Tag Archives: Manufacturing

Toyota Understands Robots are Best Used to Enhance the Value Employees Provide

Toyota has always seen robotics as a way to enhance what staff can do. Many USA executives think of robotics as a way to reduce personnel. Toyota wants to use the brainpower of employees to continually improve the organization. Toyota wants to free people for monotonous or dangerous work to let them use their minds.

Humans Steal Jobs From Robots at Toyota

Humans are taking the place of machines in plants across Japan so workers can develop new skills and figure out ways to improve production lines and the car-building process.
…
“We cannot simply depend on the machines that only repeat the same task over and over again,” Kawai said. “To be the master of the machine, you have to have the knowledge and the skills to teach the machine.”

Kawai, 65, started with Toyota during the era of Taiichi Ohno, the father of the Toyota Production System envied by the auto industry for decades with its combination of efficiency and quality. That means Kawai has been living most of his life adhering to principles of kaizen, or continuous improvement, and monozukuri, which translates to the art of making things.

“Fully automated machines don’t evolve on their own,” said Takahiro Fujimoto, a professor at the University of Tokyo’s Manufacturing Management Research Center. “Mechanization itself doesn’t harm, but sticking to a specific mechanization may lead to omission of kaizen and improvement.”

We need more companies to learn from the executives at Toyota. They show real respect for people. They are not focused on how much they can extract from the corporate treasury to build themselves castles at the expense of other employees, customers and stockholders as far too many USA executives are.

Toyota has been extremely innovative in investing in robotics as human assistants (partially this is due to the extreme demographic problems Japan faces): Toyota Develops Thought-controlled Wheelchair – Toyota’s Partner Robot – Toyota Winglet – Personal Transportation Assistance.

Manufacturing Outlook and History In the USA and Globally

I write primarily about management improvement on this blog – which makes sense given the title. In the very early days I had more on investing, economic data, science, engineering and travel. Then I created three new blogs (Curious Cat Investment and Economics Blog, Curious Cat Science and Engineering Blog, Curious Cat Travel Photos blog) and that made this blog more focused.

Even so the lines of what fits where can be a bit fuzzy and I continue to write about manufacturing, and health care, with a focus on economic data, occasionally. And that is what I am doing today while touching on management related to manufacturing a bit.

As I have written before the story of manufacturing in the USA, and globally, is greatly increased quality of processes and output as well as greatly improved productivity over the last few decades. Manufacturing output also increased, including in the USA, as I have written consistently for a decade now. For example: (Top 10 Countries for Manufacturing Production from 1980 to 2010.

Still many people have the notion that USA manufacturing has been declining, which hasn’t been true, and certainly isn’t true now (the last couple of years have been especially strong and even the general public seems to realize the idea of the USA losing manufacturing is a myth).

Chart of Manufacturing Output fro 1992 to 2012 - USA, China, Japan and Germany

Based on data from the UN. See my blog post on my economics for more details on the data (to be posted next week).

The chart is impressive and illustrates the point I have been hammering home for years. The USA manufacturing base is growing and far from crumbling (job losses are deceiving as they are global and not an indication of a USA manufacturing decline). China’s manufacturing growth is incredible. China and the USA are far away the top 2 manufacturing countries. Japan and Germany make out the top 4 before a large gap which then is followed by a group of countries that are very close (Korea is 5th with less than half the production of Germany).

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Leading Manufacturing Countries from 2000 to 2010: China, USA…

chart showing leading manufacturing countries output from 2000-2010

Chart of manufacturing production by the top 10 manufacturing countries (2000 to 2010). The chart was created by the Curious Cat Economics Blog. You may use the chart with attribution. All data is shown in 2010 USD (United States Dollar).

Over the years I have been posting data on the manufacturing output of leading countries. In 2010 China finally overtook the USA to becoming the leading manufacturer (long after you would have thought listening to many news sources and political leaders). In a previous post on the Curious Cat Economics Blog I looked at the output of the top 10 manufacturing countries with a focus on 1980 to 2010.

In 1995 the USA was actually very close to losing the lead to Japan (though you wouldn’t think it looking at the recent data). I believe China will be different, I believe China is going to build on their lead. There has been some talk for several years of manufacturing moving out of China seeking lower cost countries. The data doesn’t support any decline in Chinese manufacturing (or significant moves away from China toward other South-East Asian countries). Indonesia has grown quickly (and is the largest SE Asian manufacturing country), but their total manufacturing output is less than China grew by per year for the last 5 years.

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Value Stream Mapping for Fun and Profit

Guest post by Evan Durant, author of the Kaizen Notebook blog [The broken link was removed].

I tend to get a little preachy about the importance of value stream maps, but they really can be useful tools not only to plan an improvement effort but also to monitor your progress going forward. In particular they provide a way to quantify the impact of changes to your process. Here’s a real life example as a case in point.

For a particular value stream a team went to gemba, followed the flow of material and information, collected process cycle times, and counted inventory. When everything was mapped and all the data tallied, here was the current state that they came up with:

Total Lead Time:		16.8 days
Process Lead Time:		2.2 days
Process Time:		1.9 days
Operator Cycle Time:		8.2 minutes

So what does all this mean? First of all the Total Lead Time represents the amount of time that a new piece of raw material would take to enter the value stream, be worked on, wait around with all the rest of the material in process, and then finally make its way to the customer. This number is usually driven higher by large amounts of in-process inventory caused by pushing between operations.

Second, the Process Lead Time is the amount of time it would take to process a single batch through the process, if it didn’t have to wait behind any other batches. Note that even though parts are processed one at a time through all of the manual operations, a certain amount of batching is required to overcome long machine cycle times in automatic operations. Also we do not ship parts to the customer one at a time, but rather in standard package sizes.

Third, we have the Process Time. This is the total amount of value added time, manual and automatic processing, that a part sees in the value stream.

Finally the Operator Cycle Time (also called manual time) is the amount of actual “touch” time required to make a part. The difference between the Process Time and the Operator Cycle Time is the Machine Cycle Time (also called automatic time). This is when a batch of parts is on a machine that does not require any operator intervention during a cycle. (We have a lot of machine cycle time in this value stream.)

Then the team applied the concepts of flow and pull to reduce overproduction and pace the value stream to the rate of customer demand. The results of the future state map were as follows:

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Marketplace Looks at the Apple Economy

Marketplace looks at the Apple economy in China [the broken link was removed]. Marketplace is an excellent source of actual journalism; rare in the post Bill Moyers days, sadly.

A look inside a Foxconn factory< [the broken link was removed]

The first misconception I had about Foxconn’s Longhua facility in the city of Shenzhen was that I’ve always called it a ‘factory’ — technically, it is. But after you enter the gates and walk around, you quickly realize that it’s also a city — 240,000 people work here. Nearly 50,000 of them live on campus in shared dorm rooms. There’s a main drag lined on both sides with fast-food restaurants, banks, cafes, grocery stores, a wedding photo shop, and an automated library. There are basketball courts, tennis courts, a gym, two enormous swimming pools, and a bright green astroturf soccer stadium smack-dab in the middle of campus. There’s a radio station — Voice of Foxconn — and a television news station. Longhua even has its own fire department, located right on main street. This is not what comes to mind when you think “Chinese factory.”

Yet it is: as you walk beyond the civic center of Longhua, the buildings begin to change.

[the embedded video was removed, so I removed the link]

From a management perspective there is a great deal to be desired in Apple’s manufacturing practices. The economic perspective however, for me, provides a much different picture than those in rich countries (USA, Europe, Singapore, Japan…) often feel.

The jobs provide workers a chance to earn what for them is a great deal of money. Yes the conditions are harsh – I wouldn’t want to have to work there. But I am pretty sure I would not be happier, if I lived in China, and everything else remained the same in China except now all the Apple products were made in Singapore, USA and Spain.

It is good that Apple has pressure to improve conditions at their plants. I also wish they would adopt more lean thinking in their management system. Doing so would likely include moving production to at least 2 or 3 locations (probably adding the Americas and Europe while remaining in China). Apple pays a great deal of attention to customer focus (though they still have plenty to do here too); they really need to pay much more attention to respect for employees (I include their sub-contractors in this statement).

The market is also working. Chinese salaries are rising rapidly. From a very low wage, but still rapidly which is a great thing for tens of millions of people. And there are huge economic spillover affects as those people spend and invest their money (as one of the workers was quoted as saying he is saving up money while working at Foxconn to open his own construction business).

Looking at Auto Manaufacturing in the USA

America’s Dirty War Against Manufacturing

Bob Lutz, the former head of GM, says it was neither uncompetitive wages nor unions that drove the Big Three into decline. It was a management with its eye focused on the bottom line and the short term.

That sentiment should be familiar to students of Deming (it is one of Deming’s 7 deadly diseases). It is sad that this bad management practices, short-term thinking, continues to do harm several decades later. Hopefully we can do better in the next few decades.

retiree health care and pensions — burdens that are borne by society, not manufacturing plants, in every other advanced country. That disparity, the result of policy decisions made in Washington rather than wages negotiated by the United Auto Workers, was the source of most of the labor-cost advantage enjoyed by foreign companies.

The excessive health care costs in the USA, another of Deming’s 7 deadly diseases, has continued to get worse every year since he classified it as one. The damage that the failed health care system in the USA does to the USA is enormous.

Manufacturing Skills Gap or Management Skills Gap?

I stumble across articles discussing the problem of manufacturers having difficulty finding workers with the skills they need (in the USA largely, but elsewhere too) somewhat regularly. While it is true that companies have this problem, I think looking at the problem in that way might not be the most insightful view. Is the problem just that potential workers don’t having the right skills or the result of a long term management skills gap?

To me, the current manufacturing skills gap results directly from short term thinking and disrespect for workers practiced by those with management skills shortages over the last few decades. Those leading the manufacturing firms have shown they will flee the USA with the latest change in the wind, chasing short term bonuses and faulty spreadsheet thinking. Expecting people to spend lots of time and money to develop skills that would be valuable for the long term at manufacturing firms given this management skills shortage feels like putting the blame in the wrong place to me.

Why should workers tie their futures to short term thinking managers practicing disrespect for people? Especially when those managers seem to just find ways to blame everyone else for their problems. As once again they do in blaming potential workers for their hiring problem. The actions taken based on the collective management skill shortage in the manufacturing industry over the last few decades has contributed greatly to the current state.

If managers had all been managing like Toyota managers for the last 30 years I don’t think the manufacturing skill gap would be significant. The management skill gap is more important than the manufacturing skill gap in my opinion. To some extent the manufacturing skill gap could still exist, market are in a constant state of flux, so gaps appear. But if their wasn’t such a large management skill gap it would be a minor issue, I believe.

That still leaves companies today having to deal with the current marketplace to try and find skilled workers. But I think instead of seeing the problem as solely a supplier issue (our suppliers can’t provide us what we need) manufacturing firms would be better served to look at their past, and current, management skills gap and fix that problem. They have control over that problem. And fixing that will provide a much more solid long term management base to cope and prosper in the marketplace.

Another management issue may well be the hiring process itself. As I have written about many times, the recruitment process is highly inefficient and ineffective. When you see workers as long term partners the exact skills they have today are much less significant than their ability to meet the organizations needs over the long term. In general, information technology recruiting has the worst case of focusing on silly skills that are really not important to hiring the right people, but this also can affect manufacturing hiring.

6 New Kiva Loans to Manufacturing Entrepreneurs

I have been a big fan of Kiva for quite some time, and have written about it previously: Kiva – Giving Entrepreneurs an Opportunity to Succeed, Thanksgiving: Micro-financing Entrepreneurs. I made 6 new loans today to manufacturing entrepreneurs in the USA (and Mexico); Tajikistan; Nicaragua; Armenia; and 2 in El Salvador. The webcast above shows Armen Tsaghikyan in Armenia. It does seem like his process maybe could use a benefit from a bit of application of lean manufacturing ideas.

It is great to be able to help out people whether it is providing useful information (like I hope my web site and blog do) or a small loan of capital that allows some capital improvements. Many of the loans through Kiva amount to providing a loan to get additional supplies (often they have very limited capital). But my favorite loans are those that allow for purchases of new equipment that will make them more efficient.

It is easy to help out yourself; you can loan as a little as $25. The 10 members of the Curious Cat team have made 292 loans for a total of $12,000. Comment with the link to your Kiva page and I will add a link on Curious Cat Kivans.

Touring Factories on Vacation When I Was Young

Growing up, occasionally, a family vacation would include a factory tour related to my Dad’s work. He was providing some management or engineering consulting and took the opportunity to check in on progress and visit the gemba. Here is a photo from one of those tours (in Nigeria, I think). My brother and Mom are visible in the photo.

The tours (which were not a very common occurrence) were quite enjoyable and interesting. Though I really didn’t like how noisy the factories were. Seeing all the machines and vast scale of the systems was quite a change of pace and added some excitement to the vacations (that often were already pretty exciting). I remember we also visited some factories in Kenya (in between seeing the game parks).

photo of factory tour with my family when I was a kid

Factory in Nigeria (I think) that my family toured

On this tour we found a bit of visual management showing which side of a crate should be on the top.
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Factorial Designed Experiment Aim

Multivariate experiments are a very powerful management tool to learn and improve performance. Experiments in general, and designed factorial experiments in particular, are dramatically underused by managers. A question on LinkedIn asks?

When doing a DOE we select factors with levels to induce purposely changes in the response variable. Do we want the response variable to move within the specs of the customers? Or it doesn’t matter since we are learning about the process?

The aim needs to consider what you are trying to learn, costs and potential rewards. Weighing the various factors will determine if you want to aim to keep results within specification or can try options that are likely to return results that are outside of specs.

If the effort was looking for breakthrough improvement and costs of running experiments that might produce results outside of spec were low then specs wouldn’t matter much. If the costs of running experiments are very high (compared with expectations of results) then you may well want to try designed experiment values that you anticipate will still produce results within specs.

There are various ways costs come into play. Here I am mainly looking at the costs as (costs – revenue). For example the case where if the results are withing spec and can be used the costs (net costs, including revenue) of the experiment run are substantially lower.
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