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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 25: Downtime Losses  

2012-06-24 11:41:14|  分类: Buffer Mentality |  标签: |举报 |字号 订阅

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On May 21, 2008, John and I were having lunch at the BIE villa. After we have placed our orders for several dishes, we were left with some quiet time while waiting for our lunch to be served.

Capitalizing on the time available on hand, John said, “In operations management, the number one focus is to get the job done and delivered on-time. When the production folks missed a delivery date, the most frequently used excuse is shortage of workers. This is the standard answer a production supervisor, the production superintendent, the production manager and all the way right up to the senior management will use to explain the missed in delivery schedule. I can guess behind their minds, there is a simply objective. That is, to hire more workers.”

I added, “Everybody seems to buy in to this explanation without giving it much thought and it often leads to the hiring of more workers. As I have explained in chapter 12, ‘Speed losses’, work expands with time. Hiring more workers will result in lowering the workers’ productivity. Lower productivity leads to lower year-end performance bonus (or total annual remuneration) which in turn, leads to low worker morale. As a result of low morale, workers turnover rate shoots up.

But then why is it that every production supervisors and managers still made this common mistake? It is buffer mentality.

“Well, that is the easy way out. Hiring more workers than is required certainly adds buffer to beef-up the production capacity. On the other hand, if the management does not increase the hiring of more workers, quite naturally, the shortfall in production for the day shall be make up by overtime,” explained John.

“May I have the liberty to explain to you what is downtime when it is applied to the workers? I want to make this point clear to you.

Downtime for a piece of equipment is well understood by almost everybody and somehow it is regularly being monitored and analyzed.

But downtime due to workers is not often measured. By the way, do you know how to measure it?” I said.

John replied, “Okay. This is an interesting topic. I have never felt there is a need to directly measure downtime attributable to the workers.”

 

Illustration #1: Workers at a construction site

 

I explained, “Take for example a likely scenario among the construction workers. The steel fixer foreman complained to the project manager that their work is delayed and his workers cannot start work because the formwork was not ready. He claimed he loses money paying his workers their daily wages even though his team of workers could not be deployed usefully to carry out productive work and hence, they did not generate any income for him.

I am very certain the project manager will yell at the formwork[1] subcontractor with this classic remark, ‘I don’t care what you do. You must complete your work by my schedule. If you can’t, you better put in more people.’

Manpower, being the most flexible resource that can be deployed to increase the production rate, is always seen as the easiest way out of a tight situation.

But adding manpower is not a good option most of the time. First, the root cause that prevents the formwork team from completing the work on time must be found. The workers were down or idle not doing useful work because of some root cause(s). If a specific root cause is found, a solution that eliminates or mitigates this problem can be implemented immediately to prevent the same occurrence that delayed the completion of the formwork schedule.

It is the perseverance of the formwork subcontractor in finding the root cause(s) and resolving the issue(s) quickly that determines whether he can resist adding more manpower or not. This is because he has to minimize the downtime losses of his workforce arising from this issue(s).

Without adding more manpower and yet he is still able to complete all future work assigned to him on schedule, he indeed had managed to control his labor cost very tightly where his workforce suffers little downtime. That will lead to high productivity and results in higher profits.

If he failed to find a resolution to eliminate the root cause of his workers’ downtime that in turn caused the delay in completion of the formwork in accordance with the project manager’s schedule, he has no choice but to add more workers than necessary. With a much larger number of workers carrying out the same amount of work his productivity is thus, much lower.”

John interrupted and said, “Downtime reduction is a crucial element to his profitability. In this case downtime is all about time lost due to workers idling their time away. The idle time could be due to several reasons that are mostly uncontrollable, I supposed.”

“You are right,” I said, “Reducing downtime is an important element of operations management. You cannot simply add workers to buffer against the high downtime. Labor productivity will spiral downwards and eats into your profit margin.”

“But really, how do you measure the workers’ downtime? I have no idea at all,” said John.

“Let me go on to explain another working environment before I come back to address this question, can I,” I asked.

John said, “Of course. I am on four ears.”

 

Illustration #2: Factory-based manufacturing of goods

 

I illustrated, “On the other hand in a factory environment, the production of goods can range from the simplest gadgets to highly sophisticated items like cars or computer chips. The number of components that goes into the production of a car could be more than 15,000 parts. The number of steps required to produce a computer circuitry could be more than a hundred processes. With so many components and process steps in making a car or a computer chip, the chance of not meeting the production schedule is very high. On-time delivery is almost never near to 100% for most companies.

In other words, the production of a single batch of products will most likely meet up with some cock-up somewhere along the production process. The only question is will the same cock-up occur frequently or for a long enough period of time so much so that management feels more workers must be employed to ease the production flow.”

John interrupted, “I am very familiar with this situation. I have been running several plants for almost 2 decades.”

I continued, “This is a real story of an inkjet printer company. I conducted a task audit on one of its production lines. The result did not come out as a surprise to me. In my task analysis, I recommended that one-third of the direct workers who are assigned to operate the highly sophisticated assembly line be up-tasked or transferred out.

In other words, one-third of the operators were excess workers. I shared this recommendation with the production manager. He was quite taken by a shock. But he diligently went through my analysis and understood my recommendation on the potential to cut manpower.

By the way, he saw that it could be a credit to him if he subsequently managed to reduce his manpower requirement for next year’s budget. But his production supervisor did not see the possibility of removing one-third of the number of operators from his production line as feasible.

Instead, he wrote a very strong email message claiming that other than keeping to the current pool of workers, he saw the needs to deploy two of his spare operators to assist a particular test station, called TOVA. He claimed that despite having four workers who were already assigned to that station he was certain it was still short of workers.

An investigation into the period when he was forced to deploy two more spare operators at TOVA showed that the TOVA equipment was producing a lot of failed parts. For each failed part, it had to be manually reloaded back onto the conveyor line for retest.

The output of the line, though already severely impacted by the large amount of parts that failed, was again slowed down by the manual reloading of the failed parts for retest. On top of the lower output causing a much lower productivity level of the assembly line, the additional workers further worsen the labor productivity.

A few weeks later, the root cause of the problem where the TOVA equipment was over-rejecting good parts was found and a solution was implemented. The production rate of the assembly line went up by 20 percent immediately. There wasn’t a need for the recently added operators since there wasn’t any over-rejection any more.

In addition, the operators were observed to be quite free, idling for most of the time.

Earlier on the impulse to add more manpower was high when downtime caused by the over-rejecting issue and that it was not resolved quick enough despite two weeks had gone by.

After the issue was eliminated, the bad memories of having to add additional operators lingered on in the mind of the production supervisor. He preferred to keep the extra workers despite knowing the fact that the operators are now relatively free. The resistance to down-size can be quite formidable. Or put it another way, the concept of “more hands lighten the load” has a strong following. This is buffer mentality.

Would you question why in the first place, I recommended 38% reduction in manpower required? In the past, there could be too much interruptions and intermittent stoppages in the assembly line. These are downtime losses. In order to catch up with lost production or unnecessary high level of yield losses, more people were added in many parts or sections of the production line in order to cope up with the production schedule.

As the number of interruptions or intermittent stoppages gradually decreased due to continual improvements put in place over the last two weeks, the equipment needs less human attention now. The equipment downtime had gone down significantly.

However, the production supervisor still remembers vividly, how he had to overcome the production backlogs and missed schedules with his enlarged pool of operators. He prefers to keep a bloated workforce despite knowing it contributes to lower level of productivity. In his mind, the inability to meet the schedule is of utmost importance. Productivity is secondary.

To avoid low labor productivity it is strongly advised that there is a need to conduct task audit to review the manpower requirement once every three years. This is absolutely necessary to ensure that the company does not lose focus on its level of labor productivity and effectively prevents a bloated workforce that could lead to undesirable psychological problems among the workers.”

“Eric, I too, agree with you. If the equipment downtime is not monitored closely, the resulting scenario is more manpower than necessary is deployed to make up for the shortfall in production capacity due to downtime losses.

Can you give me a real-life example that touches on equipment downtime and how it could be reduced effectively to deliver double digit percentage increased in productivity?” asked John.

I scratched my head and thought hard. I remember when I was a consultant to Eastern Wire, a Singapore company that produces wire mesh for the construction industry. This company equipment downtime was horrendous. I decided to use this company’s poor equipment maintenance program as a case study.

 

Illustration #3: Poor equipment maintenance

 

I explained, “Eastern Wire bought very expensive equipment of value more than $1.5 million Singapore dollars per piece to weld wire rods into wire meshes. In June 1991, the group general manager of NatSteel Ltd asked me to visit this subsidiary to diagnose what I can do to raise this company’s productivity. He was not happy at all with the profitability of this subsidiary when the market leader was controlling more than 45% of the market share and produces three times its annual profits. 

When I was at the factory floor, I saw a specifically tailor-made pan that lies beneath the foot-print of the welding equipment. I asked the foreman what this is for. He replied, ‘It is used as a secondary containment to prevent the lubricating oil from spreading across the floor and thus, making it an unsafe place to work in. It is a safety measure.’

In my mind, I was thinking, ‘This is the worst kind of scenario that I can ever see in a factory. The equipment is leaking lubricating oil and instead of stopping the leakage at the source, a pan is fabricated to contain the oozing of lubricating oil. I guess the maintenance program has been severely neglected for a few years.’

I walked down the factory and I saw a few pieces of similar equipment all cradled with a pan to contain the oozing lubricating oil.

I asked the maintenance manager if he monitors the equipment downtime. The maintenance manager replied, ‘Next to every piece of the equipment, we have this little electronic box that captures the machine downtime. When a machine is down, the operator presses a downtime-start button and keys-in the equipment downtime code. When the technician had repaired the equipment, he presses another downtime-end button.

At the end of every week, these downtime data were pulled into a server where the downtime software automatically analyzes the equipment downtime. The same data can be used to compile a monthly downtime report and produces a line-chart to show the downtime trend.

On the average, the downtime has been hovering around 40%. Before this cute little downtime box is installed, the downtime was around 60%.’

I was not amazed by the capability of this little cute box or the downtime software. What I am more interested is the accuracy of the downtime collected in this manner for several reasons.

First, short intermittent stoppages are frequent and perhaps, far too frequent that this kind of downtime is not recorded. These intermittent stoppages are usually fixed by the production operators themselves. For this reason, the operators do not diligently capture the time lost to intermittent stoppages.

Second, the equipment could be down intermittently for reason of running out of materials. These time lost were not recorded. I noticed that the operator had to leave the equipment idled while he went to search for the cross wires. Cross wires are dropped from the cross wire feeder onto the welding blocks where they are welded to the main wires to form a wire mesh.

Third, when a batch of wire mesh has been produced, the operator has to stop the equipment, tie up the bundle of wire mesh and hoist them away from the welding equipment. This time lost too, were not recorded.

Four, the operator was seen busy keying in the production order information into the welding equipment before he can start the welding process. This is because every batch of production orders must be keyed into the equipment which then automatically re-set itself to produce the desired length and wire spacing. This lost time was not captured.

All these equipment downtime losses could easily contribute to more than 20% of the equipment downtime. But the cute little electronic box did not capture these downtime losses. I believed the downtime must be at 20% higher than the reported 40%.

I collected the standard times for each of wire mesh types for every piece of the equipment. Using the standard time that I have compiled for each of the mesh type and equipment operating speed, I went on to compute the productivity of all these equipment. The productivity was about 30%.

A cool 70% of lost production was attributed to the equipment downtime. Can you imagine wasting 70% of the equipment capacity to downtime alone?”

“Hey, Eric, the maintenance manager reported the equipment downtime was 40%. Based on your productivity analysis using the standard time method, the downtime was 70%. There is a big gap of 30%. How do you explain this discrepancy?” asked John.

“The reported downtime at 40% was the downtime losses that were diligently captured by the cute little box. The four types of downtime losses due to; intermittent stoppages resolved by the production operators, downtime due to material shortages, removal of the finished goods from the equipment and the time lost when the operator set up the equipment to produce the next batch of wire meshes were not captured by the cute little downtime boxes.

These downtime losses accounted for the difference of 30% in the calculated downtime of 70% less the reported 40% downtime losses. In this case, the unrecorded downtime is as high as 75% of the recorded downtime.”

“Eric, I quite don’t get you. Do you mean the downtime losses captured by the electronic unit is grossly under-reported?” asked John.

“Precisely,” I replied, “Most companies actively capture the equipment downtime losses in this way. However diligent the workers are, there are a significant amount of downtime that goes un-captured. To account for this kind of downtime that was not officially captured but the downtime recorded either manually or through the most sophisticated computer system, a term, ‘hidden losses’ is used.”

“What is hidden loss?” asked a baffled John.

“Hidden loss is used to account for the downtime losses that were not diligently recorded. In other words, it is used to surface the true picture of the downtime losses. It tells us that the recorded downtime is only a fraction of the true downtime. In most cases, the true downtime is much higher than the recorded equipment downtime.”

“Hmm! Hidden losses is an interesting concept. Can you elaborate further?” asked John.

I replied, “I will explain the detail of hidden losses in the next chapter.”         

“Alright,” said John, “I need a break for cigarette.”

 



[1] The formwork must be put up first before the steel fixer can fix the steel reinforcement bars.

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