Can Industry 4.0 rejuvenate Total Productive Maintenance?

In this post:

The youngest among my blog readers may not understand what I mean with Total Productive Maintenance, this pre-Lean management approach to maximize machines and equipment effectiveness and aiming to improve companies’ performances.

TPM in a nutshell

In a nutshell, Total Productive Maintenance or TPM in short, originated in Japan, 1971. It was a participative spin-off of the american Productive Maintenance (a mix of maintenance policies to maximize machines’ availability and effectiveness), aiming to minimize all kind of losses by involving every department and everyone.

TPM had its heyday in the 1985-1995s in the western companies and failed to get mainstream despite the efforts to rebrand it Total Productive Management. The original name and much of the content, even so transposable to almost any activity, was too much linked to industrial machinery maintenance.

Total Productive Maintenance gave way to Lean Manufacturing and somehow got absorbed by Lean. TPM brought Overall Equipment Effectiveness (OEE) indicator to the world, a still very popular KPI nowadays.

Industry 4.0 and Total Productive Maintenance 2.0?

My basic assumption for this prospective thinking is that industry 4.0 environments will be highly automated so that the human factor will have lesser impact on the machines / cells / lines /workshops performance. Conversely machines’ utilization will regain focus.

Performance is determined by market requirements, but it will continue to be a mix of responsiveness, speed (time to market, lead time… ) and quality, with a higher expectation for agility than today. Costs may come second when dealing with high customization.

Performance will be mainly driven by machines’ availability, speed and yield, the latter being roughly the right first time rate. In other words OEE.

Availability is key for agility and responsiveness. This stresses the need of preventive maintenance and quick changeovers. Preventive maintenance starts with daily cleaning and inspection in order to keep all equipment in operational state and detect any wear or damage early. Some equipment will probably also need periodic calibration and geometry checks to ensure accuracy e.g 3D printing.

These tasks may be passed to former operators now converted into level one maintenance technicians. Further more in-depth periodic inspection will also be required by more expert staff that can be either company’s own or third-party. This reminds of the ‘autonomous maintenance’ pillar of TPM.

TPM autonomous maintenance in 4.0 environment

Autonomous maintenance intent was/is to give operators greater “ownership” of their equipment in order for them to take care and use responsibly. By increasing operators’ technical knowledge of the equipment they use and entitle them to do the simple daily maintenance tasks, autonomous maintenance aim was/is to:

  • ensure equipment is constantly well-cleaned and lubricated
  • maintenance experts’ time is freed for higher-level tasks
  • emergent issues are noticed and identified before they become failures
  • enrich the job of production operators.

if operators showed interest and demonstrated capacities, they could be trained further and assist maintenance experts for more complex maintenance tasks and even take part in repairs and overhauls.

In a industry 4.0 environment, the content of this ‘autonomous maintenance’ pillar of TPM must be adapted to the new technologies. It could encompass data management, using the digital twin, simulate… and require digital literacy.

In a industry 4.0 environment the role of operators as machine feeder, unloader and tool fitter may be marginalized thanks to automation. The jobs for production operators as we knew them may diminish and new jobs will be created requiring different skills and abilities, but not as many.

I could imagine recycling some of the former production operators into ‘autonomous maintenance’ operators, but my guestimate is that one operator could take care of 5 to 20 3D printers. The operator-to-equipment rate compared to traditional manufacturing will surely shrink. Besides, everyone will not show the necessary capacity to evolve.

Can Industry 4.0 rejuvenate Total Productive Maintenance?

As for the autonomous maintenance my guess is that chances are good, even so it may need to be updated in a new 2.0 version fitting the new technical environment.

Focus will be on equipment because of the investment, because of managers in love with tech, because equipment performance will be the main driver for (a production) company’s performance, and for probably more reasons.

For the other 7 traditional pillars I am not sure. You’re welcome to share your own thoughts.

About the author, Chris HOHMANN

About the author, Chris HOHMANN

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What is Industry 4.0 – Juergen Kanz

“Industry 4.0” was coined in Germany and is becoming the European name of what is also known as Smart Factory, Smart Manufacturing, Industrial Internet among others.

Note: German and French write “industrie” instead of “industry”

In this slightly more than one hour video, Juergen Kanz, Systemic Thinker and Theory of Constraints expert, introduces to the concept of Industry 4.0

You may jump to 4:55 to the explanations of 4th industrial revolution and how the German federal government came to encourage this initiative, and 12:40 for the presentation of the structure of the “platform industrie 4.0”.

Juergen takes the viewers deeper into the details and implications before linking the opportunities of Industry 4.0 to the Theory of Constraints (ToC) Body of Knowledge (around 49:00).  ToC provides several mindsets, principles, methods and tools that may help to install and get the benefits of industrie 4.0 based solutions.

Is 3D printing the ultimate postponement? Part two

In the previous post of this series, I used somewhat extreme examples to illustrate the benefits of postponement with additive manufacturing i.e. 3D printing (space exploration, ships amidst oceans and warfare). In this post I use more common examples about how the promises of these new techniques will disrupt existing businesses and bring new benefits to competitors and customers.

Spare parts for automotive industry, appliances, etc.

Spare parts are needed for mending cars or appliances for example. Until now, spare parts must be produced and kept in inventories in the eventuality someone needs a part. This happens eventually but it is hard guess to tell which parts, when and in which quantities parts will be required.

Therefore, spare parts production is launched according to complex and more or less scientific guessing, based on statistics. Once these parts are produced, they’ll go for various locations through the proprietary network or through  importers, distributors, retailers and repair stations.
Huge amounts of cash are kept frozen in inventories, scattered in many warehouses in various locations.

  • These inventories are likely to grow with each new specification change that affects a part, as the adequate replacement part must be provided
  • These inventories’ value will have to be depreciated when parts become obsolete and the probability of their sales diminishes

Storing and distributing spare parts is a business per se, but the value-added remains limited (which does not mean it is not profitable!), especially for the “players in the middle” who act more like cross-docking platforms taking their share of profits and risks.

Over time distributors and retailers slightly changed their business model and drift away from their original business: storage and retail.

In old days it was important to be the reliable parts provider and huge inventories were normality.

More and more those companies embrace a financial, more profit-driven purpose and keeping inventories is for them a necessary evil at best. Distributors and retailers try to get delivered at short notice in order to keep inventories – that is frozen capital and risk – low.

They push the problem upstream to manufacturers, the latter being required to reduce delivery lead time, which most often ironically means holding inventories to serve “off-the-shelf”. Distributors and retailers become a kind of post-office collecting orders, passing them over to manufacturers, who in some case have to deliver to the point of use, by-passing the distributor/retailer.

I worked in some industries facing this “problem” and the distributor / retailer channel in this way does not seem sustainable as manufacturers try to get rid of these “order collectors”.

Now with the rise of additive manufacturing techniques, new opportunities appear. Distributors and retailers may use them to become manufacturers themselves. What they need are competencies to use such equipments and managing CAD files from OEMs’ libraries, “print” spare parts at will: at the right moment, in the right version, without holding huge, costly and risky inventories of parts in huge warehouses, with high fixed costs.

Furthermore, customizing parts locally would yield additional revenue, as customers with specific and maybe urgent needs are willing to pay a premium.
So would scanning and redesigning no longer supported parts for which no CAD files are available.
This kind of service is an ultimate postponement because the manufacturing of parts is on hold until the very last moment, when the orders are confirmed or the parts paid!

This is one example about additive manufacturing (i.e. 3D printing) techniques can disrupt existing businesses and bring new benefits to (some) competitors and customers. The financial barriers to entry dropping significantly, OEMs could reconsider to re-integrate this kind of activity and keep the value creation all by themselves.

This post being a prospective analysis, I would be glad to read your comments.

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Is 3D printing the ultimate postponement? – Part one

Imagine the first habitable base on mars. Your challenge is to pack the first cargo spaceship with all the necessary for the staff to face all maintenance issues, until the next cargo spaceship can lift up, say three months later.

Chances are you’ll include a 3D printer and enough of printer’s raw material, simply because it would be the most efficient way to provide many things needed despite tremendous logistics constraints.

Now quit outer space and consider a tanker, an aircraft carrier or container ship amidst the ocean. In some aspects, these vessels share common traits with our base on mars:

  • storage space for spare parts, raw material and machines for maintenance purpose is scarce
  • they are far from everything, can be supplied only after some delay
  • supplying them is not without some risk (weather, enemies, etc.)
  • supplying them is not only risky but comes at (very) high cost

In these cases too, 3D printing is a good option to consider as printing what is needed at the very moment it is needed is the optimum solution and ultimate postponement.

What is postponement?

In manufacturing and supply chain operations, postponement means delaying the completion of a product or packaging products until a signal assigns specific customer or destination. This is useful when many variants would lead to possible misallocation if the completion would be based on forecasts.

Put simpler, postponement delays a decision until what is expected is clearly specified. The reason is most of transformation step in a process modify the product in such manner that returning to previous state is impossible.

Example: if you cut a piece of fabric to make a handkerchief, it cannot be returned to a piece of fabric for a trousers’ leg. (except it was a huge handkerchief or tiny trousers)

Materials usually lose flexibility along the transformation process. Once transformed there is no stepping back.

Postponement is used to delay the completion or manufacturing until a differentiation point from which the item loses its flexibility (e.g. pack in white box and add customized label latter).

Because postponement and later completion is no realistic option for our vessels or space base, they must embark spare parts for all possible cases, but under constraint of volume and in some cases weight.

The embarked mix is a set of items based on forecasts and tradeoffs about what could possibly happen and what is most likely needed, still carrying the frightening risk that what will really be needed will not be included in the cargo.

Printing at will

Now if you can trade the same finite volume and mass of many different spare parts selected through complicated statistical computation for a 3D printer and raw printer material, the risk drops to almost none as any required part (as long as material is suitable) can be printed when required, and even customized to some unexpected specification change.

This is why NASA, the navy or some private companies consider to embark 3D printers and train staff in order for the unit to be independent from its supply base for a longer period.


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Future of Lean and additive manufacturing

In a previous post titled “How much non-added value additive manufacturing can take out of actual processes?” my prospective thinking was all about technological disruptions and the impact on companies.

The same question is valid for the future of Lean. If as I assume much of the non-added value can be taken out of actual processes by additive manufacturing, what will be left for lean practitioners to work on?

Whole processes could be reduced to 3D printers or equivalent*, taking out lots of costs and non-value added. But what may be really shocking in near future could be to reconsider what we assumed being added-value in traditional manufacturing, e.g. cutting away material by lathing, milling, etc.

*3D printers stand here for a generic expression for additive manufacturing techniques and machines. 3D printers are already well-known from the public, therefore it makes it easier at present time to refer to additive manufacturing as 3D printing.

These processes transformed raw material in something of higher value, but at expense of a lot of energy, capital and material, like shavings, for example.

With the new perspective of additive manufacturing techniques, raw material will be used in just necessary quantity, most of the energy will really be used to “add” value and almost all of the manufacturing cycle time will be added value time.

Even the non-added value that cannot be suppressed – a former colleague of mine positively calls it “value enabling” – like all the fragmentation of the process between different techniques/machines, hand-offs, transfer, wip, etc. may simply disappear or at least seriously shrink.

Value Streams will become shorter and efficient, some Value Stream Maps limited to the order input and 3D printer!

While today about 2% of the lead time is usually added value, in near future it could soar up to 80% or more!

Future of Lean, Lean in the future, what is your point of view?

Bandeau_CH11You may share your opinion via a comment.

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Lean in digital age: sensors and data

In near future, technology and especially connected objects – smart things stuffed with sensors and so-called wearable devices – will supercharge Lean improvements.

One example of such already used device is given in a Mark Graban podcast about Hand Hygiene & Patient Safety. In this podcast (Episode #205), Mark’s guest Joe Schnur, VP Business Development at Intelligent M, explains how his wearable solution called smart band, (see video below) helps gather huge amount of accurate data compared to human observer with a clipboard.

You may listen to the whole podcast or skip to 13:30 and more specifically to 15:00 to hear about the wearable smart band, 21:50 about the data gathering.

Human observer has its limitations as to what information he/she can catch and how accurately it can be done. Think about fast events occurring often and/or tasks not easy to watch because of the layout. Human observations are therefore often limited to ticks on a pre-formated check sheet.

As human observers are high cost (compared to newer technology), they are used in limited number, during limited time and usually with sampling techniques.

Appropriate technology can gather many data for a single event: temperature, motions, duration, acceleration, applied force and what ever embedded sensors are designed for. These devices capture everything of each event, not only samples.

The cost per data point is obviously in favor of technology, not only because of quantity of data but also its quality (read accuracy). In near future the cost of these technologies will further drop, making automatic data collection available almost for free.

The mass of data captured allows using big data techniques, even so data scientists may smile at the “big” in this specific case. Nevertheless, with more smart objects and sensors everywhere (Internet of Things, Smart factories, etc.), the flood of data will grow really big and allow process mining, correlation search on a huge sets of parameters and more.

I am convinced that in near future, most of Value Stream Maps will be generated automatically and updated real time by such kind of devices/data sets, with ability to zoom in on details or zoom out for a broader view at will, and more.

The same systems will be able to pre-analyze and dynamically spot bottlenecks and sub-optimized parts in the process, make suggestions for improvements if not corrections by themselves.

  • Artificial intelligence with machine learning ability will suggest improvements based on scenarios stored in their literally infinite memory or on their predictions about potential problems.
  • The Internet of Things (IoT) will be made by objects communicating and interacting with each other.

What is likely to come are intelligent monitoring systems for any process, that build and maintain themselves, hence smart factories.

So, when Lean goes digital to that point, what will be left to humans?

This is a topic for a next post and an opportunity for you to give your opinion in a comment.

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You may also be interested by my series about What jobs in the factory of the future?

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Technologies alone will not regain competitive advantage

Smart factories, high level of automation, robots, cobots and industry 4.0 concepts will not be enough to regain competitive advantage for Western European* companies. The reason is very simple, these technologies will be available to everyone and there is no real barrier to entry. These technologies won’t be very expensive and the ease of mastering them is their core claim.

Christian HOHMANNThus, everything else being equal, technologies alone won’t change contestants’ actual competitive advantages once they all acquired and mastered them.

Will the innovations therefore be useless? Surely not, they’ll enhance tools and processes and open new perspectives, but technologies alone won’t regain competitive advantage.

* This post is written from a French perspective which may be valid for Western Europe and United States as well

What can differentiate a competitor from his peers is the attractiveness of its offers, as it already did and still does before the next techno revolution. Attractive offers are based on:

  • Innovative products and services
  • High level of customization
  • High perceived value
  • Fast deliveries

These features are responses to common customers’ expectations like:

  • the fascination for novelty, originality
  • the desire to distinguish from the mass with something custom made
  • the ratio from perceived quality and value to its cost
  • the instant satisfaction of desires

In other words, it is not the means – read technologies – used to please customers that determine performance but the way of using them. The keys to competitive edge do not relate to machinery, automation nor sophisticated IT alone but to smarter use of them.

Hints for future successes, with a bit of high-tech

Analyzing voice of customers, soon greatly improved with big data.

Big data brings all kind of heterogeneous information together, analyze them and refine customers’ preferences better than traditional inquiries could achieve. For a simple reason: inquiries are based on limited questions with limited answer options and too often biased. Respondent keep much of their expectations and desires unspoken, implicit and thus hidden. Big data allows gathering small pieces of information in tweets, facebook posts, online orders, blog comments, etc. and finding correlations that allow to refine the offering to customers’ unspoken and maybe unconscious longings.


Innovation is not only responding to customers’ whishes but surprise them with something new, different. Here TRIZ may help. TRIZ is one of these powerful methods and tools that didn’t really make it into the light so far.

TRIZ is a problem solving method based on logic and data, not intuition, which accelerates the project team’s ability to solve these problems creatively. TRIZ also provides repeatability, predictability, and reliability due to its structure and algorithmic approach. “TRIZ” is the (Russian) acronym for the “Theory of Inventive Problem Solving.” G.S. Altshuller and his colleagues in the former U.S.S.R. developed the method between 1946 and 1985. TRIZ is an international science of creativity that relies on the study of the patterns of problems and solutions, not on the spontaneous and intuitive creativity of individuals or groups. More than three million patents have been analyzed to discover the patterns that predict breakthrough solutions to problems.


The TRIZ pioneers used a big data approach in time big data as technology and tool did not exist. Now that big data is growing mature, methods like TRIZ and QFD (Quality Function Deployment) could be boosted and jointly used for invention.


Speed, both for launching often new products/services and deliver them fast to market, is a key success factor. Additive manufacturing (3D printing) may be a technical response, but when it comes to speed Lean can help a lot.

Lean is not only about reducing lead time, but also avoiding loops (e.g. rework), unnecessary dwelling (e.g. waiting for next process step or waiting for inventory queue to flush). Lean also cares about doing things right first time, improving in-process quality and doing what is really necessary to deliver value and thus stop over processing and needless tasks. While all this reduces lead time, it reduces also costs and improves quality.


Profitability means that all the previous should not be done at the expense of company’s profit. Profit making is essential for company’s sustainability. What’s the use of a one-shot success?


3D printing as additive manufacturing

Every day sees new surprising applications of 3D printing and most of them are forerunners of disruptions, larger applications, breakthroughs, etc.

The fast maturation of 3D printing techniques and their proven abilities make them stand as symbol of the factory of the future.

In this near future additive manufacturing with 3D printing should tackle the problem of “High-Mix, Low-Volume” and help to bring new products faster to market.

Additive manufacturing is building objects layer by layer by 3D-printing layers or extruding material, e.g. metal or concrete. As the name tells, additive manufacturing adds material, compared to “subtractive” techniques where material is taken away, by machining for example.

This article is inspired by McKinsey Quartely’s article “3-D printing takes shape” (2014)

3D printing appears ready to emerge from its niche status and become a viable alternative to conventional manufacturing processes in an increasing number of applications.

Adding material with 3D printing techniques to create an object carries many advantages:

  • Less wasted material as when subtracted from a bigger piece, e.g. by lathing, milling, etc.
  • Presumably cheaper in regard of tooling, molds or die costs
  • Faster, again because no special tools or molds must be created first and because it is possible to “create complex shapes and structures that weren’t feasible before”.

Complex shapes means primarily geometry but means also full functional moving parts that can be encased one in another and printed at once. In traditional manufacturing that may have required at least producing the two parts and assemble them, thus multiplying time and cost.

In comparison to additive manufacturing, subtractive manufacturing is about cutting and grinding, taking away material, while additive manufacturing is building to shape, adding layers over layers. Layers can be of different materials, allowing composite, sandwiched structures using the just necessary amount of material.

3D printed items costs compared to traditional manufacturing ways seem to favor additive. Cost in one of the key success factors, among others.

Speed, one of the key success factors

Being first on the market with a new offer is an opportunity to yield earnings and make profit without competition. Being fast often (increasingly?) means making profit as long as it is possible, before the next fashionable product or disruptive technology shows up.

To get faster a product to market, additive manufacturing vith 3D printers allows to cut or eliminate time:

  • for prototyping
  • for tooling
  • for production

The ability to make prototypes without tooling lets companies quickly test multiple configurations to determine customer preferences, thus reducing product-launch risk and time to market.

Letting customers participate in early engineering choices and giving their input is called crowdsourcing.

High-Mix, Low-Volume

For items that can be 3D printed, additive manufacturing may be an elegant solution to the High-Mix, Low-Volume problem. In theory, batch size of one is no problem for 3D printer as there is no such a thing as tool changeover (provided the material is the same or automatically switched/fed), no adjustments, no preproduction runs nor sample tests before unleashing the production.

Many benefits of 3-D printing could cut the cost of market entry for new players: for example, the use of the technology to lower tooling costs makes it cheaper to begin manufacturing, even at low volumes, or to serve niche segments.

More to come on this subject!

Robots won’t take your job, investors will

In a previous post I outlined cobots utopia where collaborative robots extend the worker’s abilities and compensate some human weaknesses. In this perspective cobots could keep aging workers on the job and help to improve industrial jobs’ image, often quoted Dirty, Dangerous and Difficult.

The cooperation between robots and workers could increase manpower productivity, hence reducing the cost gap with low-cost countries.

How likely is this to happen?

Let’s put it bluntly: why should an investor invest to compensate the human weaknesses with high-tech, knowing that in the system made of the association of robots and humans, the latter will still be the limiting factor?

Everything else being equal, why should an investor choose the precarious option of backing-up expensive workforce with cobots when a cheaper basic workforce is available somewhere in poorer, not-so-advanced countries?

Everything else being equal, why should an investor choose to invest in a complex combination of man-and-machine when full automation / robotics may soon be / already is (?) available?

Big Data combined with cyberphysical devices will come closer to human intelligence, allowing machines to learn from experience and predict failures, stoppage, breakdowns and act accordingly.

If investors are facing the choice between a cobot assisted human worker and a full automated process, I’m not sure many cobots will sell. What’s sure, the robot makers will sell, either robots or cobots!

Related: Cobots utopia