High Wip To Make Production Control Easier ?

Early in the morning the ramp up manager tell me the project that I hand over giving him a lot of problems. The machine stoppage and yield loss is high. He as me why and ask me to walk into the production floor to have an investigation for him.

I quickly pull the process engineer and walk into the line. We inspect the machine hardware and software set up, no abnormality observed. So, we load in a fresh lot to let the machine run so that we can monitor the performance. The machine runs without giving any error message. I waiting at the machine for 2hr, I didn’t observe any problem. Therefore I go back to the office and tell the ramp up manager – No Problem.

He look at me with a big eye and say,
“of course you don’t see problem because you load in a fresh lot right from the N2 chamber. Try to run the lot that already exposed to the production environment for more than 1day. See you still can get the machine run without giving problem or not”

I ask him, why we have lot that exposed in the production environment for more than 1 day? Why can’t he control the peoples working in the production floor only draw a lot from N2 chamber when they really need?

He reply, it is a production Standard Operating Procedure to keep one “Standby Lot” beside the machine to ensure continue supply of raw material.

I don't agree his point because with a process cycle time of 50 second and lot size of 1400 units. Machine time required to complete one lot take 19.44 hour provided the machine running non stop. This mean, the standby lot at the machine will be exposed to the production environment for nearly 24 hour before being process. No wonder the machine giving lot of problem when processing such material.

Do we really need a Standby lot in this case? We knew that material surface will be contaminated when exposed to the ambient. That is the reason why we keep it in the N2 chamber. Another question, since we knew the material need to keep it in the N2 chamber and N2 chamber is very expensive to maintain, why we produce so much from the upstream process and keep? Why can’t we produce just enough to cover the need of the downstream process?

Answer given to me was: it makes the production control easier.

I want to faint when I get the answer like this.

Mc Donald's Production System III

一直以来我都很留意Mc Donald's的Production System。我觉得，Mc Donald's 是世上唯一能够把Lean Production System呈现于大众眼前的公司。而且，一直以来都管理得很好，也不断的改进。

新年期间有机会在光顾住家附近的Mc Donald's，发现道Mc Donald's又耍新花样了。赶快拿起相机把这新改良的Mc Donald's Production System 拍下。

以下是新的Mc Donald's Production System，和旧的system相比，看得出有设么分别吗？
是的，新的system比旧的system来得Lean，而且已达到了one piece flow的境界了。



我时常和同事说，要学Lean Production System 或是Toyota Production System，不需要跑到Toyota工厂那里去，去Mc Donald's 看就得了。Mc Donald's 的柜台服务员或许不能够告诉你什么是Just In Time，什么是One Piece Flow，什么是build to order还有很多关于Lean 的学问，可是他们每天的工作，都和TPS脱离不了关系，也不会歪离TPS的原则。为什么？

Last update : 01/03/2009

Mc Donald Production System II

Toyota production system classifies WIP or Over Stock as one of the major waste in the production system. But in Mc Donald, people seem like having different point of view.

Photo shows the WIP accumulated on the soft drink dispensing machine. I observe this while waiting for my turn to place order in one of the Mc Donald restaurant in Melaka Raya.

This is definitely not a good idea to me. In fact, this is not the 1st time I observe the similar case in Mc Donald, just can’t understand why the management allow such practice repeat again and again.

Simple question; why you produce if you don’t need it?

Last update : 02/01/08

Mc Donald's Production System

I got a chance to snap the photo in a Mc Donald's restaurant while waiting for my turn to place order.

The incident happen when a customer service attendant found the burger tray is empty and the kitchen is not able to role out enough burger to meet customers demand. The crews seem like lack of experience to handle such messy situation. They loss control, leave the angry customers aside and having side discussion in front the burger tray. There are customer really unhappy to be serve in such situation. Some inpatient customer just walk away from the restaurant.

Mc Donald's is one of the successful company in lean production system, yet they end up in such situation.

Why ?

Actually, I don't really like the communication system that Mc Donald's is using. Where the customer service attendant asking for stock replenishment through shouting to the kitchen. Is this effective ? I doubt, how many order the guys in the kitchen can remember ? The system make the restaurant looks busy but not really effective.

In the Mc Donald's Production System, there is a Kanban tray in the system, but without the Kanban or Ticket to trigger the demand pull. Whereas, the demand pull is trigger by shouting.

May be, it is the company's culture, the management want it this way. Some noise in the restaurant can make the environment looks young and energetic.

Anyway, there are room for further improve the operation system.

Last update : 28/11/2007

Six Sigma Is Not A Management Approach

During a lunch with a group of managers, someone bring up the topic of feasibility of Six Sigma approach in management. Suddenly the operation manager look at me and throw me a simple question.

Do you think the Six Sigma management approach works in our daily operation? He ask me.

Hub....I m really frighten by the unexpected question thrown to me. I don't have the answer in my mind actually. I look at him with my big eyes and a smiling face. I only respond to him after idling for few second.

I tell him I don't think there is such management approach call Six Sigma management.

The group of managers seem confused after getting my respond.

OK, lets make ourself clear the true meaning of the term “Management”. In wikipedia management was explain as an activity comprises planning, organizing, leading and controlling a team for the purpose of coordinating and harmonizing them towards accomplishing a common goal. It is an art. Whereas, Six Sigma DMAIC is a systematic problem solving approach that comprise of scientific and mathematical analysis.

Six Sigma DMAIC systematic problem solving approach could be a strategy in managing an organization, but by itself it could not be a management approach.

Last update : 16/02/08

Common Term In Lean Production System

Common term use in Lean Production System.
That I learn from Wikipedia.
Just for info sharing

Andon (行灯) (English: Signboard)

Genchi Genbutsu (現地現物) (English: Go and see for yourself)

Hansei (反省) (English: Self-reflection)

Heijunka (平準化) (English: Production Smoothing)

Jidoka (自働化) (English: Autonomation - automation with human intelligence)

Just In Time (ジャストインタイム) (JIT)

Kaizen (改善) (English: Continuous Improvement)

Kanban (看板, also かんばん) (English: Sign, Index Card)

Manufacturing supermarket where all components are available to be withdrawn by a process

Muda (無駄, also ムダ) (English: Waste)

Mura (斑 or ムラ) (English: Unevenness)

Muri (無理) (English: Overburden)

Nemawashi (根回し) (English: Laying the groundwork, literally: Going around the roots)

Poka-yoke (ポカヨケ) (English: fail-safing - to avoid (yokeru) inadvertent errors (poka))

Six Sigma 之来由

要了解Six Sigma这个名词的来由，就必须由Sigma（）这个字谈起。相信很多人都知道，在数学里，Sigma其实就是我们常说的Standard Deviation。

以当今的科技，无论你使用多么精准的机械，始终无法连续制造出一摸一样的成品。无可否认，很多成品外表看起来都很相似，但是，如果经过详细的测量，我们会发现到所有的产品都有一些小小的偏差。这些偏差或许可以小得令我们很不在呼，可是，很多时候这些小小的偏差对整个成品生产过程带来诸多的问题。

在现实的世界里，偏差是无法避免的。在成品生产过程当中，我们需要原料，机械及人力。原料与原料之间的差异，机械与机械之间的差异以及人与人之间的差异，造成了一个不完善的制成品。偏差永远存在，无可避免，唯一能做的，就是想尽办法减少差异。

Six Sigma的意思是在某个成品的Standard Deviation 相等于( UCL – mean ) 或是 ( mean – LSL ) 的六分之一，我们能够以为该成品制造过程的能力已达到Six Sigma的标准。也能够合理的推测，在百万个制成品当中，最多只有3.4个不合规格的成品。所以，想要达致Six Sigma的标准，并不是一项简单的工程了。

Sigma (the lower-case Greek letter σ) is the symbol represents standard deviation of a statistical population. It is not new to peoples who have some basic statistic study.

Based on today’s technology, we are still not possible to reproduce exactly alike regardless how high precision the equipment we use to produce the part. No doubt, in many products, there are looks alike from the outside, but if you go through a detail measurement, you will notice there are deviation, the deviation could be very minor to the extend that peoples used to ignore, but most of the time, it is the root cause of many problems that we face in our daily life.

In the real world, deviation is unavoidable. Deviation exists due variation between material batches, machine to machine and peoples. The deviation cause an imperfect product. Since we can avoid deviation, what we can do, is to think way to minimize it.

A Six Sigma process mean when a process standard deviation is 1/6 of the range between process mean and upper control limit or lower control limit. Statistically, there are 3.4 chance for Six Sigma process to produce a defect out of one million part produced. It looks simple, but in fact it is not so simple to achieve Six Sigma level.

Hidden Factory

Hidden factory are non value added activities hided or embedded in any process operation. Because it is invisible to us, therefore we are not aware of it most of the time.

Toyota production system ( Lean ) classify the non value added processes as waste in the production system. Waste in the production system affecting process efficiency, resulting of higher operation cost.

Founder of Toyota production system Taiichi Ohno & Shigeo Shingo identified 7 critical wastes that need to remove from the main stream process flow. There are;

1. Overproduction
2. Waiting
3. Transportation
4. Inappropriate processing
5. Excess inventory
6. Unnecessary motion
7. Defect

Out of the 7, I would like to add one more: Inspection

Wastes listed above is not unique to Toyota, it exist in our work place as well. We did not aware the existence most of the time, because it is invisible or it is being accepted as part of the main stream process operation.

When a company accepts hidden factory build up in their main stream process operation, a portion of the company resource will be take up to support the invisible operation that do not generate income for the company.
Hidden factory will growth over time. The cost to maintain the hidden factory will roll like a snow ball if management did not clean up their main stream process regularly. The bigger the size of the invisible factory, the more money will be taken up by the invisible monster.

Last update : 31/05/07

Can Lean Implementation To Service / Finance Industry ?

This is to reply a comment left on my earlier post.

“Do have any idea of lean implementation to service/finance industry?”

Answer to you : Yes

Don’t forget, the original concept of Lean Production System is to eliminate wasted / or non value added activities that build in the business processes.

Business processes refer to a chain of activities taken to materialize a product from the point of customer order to delivery or even after sale service.

Products can be a finish product or service that customer pay for and expected.

I have seen Lean and Six Sigma heavily apply in banking industries to improve loan and credit card application.

I don’t see any problem to further enhance the concept in service sector like banking and insurance.

Last Update 16/04/08

Ppk Estimation For Non Normal Distributed Data

Non normal data is the data that do not fit into the shape of normal distribution. In fact, we are facing this type of data most of the time in the actual process.

As an engineer or manager, we should understand our process well and know what kind of distribution a particular process should behave.

Process capability calculation for non normal data isn’t straight forward as what we did for normal distributed data.

In fact, I am not so sure how to estimate the Cpk value this type of distribution manually. I still rely on Minitab when dealing with this kind of data.

I tried to search through Minitab Help and here the formula I get.

The formula looks simple, but I still can’t get a correct answer by substituting the figure I have into the equation. How come? Anyway, I need not to worry so much as Minitab can do all the statistical analysis for me.

Here the problem I have, can anybody tell me how Minitab work out the PPL = 0.4?

Last update : 18/02/07

The 1.5 Sigma Shift

This is a topic that many Six Sigma practitioners put in lot of effort in their Six Sigma research.

Actually, there is no evident to prove most manufacturing process shift within 1.5 Sigma over a long term process.

Experience from Motorola shows that Sigma level of a long term process may be shift within the 1.5 sigma range due to uncontrollable external factors. Don’t forget, Motorola is a big organization that involves many complicated manufacturing processes. At which process the engineers encounter the shift and can 1.5 sigma level shift applicable to all processes under Motorola organization? This is still a big question mark.

I would say, 1.5 is just an artificial number for benchmarking. It is not necessary applicable to all, therefore, why bother so much about the magic number?

Last update : 27/03/08

Cpk vs Ppk - Part 5

Here the sample data collected from the SPC activities, subgroup size = 15. Tape_1 refer to 0.53” tape and Tape_ 2 for 0.46” tape.

From the raw data, without doing any statistical analysis, believe you can tell the adhesiveness of Tape_1 is stronger than Tape_2. Common sense lah… Tape_1 is wider than Tape_2.

Now, look at the chart below, without doing any complicated calculation, you can tell that Tape_1 will have higher Cpk value than Tape_2. Common sense lah… Mean value of Tape_1 is higher than Tape_2.


Ok, now the capability analysis of Tape_1 and Tape_2.




From the data spread, both data set having more or less equal standard deviation, Cpk / Ppk Tape_1 = 2.50/2.47 and Cpk/Ppk Tape_2 = 1.48/1.51. Oh no… Cpk and Ppk Tape_2 is not meeting the industrial standard. How can we conclude that the process of putting smaller tape on the PCA is not capable therefore we should put in more effort to increase the Cpk and Ppk value at least to the industrial standard ?

There are two possible way to increase the Cpk / Ppk value if you want it. You can either increase the adhesive strength or reduce the standard deviation of the smaller tape. Anyway, Tape_1 and Tape_2 having similar material property. Practically it is not possible to make the smaller tape stronger than the larger tape. Now, the only solution to increase the Cpk / Ppk is to reduce standard deviation. The chart above shows that standard deviation of Tape_1 and Tape_2 are more or less equal, it gives me an impression there is no abnormally or special cause happen. Yes, you can try to minimize the process variation, but I m not sure how much we can achieve and how much impact to the Cpk or Ppk value.

Ok, after the long story, is time for conclusion. Cpk and Ppk is a measure for process capability, 1.67 is an industrial standard benchmark. I don’t have any objection on this. When we decided to choose the index as a guide line to measure the process capability, we have to understand the background and nature characteristic of the process. Of cause, we hope everything can be 1.67, but unfortunately not everything can be done. However, it is not the end of the world if 1.67 cannot be done. As a manager, we must have the knowledge to weigh the situation and set practical target.

My personal opinion, Cpk/Ppk 1.48/1.51 is good enough for Tape_2 because I know the natural characteristic of the process. I don’t worry too much about the process shift because overall distribution is far away from the LSL. What I suggest is to continue monitor the process stability through SPC.

Last update : 19/06/08

Cpk vs Ppk - Part 4

Case 2

Peel test is part of a process control I used to monitor in the SPC data. This is an important data I need to monitor because I may face high field return from customer if the process is not in control.

The story happen in one of my large scale printer PCA project. The printer was design in such a way the PCA panel will stick on the enclosure of the printer with a 6” long strong double sided tape. Two type of tape width were use for different application.

We apply the double sided tape manually on the PCA after final test. It is a critical process because the PCA will fall down from the enclosure if the operators did not apply the right pressure when putting the tape on the PCA. In order to control the process stability, SPC is the easiest way. The original intention I add in peel test in SPC is to monitor the process stability, unfortunately fall into a Cpk trap and end up a never ending story.

Picture below shows double sided tape dimension to be place on the PCA, for safety reason, both tape have to withstand a minimum 2kg pull force.


From the tape dimension itself, we can sense that peel strength is proportional to the tape width. Smaller tape width will give lower peel strength, larger tape width will give larger peel strength, it is a common sense.

One evening a new engineer call me up and tell me he want to stop the line for smaller tape because SPC data shows the Cpk is not meeting the requirement, i.e. 1.67. I don't know where he get the number and ask him why 1.67. He reply, oh... it is a industrial standard. The process is not meeting the industrial standard, therefore he have to shut down the line.

A day later, I receive a mail from his manager regarding the same issue, he ask why process is not capable for smaller tape whereas no problem for larger tape. He demands a further improvement on the process to bring up the Cpk value for smaller tape size, at least to the level of industrial standard.

Do you ever face the same problem ?

I will show you why we end up two different Cpk in the same process and material property.

Last update : 16/06/08

Cpk vs Ppk - Part 3

Actually, there is nothing so special about Cpk and Ppk. Both numbers are figure out from the same formula as below



This is how Minitab figure out the magic number.
The only different is Sigma (within) and Sigma (overall)

How to get the Sigma (within) and Sigma (overall) then?

Honestly I am not really sure how Minitab estimate the Sigma value, I tried to figure out the Sigma value on Microsoft Excel with reference to Minitab help, I only manage to get which is very close to what Minitab reported, but so far I never get and exactly answer. Here is the answer of Sigma (within) & Sigma (overall) from my manual calculation.

Correct me if I m wrong.

Last update : 06/09/08

Cpk vs Ppk - Part 2

In fact I m not so interested in Cpk or Ppk value because I feel the number can be very misleading if we don’t really understand how the data behave. Understand data behavior is more important because we may end up drawing a wrong conclusion if solely make decision based on Cpk or Ppk value as what my managers is doing.

Usually, when I receive a set of 10Lot data, I will straight dump the data into Minitab and lot the I-MR chart as shown below;





I like to analyze my data this way because it provides me a quick understanding of data behavior either within or between the lots. From the data, I can see that the overall process is stable and in control in general. Any abnormality also can easily identify.

After assessing the I-MR chart, only I check for the process capability. I will check on the Cpk and Ppk value and the distribution of the data, again, Cpk and Ppk is not the only criteria use for measuring the capability of a process.

Look at the chart below, Cpk and Ppk value is so low, can say that the process is not capable for mass production ? Yes, the process is not capable for mass production, if I make my conclusion solely based on the number. But if look at the I-MR chart and the overall data distribution, it shows that the process is stable enough for production release. What I m more particular is mean of the data distribution must be on target.



The low Cpk or Ppk in this case mainly because by the process variation, and don’t forget we are now considering the overall process variation. Of course we expect a bigger variation compare to the variation within individual sub group. This is because there are many variations have to factors in when we are in the actual production mode, such as machine to machine, people to people and batch to batch variation.

Since I mentioned the main contributor to the low Cpk and Ppk value is the process variation, what happen if the process shift, then the process will out of control!

Ok, in fact I m not so worry about the process variation in 10 Lot monitoring, this is because the data were collected from several machine, several set up and several shift over quite along period. The spread of the data shows above is good enough to represent the future production condition. In other word, variation of the long term process should not be different too much from the 10 lots data, provided the machine condition, and set up is well controlled.

Last update : 06/06/08

Cpk vs Ppk - Part 1

I have a new product launch to production few month a go. For any new product ramp up, there are a series of data collection to monitor the process stability and capability. The whole purpose of the monitoring is to ensure consistency of machines and peoples variations. I used to call the exercise as 10 Lots monitoring.

Here the example of a data set collected from the 10 Lot monitoring. And I will report the process performance to the management in this form.

If you are familiar with Cpk and Ppk stuff, you will not agree with me.

Actually, I also dislike the format because we only measure Cpk value of each lot and conclude the process performance based on the Cpk value estimated. No choice, it is the yard stick I asked to follow.

The Cpk value of each monitoring lot cannot be use to present the overall process performance because the standard deviation use for Cpk calculation is the standard deviation within the sub group. Variations between machine, peoples, material batch and others were not taking into consideration in Cpk calculation.

Therefore, Ppk is a better yard stick to measure the overall process performance for new product ramp up.

Last update : 02/06/08

Six Sigma 简介

Six Sigma 是一套完善的作业流程改善工具。启至于一九八六年，由Bill Smith在Motorola公司开发。当初Bill Smith开发这套工具，主要是为了要减少Motorola产品在装配过程中所出现的偏差，以提高Motorola产品的质量。但是，经过二十多年的进化，这套原本只用来改进生产流程的工具，已经变成了一个通用的作业流程改进工具，适用于各领域的改进工作。

在Six Sigma之前，Total Quality Management ( TQM )，Zero-Defect之类的品保提升策略早已非常普篇。这些改进策略都是根据于数为品管大师（Shewhart，Deming, Juran，Ishikawa和Taguchi ）的创新理论演变而成。
和其他的管理则学一样，Six Sigma所提倡的是

- 不间断的改进以让作业流程达致一个能以预测的稳定程度。在商业的角度来看，稳定的作业流程是一个成功企业的关键。

- 技术上，所有的作业流程效率都能够以数字来衡量，分析，改进和监控。

- 为有企业团队的承诺与支持是确保高素质作业能以长期保留之关键。

通告

想了很久，终于决定暂时性关闭这个部落各以便进行一次大清洗。

成立这个部落各三年多了，除了累计了不少有关Six Sigma的经验以外，老实说也累计了不少的垃圾文件。
因此，我做了这个决定。

希望在星期天开始，就可以看到更新版的Six Sigma知讯