planning or scheduling, you cannot afford to have variations. This is because variations in the production planning process automatically mean there will be a much bigger variation in the final delivery performance of the production department.”

“Eric, I fully agree with you,” said John.

I summarized with this ending note, “John, I have shared with you most of the key important areas where the takt time if misused could cause a lot of inefficiency or wastages of resources in the manufacturing process.”

“Yes, I have to be extra careful when the takt time used is a computed average number,” said John.

[1] Please refer to chapter 1, ‘Capacity utilization’ of the book, “The untold secrets of lean sigma” by the same author. You will understand the total available hours indeed vary over a large range.

[2] Did you ever ask why all the assembly plants owned by Toyota Motors Corporation operate on a fixed number of available hours per day and for almost 365 days a year? For that matter, almost all car companies too, operate on a fixed number of hours per day.

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