Jidoka (自働化) isn’t just “stop and fix” or “stop and call.” It is a complete approach to automation that includes building in the ability of a machine to stop when it malfunctions but also includes many other things. Sakichi Toyoda’s Type-G loom didn’t just stop when the yarn broke, it also had automatic shuttle change, which reduced the need for human intervention in its normal operations, and was a breakthrough that had eluded everybody else.
“More robots means lower unemployment and better trade performance. […] The United States does not lose jobs because there is not enough work to be done but rather because U.S. industry is not competitive with foreign producers. More robots will help fix this.”
It doesn’t mean robots are bad, only that they are not a panacea. Toyota’s Global Body Line is designed to use welding robots where they are justified, and manual welding where not, using the same fixtures.
In an auto parts plant in Japan, I remember seeing a machining cell with old machines served by robots. A few yards away were new, automated lines that didn’t use robots.
It looked very much as if the old cell with new robots was the result of incremental automation, and that the lessons learned had been applied in the design of the new lines.
Robots are tools. If you know how to use them, they will help you; if you don’t, buying more is just a waste of money.
See on Scoop.it – lean manufacturing
“Inside Toyota Motor Corp.’s oldest plant, there’s a corner where humans have taken over from robots in thwacking glowing lumps of metal into crankshafts. This is Mitsuru Kawai’s vision of the future…”
According to the article, Toyota’s management feels that maintaining the know-how to make parts manually is essential to be able to improve automated processes.
See on www.bloomberg.com
See on Scoop.it – lean manufacturing
“…Automation has long been a central tenet of lean. It is in the automation versus labor cost issue where conflict arises. Toyota spends a lot of time thinking about and working on jidoka – automation with a human touch. In a nutshell, it means investing in automation to enhance human capability, rather than replace it…”
One of the rare articles in English where Toyota’s jidoka is accurately portrayed as a complete — and effective — automation strategy, rather than reduced to the notion of machines that stop when they malfunction. As Bill recognizes, there is more to it than that.
See on www.idatix.com
Google “Karakuri Kaizen,” and you see a small number of Youtube videos from Japan, Thailand, Italy, and Hong Kong showcasing materials handling devices that rely on gravity, levers, cams and inertia to move bins in elaborate ways, transfer parts between machines, or deliver a controlled number of small parts to an operator’s hand.
Here is one from Japan’s JMAC with multiple examples:
Such devices have long been used as part of TPS and Lean, but now we have a generic name for them. The principles of Karakuri Kaizen given at the end of this video are as follows:
- Don’t use the human hand. Move objects automatically.
- Don’t spend money.
- Use the force of your equipment.
- Build it with the wisdom and creativity of the people of the shop floor.
- For safety, don’t just rely on paying attention but build a device that stops automatically.
While “Karakuri Kaizen” is an alliteration that rolls of the tongue almost as easily as “cash for clunkers” or “toys for tots,” you may still wonder where “Karakuri” comes from and what it means. Until “Karakuri Kaizen,” I had never heard it stand-alone but always as part of “Karakuri Ningyo,” or Karakuri Dolls, which are wind-up automata with wooden gears and levers developed at toys in 18th-century Japan. The best known are tea-serving dolls, like the one in the featured image.
As Karakuri dolls are a reminder of ancient ingenuity, the term has a positive connotation in Japan. I once used a picture of one in a magazine ad for US-made automation software, to connect the product with the local culture. But the term, obviously, means nothing to anybody who is not Japanese.
It was a single thread that gave a man a dream, created a little history and displayed the talents of a remarkable mind and a family with resourcefulness in its genes.
Sakichi Toyoda wasn’t all that interested in fast-moving machinery, just machines in motion. It’s how the Toyota Production System began. It’s how an inventor with a sharp eye and even sharper mind built an empire…
A summary of Toyota history with the usual omissions:
- Automatic shuttle change. The ability to stop when thread broke was not the only innovation of Toyoda looms. Automatic shuttle change was equally important, not just to looms but as a forerunner of autonomation, the Toyota approach to automation.
- The German connection. Toyota learned much about car technology from Germany through Kazuo Kumabe and his research team, in particular reverse-engineering a 1936 DKW. The concept of Takt also came from the German Junkers company via the Mitsubishi Aircraft plant in Nagoya.
See on www.newsday.com
This article from Industry Week suggests that for Toyota to use high technology in Manufacturing is something new or a departure from its traditional system. It presents the Assembly Line Control (ALC) system as something new, when it has been in existence since at least the early 1990s.
We should not forget that even Ohno described jidoka as one of the two pillars of the Toyota Production System, on a par with Just-in-Time, and that jidoka means “automation with a human touch,” or “autonomation.”
The English-language literature often reduces jidoka to making machines stop when they malfunction, but the actual jidoka includes a complete automation strategy, with sequences of steps to automate both fabrication and assembly operations, as well as an approach to managing the interactions between humans and machines on a manufacturing shop floor.
This is what I wrote about in Working with Machines.
See on www.industryweek.com
This is what jidoka/autonomation is about! Contrary to what you read in the reductionist literature, jidoka is not just about stopping machines when they start to malfunction. It is instead a complete and intelligent approach to automation.
See on www.dcvelocity.com
Toyota’s jidoka isn’t just about stopping production when something goes wrong. It is an automation strategy that works because it is incremental and centered on human-machine interactions. It is essential to the strength of manufacturing in high-wage economies and should command more attention than it has so far among Lean implementers.
The most striking characteristic of automation in manufacturing is that, while making progress, it has consistently fallen short of expectations. In Player Piano, Kurt Vonnegut articulated the 1950s vision of automated factories: integrated machines produce everything while their former operators are unemployed and the managers spend their time playing silly team-building games at offsite meetings. 60 years on, the most consistently implemented part of Vonnegut’s vision is the silly team-building games…
Nippon Steel’s Yawata Steel Works in Kitakyushu, Japan, produce as much today with 3,000 employees as they did with 40,000 in 1964, and this transition was accomplished without generating massive unemployment. There are other such limited areas of automation success, like the welding and painting of car bodies. When manufacturing jobs are lost today, it is almost never to automation and almost always to cheaper human competition elsewhere. In the words of an experienced operator in a plant making household goods in the US, “When I joined 25 years ago, I expected these jobs to be automated soon, but we’re still doing them the same way.”
What is holding up automation today is not technology but the lack of consideration for people. There are entire books on automation without a paragraph on what their roles should be. Of course, a fully automatic, “lights-out” factory has nobody working inside, so why bother? There are at least two reasons. First, even an automatic plant needs people, to program its processes, tell it what work to do, maintain it, monitor its operations and respond to emergencies. Second, successful automation is incremental and cannot be developed without the help of the people working in the plants throughout the migration.
Enter autonomation, or jidoka, which is sometimes also called “automation with a human touch” but really should be called human-centered automation. Instead of systems of machines and controls, it is about human-machine interactions. In the classical House of Lean model, the two pillars holding up the roof at Just-In-Time and Autonomation, or Jidoka. Figure 1 is lifted from the introduction to Working with Machines, and shows what happens when the jidoka pillar is ignored.
More and more, the Lean literature in English uses the japanese word jidoka rather than autonomation, but with its scope reduced to the idea of stopping production whenever anything goes wrong, and the concept is tucked away under the umbrella of Quality Management.
Toyota’s jidoka is a tricky term, because it is an untranslatable pun. Originally, the Japanese word for automation is jidoka (自動化) , literally meaning “transformation into something that moves by itself.” What Toyota did is add the human radical 人 to the character 動 for “move,” turning it into the character 働 for “work,” which is still pronounced “do” but changes the meaning to “transformation into something that works by itself.” It”s automation with the human radical added, but it is still automation, with all the technical issues the term implies.
The discussion of automation in the first draft of Working with Machines started with the following historical background, which was edited out like the chapter on locomotives and typewriters, on the ground that it contained no actionable recommendations. In this blog, I can let you be the judge of its value.
From tea-serving wind-up dolls to autonomation
The word automation was first used by Ford manufacturing Vice President Delmar Harder in 1947 for devices transferring materials between operations. He set as targets a payback period of at most one year in labor savings, which meant in practice that each device should not cost more than 15% above an operator’s average yearly wages and eliminate at least one operator. While this kind of economic analysis is still used, from the perspective of Toyota’s system, Ford’s focus on materials handling was putting the integration cart before the unit operation horse. Toyota’s approach focuses on individual operations first, and only then addresses movements of parts between them. In 1952, John Diebold broadened the meaning of automation to what has become the common usage, and painted a picture of the near future that was consistent with Kurt Vonnegut’s.
At that time, automatic feedback control was perceived to be the key enabling technology for automation, to be applied to ever larger and more complex systems. It was not a new concept, having been applied since 1788 in the centrifugal governor regulating pressure in a steam engine (See Figure 2)
Figure 2. James Watt’s 1788 centrifugal governor
Applying electronics to feedback control in World War II had made it possible, for example, to move a tank’s gun turret to a target angle just by turning a knob. Postwar progress in the theory and application of feedback control both caused many contemporary thinkers, like Norbert Wiener, to see in the concept a philosophical depth that is truly not there, and to underestimate what else would need to be done in order to achieve automation. Of course, if you cannot tell a machine to take a simple step and expect it to be executed accurately and precisely, then not much else matters. Once you can, however, you are still faced with the problem of sequencing these steps to get a manufacturing job done.
While automatic feedback control was historically central to the development of automatic systems, it is not at center stage in manufacturing automation today. With sufficiently stable processes, open-loop systems work fine, or feedback control is buried deep inside such off-the-shelf components as mass flow controllers, thermostats, or humidity controllers. Manufacturing engineers are occasionally aware of it in the form of variable-speed drives or adaptive control for machine tools, but other issues dominate.
Fixed-sequence and even logic programming also have a history that is as long as that of feedback control and are by no means easier to achieve. Figure 2 shows two examples of 18th century automata moved by gears, levers and cams through sequences that are elaborate but fixed.
Figure 2. 18th century automata from France and Japan
These concepts found their way into practical applications in manufacturing as soon as 1784, with Oliver Evans’s continuous flour mill that integrated five water-powered machines through bucket elevators, conveyors and chutes (See Figure 3). The same kind of thinking later led to James Bonsack’s cigarette making machine in 1881, and to the kind of automatic systems that have dominated high-volume processing and bottling or cartonning plants for 100 years, and to the transfer lines that have been used in automotive machining since World War II.
Fixed-sequence automation works, but only in dedicated lines for products with takt times under 1 second, where the investment is justifiable and flexibility unnecessary. Rube Goldberg machines parody this type of automation.
Automation with flexibility is of course a different goal, and one that has been pursued almost as long, through programmable machines. The earliest example used in production is the Jacquard loom from 1801, shown in Figure 4. It is also considered a precursor to the computer, but it was not possible to make a wide variety of machines programmable until the actual computer was not only invented but made sufficiently small, cheap and easy to use, which didn’t occur until decades after Vonnegut and Diebold were writing.
By the mid 1980’s, the needed technology existed, but the vision of automation remained unfulfilled. In fact, more technology was available than the human beings on the shop floor, in engineering, and in management knew what to do with. As discussed in the post on Opinels and Swiss knives, the computer as a game changer. In manufacturing, this was not widely recognized when it became true, and it still is not today.
Writing in 1952, John Diebold saw nothing wrong with the way manufacturing was done in the best US plants, nor did he have any reason to, as the entire world was looking at the US as a model for management in general and manufacturing in particular. In the 1980’s, however, when GM invested $40B in factory automation, it was automating processes that were no longer competitive and, by automating them, making them more difficult to improve.
Whether the automation pioneers’ vision will ever come true is in question. So far, every time one obstacle has been overcome, another one has taken its place. Once feedback control issues were resolved came the challenge of machine programming. Next is the need to have a manufacturing concept that is worth automating, as opposed to an obsolete approach to flow and unit processes. And finally, the human interface issues discussed must be addressed.
21st century manufacturers do not make automation their overall strategy. Instead, automation is a tool. In a particular cell, for example, one operator is used only 20% of the time, and a targeted automation retrofit to one of the machines in the cell may be the key to eliminating this 20% and pulling the operator out of the cell.
Using Opinel knives while picnicking last summer got me thinking about their differences in design philosophy from Swiss knives, our traditional perception of multifunction tools, and how smart phones and machining centers contradict that perception.
Mostly known for snow-capped mountains, the Savoie region of France is also the birthplace of the Opinel, a pocket knife designed 120 years ago, and very popular there with anybody who hikes or just goes on a picnic. As you can see below, it is a simple knife with a sharp, pointed blade, and a ring to lock it closed or open.
As a concept, it is diametrically opposed to its cousin, the swiss knife, and its multiple functions:
The Opinel only has one function, but performs it well; the swiss knife has many but does not excel at any. It will cut, but not as well as the Opinel; it serves as a corkscrew, but provides no leverage to pull out the cork; it will open cans, but slowly and by pulling the sharp edge of the lid outwards towards your hand rather than into the can, etc. It is convenient because you only have to carry one tool around, but, for everything it does, there is a dedicated tool that does it better.
When we think of dedicated versus multifunction tools, we usually think that they are like Opinels and swiss knives and that, when we add more functions to a tool, we necessarily compromise on performance or quality for each function. But is that necessarily true?
Our smartphones let us talk to each other but also contain the contact data of everyone we have met since elementary school. They tell you where we are on precise maps, wake us up in the morning, work as stopwatches and egg timers, play our music, receive our favorite radio station, identify a song from a snippet of a recording, etc.
Dedicated tools do not exist for everything a smartphone does and, when they do, rarely outperform the smartphone apps. For example, I have not seen an alarm clock do more than the clock app on my phone in terms of selecting whether it rings just once or every weekday at the same time, how loud, with what sound, etc.
What is it that makes a smartphone different from other multifunction devices? In what way is it not like a swiss knife?
The short answer is that a smartphone is a computer. We often think of computers as machines like any other, or worse when we are frustrated with confusing interfaces or system crashes, but the reality is that they are qualitatively different, and that programmability allows them to outperform dedicated tools. Their hardware configurations make them smartphones, game systems, laptops, or industrial controllers but, within this context, the range of services they can render well is limited only by the imagination and talent of programmers.
In production, machining centers or computer-controlled fabrication facilities are not swiss knives, in that their flexibility is not bought by a compromise in performance, and this has far-reaching consequences on production engineering and operations.