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Dec 27 2011

IndustryWeek survey on Continuous Improvement

Via Scoop.it – Cellular manufacturing
According to this article, the survey shows that continuous improvement separates the winners from the losers and drives financial gains.  The body of the article, however, contains no information about the survey method. We know neither how many companies responded nor the positions of the people who responded. I assume that survey questionnaires were sent to a selected group of executives, and that some among the recipients opted to answer. I am not sure what such a sample is supposed to represent.

The article says that more respondents with continuous improvement programs expect revenue and income growth >3% in 2012 than respondents without such programs. So it is about what this self-selected sample believes will happen next year. The only statement about actual results is a similar one about cash flow for this year. Based on the article, I fail to see how the survey supports the claims in the title and subtitle.
Via www.industryweek.com

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By Michel Baudin • Press clippings • 0 • Tags: Continuous improvement, Management

spc1

Dec 27 2011

Is SPC obsolete?

In the broadest sense, Statistical Process Control (SPC) is the application of statistical tools to characteristics of materials in order to achieve and maintain process capability. In this broad sense, you couldn’t say that it is obsolete, but common usage is more restrictive.

The semiconductor process engineers who apply statistical design of experiments (DOE) to the same goals don’t describe what they do as SPC. When manufacturing professionals talk about SPC, they usually mean Control Charts, Histograms, Scatter Plots, and other techniques dating back from the 1920s to World War II, and this body of knowledge in the 21st century is definitely obsolete.

Tools like Control Charts or Binomial Probability Paper have impressive theoretical foundations and are designed to work around the information technology of the 1920s. Data was recorded on paper spreadsheets, you looked up statistical parameters in books of tables, and computed with slide rules, adding machines or, in some parts of Asia, abacuses (See Figure 1).

In Control Charts, for example, using ranges instead of standard deviations was a way to simplify calculations. These clever tricks addressed issues we no longer have.

Figure 1. Information technology in the 1920s

Another consideration is the manufacturing technology for which process capability needs to be achieved. Shewhart developed control charts at Western Electric, AT&T’s manufacturing arm and the high technology of the 1920s.

The number of critical parameters and the tolerance requirements of their products have no common measure with those of their descendants in 21st century electronics.

For integrated circuits in particular, the key parameters cannot be measured until testing at the end of a process that takes weeks and hundreds of operations, and the root causes of problems are often more complex interactions between features built at multiple operations than can be understood with the tools of SPC.

In addition, the quantity of data generated is much larger than anything the SPC techniques were meant to handle. If you capture 140 parameters per chip, on 400 chips/wafer and 500 wafers/day, that is 28,000,000 measurements per day. SPC dealt with a trickle of data; in current electronics manufacturing, it comes out of a fire hose, and this is still nothing compared to the daily terabytes generated in e-commerce or internet search  (See Figure 2).

Figure 2. Data, from trickle to flood, 1920 to 2011

What about mature industries? SPC is a form of supervisory control. It is not about telling machines what to do and making sure they do it, but about checking that the output is as expected, detecting deviations or drifts, and triggering human intervention before these anomalies have a chance to damage products.

Since the 1920s, however, lower-level controls embedded in the machines have improved enough to make control charts redundant. The SPC literature recommends measurements over go/no-go checking, because measurements provide richer information, but the tables are turned once process capability is no longer the issue.

The quality problems in machining or fabrication today are generated by discrete events like tool breakage or human error, including picking wrong parts, mistyping machine settings or selecting the wrong process program. The challenge is to detect these incidents and react promptly, and, for this purpose, go/no-go checking with special-purpose gauges is faster and better than taking measurements.

In a nutshell, SPC is yesterday’s statistical technology to solve the problems of yesterday’s manufacturing. It doesn’t have the power to address the problems of today’s high technlogy, and it is unnecessary in mature industries. The reason it is not completely dead is that it has found its way into standards that customers impose on their suppliers, even when they don’t comply themselves. This is why you still see Control Charts posted on hallway walls in so many plants.

But SPC has left a legacy. In many ways,  Six Sigma is SPC 2.0. It has the same goals, with more modern tools and a different implementation approach to address the challenge of bringing statistical thinking to the shop floor.

That TV journalists describe all changes as “significant” reveals how far the vocabulary of statistics has spread; that they use it without qualifiers shows that they don’t know what it means. They might argue that levels of significance would take too long to explain in a newscast, but, if that were the concern, they could save air time by just saying “change.” In fact, they are just using the word to add weight to make the change sound more, well, significant.

In factories, the promoters of SPC, over decades, have not succeeded in getting basic statistical concepts understood in factories. Even in plants that claimed to practice “standard SPC,” I have seen technicians arbitrarily picking parts here and there in a bin and describing it as “random sampling.”

When asking why Shewhart used averages rather than individual measurements on X-bar charts, I have yet to hear anyone answer that averages follow a Bell-shaped distribution even when individual measurements don’t. I have also seen software “solutions” that checked individual measurements against control limits set for averages…

I believe the Black Belt concept in Six Sigma was intended as a solution to this problem. The idea was to give solid statistical training to 1% of the work force and let them be a resource for the remaining 99%.

The Black Belts were not expected to be statisticians at the level of academic specialists, but process engineers with enough knowledge of modern statistics to be effective in achieving process capability where it is a challenge.

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By Michel Baudin • Technology • 127 • Tags: problem-solving, Quality, Six Sigma, SPC

process plant

Dec 25 2011

Work Cells in Process Plants: Virtual or Pretend?

Via Scoop.it – Cellular manufacturing

In the latest issue of the AME’s Target magazine, Peter King explains how he has applied the cell concept in process plants, but his cells are virtual, meaning that their implementation does not involve relocating equipment.   In the case of synthetic rubber at Dupont’s plant in Louisville, KY he reports decreasing scrap and lead time by 28%, and decreasing finished goods inventory by 50%. There is no mention of improvements in Productivity, WIP and Raw Materials inventory, or Space Requirements.

While these improvements are substantial and respectable, they are  not up to cell benchmarks: reductions of 80% to 90% in lead time, inventory and defect rates, with a 30% to 50% increase in productivity, all in 25% to 30% less space. But that cannot be achieved without moving equipment…

If you can’t move the equipment, I prefer to call it managing monuments than implementing cells. Since you can’t get from managing monuments the order-of-magnitude performance boosts that you get from cells, I prefer to keep the distinction in sharp focus rather than blur it by pretending that “virtual cells” are cells.   Where cells apply, they are wonderful, but they are not a panacea. Even in discrete, mechanical manufacturing plants, there are often a few areas like, Heat Treat, Electroplating or Painting, where cells are difficult or impossible for now, and the skill of managing monuments is necessary.
Via www.ame.org

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By Michel Baudin • Press clippings • 2 • Tags: Cellular manufacturing, Lean manufacturing, Monument management

Dec 23 2011

How to achieve a lean transformation

Via Scoop.it – lean manufacturing

The Manufacturing Digital ezine devotes an entire section to Lean, and this is the latest entry. It is more about what needs to be done than how to do it. In the featured picture, the executives look like the marines on Iwojima, but they also seem about  to jump off a cliff.
Via www.manufacturingdigital.com

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By Michel Baudin • Press clippings • 0 • Tags: Lean, Lean implementation, Lean manufacturing, Manufactuting

elephant

Dec 22 2011

The Lean Body of Knowledge

Efforts at implementing Lean have become pervasive in manufacturing, branching out from the automotive industry to electronics, aerospace, and even food and cosmetics, not to mention efforts to adapt it to construction, health care, or services. As a consequence, the knowledge of Lean, proficiency in its tools, and skills in its implementation are highly marketable in many industries.

There is, however, no consensus on a body of knowledge (BOK) for education in the field, and my review of existing BOKs and university courses confirms it.  A consensus is elusive because Lean emerged as the accumulation of point solutions developed at Toyota over time, rather than as the implementation of a coherent strategy.

As Takahiro Fujimoto explains, there was no individual thinker whose theories started the company down this path. Decades later, we are left with the task of reverse-engineering underlying principles from actual plant practices. Those who have attempted it produced inconsistent results because they have gone at it like the six blind men with the elephant: their personal backgrounds, mostly in business school education, management, or even psychology allowed them to see different slivers of the Toyota system but not the whole, giving, in particular, short shrift to its engineering dimension.

In the following paragraphs, first I explain what I think the Lean BOK should be. Then I review five programs offered in the US by universities and professional societies and highlight where they differ.

My view of the Lean BOK

A well-rounded program for manufacturing professionals would provide Lean skills to all the professionals involved in designing and operating manufacturing plants. Organizations that are successful at Lean do not rely on one department to “do Lean” for everybody else. Instead, Lean is part of everybody’s job. There are basics that everybody needs to know, and then there are different subsets of skills that are useful depending on where you work in the plant.

Beyond the common background, the knowledge should be organized around functions performed by people. In this way of thinking, Visual Management, for example, would not be a stand-alone subject, because factories don’t have “visibility managers.” On the other hand, plants have assembly lines, machining or fabrication shops, shipping and receiving departments all in need of visual management. As a consequence, visual management is part of the training of professionals in assembly, machining, fabrication, logistics, quality, maintenance, etc. And each one only needs to know visual management as it is relevant to his or her position.

Over time, Lean should  migrate into the mainstream of manufacturing and industrial engineering, and lose its separate identity, both in industrial practice and in engineering and management education. This has been the fate of successful innovations in manufacturing in the past. For example, the “American system of manufacture” to which we owe interchangeable parts is now only a subject for historians. It is not the object of a standard or certification, and nobody explicitly undertakes to implement it. That is because its components — engineering drawings, tolerances, allowances, routings, special-purpose machines, etc. — have all become an integral part of how we make things. Likewise, in Japan, TQC is no longer a topic, as its most useful components have just fused into the manufacturing culture 30 years ago. This is what must happen to Lean in the next 30 years.

Lean proficiency should be built around manufacturing functions, not Lean tools. From foundation to superstructure, we see the following hierarchy — originally defined by Crispin Vincenti-Brown — and structure the body of knowledge accordingly:

  1. Manufacturing and industrial engineering of production lines is the foundation, covering every aspect of the physical transformation of materials and components into finished goods. This is about the design and operation of a production lines using different technologies and working at different paces.
  2. Logistics and production control build on top of this foundation, covering both the physical distribution and the information processing required to make materials available to production and deliver finished goods.
  3. Organization and people covers both what an implementer needs to know in order to lead the Lean transformation of an organization, and to manage it once it is underway. The first part is about Lean project and program management; the second, about the alignment of operator team structures  to the production lines, continuous improvement and skills development, and support from production control, quality assurance, maintenance, engineering, and HR.
  4. Metrics and accountability. This is about appropriate metrics for quality, cost, delivery, safety, and morale. In routine operations, this also means collecting the data needed, computing the metrics, and communicating the results in a way that provides useful feedback. On projects, this means estimating improvements. In both cases, metrics in the language of things need to be translated into the language of money for top management.

A hypothetical participant who would master all  of the above  would understand both the philosophy and the tools of Lean, their range of applicability, and their implementation methods. He or she would possess the following skills:

  1. How to read a plant, assess its performance potential, set strategic directions, and start it moving in these directions. This entails the following:
    • Characterizing the demand the plant is expected to respond to.
    • Mapping its current, ideal and future value streams and processes and detect waste.
    • Assessing its technical and human capabilities.
    • Setting strategic directions for improvement.
    • Identifying appropriate improvement projects for current conditions and skill levels.
  2. How to generate or evaluate micro-level designs for takt-driven production lines or cells in assembly, fabrication, or machining by focusing on flows of materials and movements of people. The tools include spreadsheet calculations with Yamazumi and work-combination charts, jidoka, board game simulations, full-size mockups, and software simulations as needed.
  3. How to generate or evaluate macro-level designs for plants and supply chains, involving the organization of:
    • Internal and external logistics.
    • Milk runs.
    • Water spiders.
    • Heijunka and Kanbans.
    • Lean inventory management.
    • …
  4. How to apply the right tools for quality improvement, addressing:
    • Process capability issues with statistical methods/Six Sigma
    • Early detection and resolution of problems through one-piece flow and systematic problem-solving.
    • Human-error prevention through poka-yoke/mistake-proofing.
    • Planned responses to common problems through Change Point Management (CPM), embedded tests and other tools of JKK.
  5. How to organize people to execute and support takt-driven production, and in particular:
    • Set up a systems of small teams, team and group leaders, to carry out daily production as well as continuous improvement activities.
    • Set up a Lean daily management system with performance boards and management follow-up routines.
    • Generate and maintain a system of posted standard work instructions.
    • Apply Training-Within-Industry (TWI).
    • Set up and dimension appropriately a support structure for logistics/production control, maintenance, quality assurance, engineering, human resources, supply chain management and customer service.
  6. How to manage the Lean transformation of a plant from pilot projects to full deployment.
  7. How to select and deploy relevant metrics to monitor manufacturing performance and estimate the impact of improvement projects both in the language of things and in the language of money.

This BOK is dauntingly large, and new wrinkles are added daily.  Fortunately, you don’t need to master all of it in order to be effective.

Review of existing BOKs

I took a look at a few of the existing training programs offered by various institution, for the purpose of identifying the underlying BOKs. Table 1 shows the list. My comments follow.

Table 1: A few Lean training programs in the US
University of Kentucky Lean Systems Certification
University of Michigan Lean Manufacturing Training
SME Lean Certification
University of Dayton Get Lean
Auburn University Lean Certificate Series

The University of Kentucky program

The University of Kentucky’s program includes Core Courses — a train-the-trainer program — and Specialty Courses — for professionals outside of production operations. Some but not all the specialty courses are targeted at functions within the organization but others are about tools. Just the core courses add up to three one-week training sessions, while each specialty course is typically a one- or two-day workshop.

From the University’s web site, however, I cannot tell when, or if, participants ever learn how to design a machining cell, or an assembly line, or how to reduce setup times. In the core courses, it’s great to talk about mindsets, culture, and transformational leadership, but where is the engineering red meat?

The specialty courses address planning, improvement methods, logistics, supplier development, and other unquestionably important topics, but offer nothing about manufacturing or industrial engineering.

The University of Michigan program

The University of Michigan has a program of two one-week sessions with three-week gaps between sessions. This program does cover cell design, materials handling and factory layout,  and even rapid plant assessment, that are certainly relevant engineering topics, but I didn’t see anything about the design of lines that are not cells, autonomation, or the Lean approach to quality. There is a module about integrating Six Sigma with Lean, but there is a lot to Lean Quality that has nothing to do with Six Sigma, such as mistake-proofing.

There is also some coverage of logistics, organization, and accountability, but not as much as in the University of Kentucky program.

The SME

The SME has published a document entitled Lean Certification Body of Knowledge, in which the major headers are:

  1. Cultural Enablers
  2. Continuous Process Improvement
  3. Consistent Lean Enterprise Culture
  4. Business Results

Organization and People issues are treated in 1. and 3. The first two line items under Cultural Enablers are “Respect for the individual” and “Humility.” I am not sure how you can teach this or test for it, particularly humility. It is followed by techniques that have to do with implementation. The topics  in 3. have more to do with management once Lean is started, but it doesn’t say it in so many words.

All Engineering and Logistics is lumped under Continuous Improvement, which is clearly a misnomer because many of the Lean techniques in these areas are radical innovations that have nothing to do with continuous improvement. Inside this section, the choice of topics and their structure is surprising. For example, the only method of data collection considered is the check sheet, and it ranks as high in the hierarchy of topics as poka-yoke or one-piece flow.

As the name suggests, Business Results covers metrics and accountability.

The weight of the different areas varies with the level of certification. At the Bronze level, for example, Continuous Improvement counts for 60%; at the Gold level, only for 15%.

The University of Dayton

I have ties with this institution from having taught courses there  for many years, and I am still listed among their Experts. But I am not involved with their GetLean Certification program. It is an 8 to 10-day curriculum with a core of 5 days on the following topics:

  • Introduction to the Lean Tools
  • How to Develop New Metrics in a Lean Culture
  • Human Error Reduction: Root Cause Analysis
  • Fundamentals of Negotiation
  • Strengthening Your Business Services using LEAN Tools
  • Managing Projects in a LEAN or Six Sigma Environment
  • Managing an Efficient Supply Chain

The choice of topics may seem odd. For example, you might wonder what Fundamentals of Negotiation is doing in a Lean training program, or why Root Cause Analysis only appears under Human Error Reduction. What about root cause analysis of process capability problems?

Auburn University

Of all the Lean programs reviewed here, Auburn University’s probably has the deepest roots, through the influence of JT Black, whose passion for Lean goes back to the late 1970s.

The list of subjects they cover is as follows:

  • Principles of Lean
  • Value Stream Mapping
  • 5s
  • Total Productive Maintenance (TPM)
  • Quick Changeover
  • Pull / Kanban / Cellular Flow
  • Sustaining Continuous Improvement
  • Lean Office
  • Lean Accounting
  • Rapid Improvement Event
  • Problem Solving

If anything, this program has too much of the red meat that is lacking in some of the others. It could, without harm, emphasize Logistics and Management a bit more.

Conclusion: no consensus

Even when considering the programs solely on the basis of their published syllabi, it is clear that their graduates will have received vastly different instruction, and that the designers of these programs have no common view of what the Lean Body of Knowledge is.

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By Michel Baudin • Management • 12 • Tags: Lean, Lean manufacturing, Management, Strategy, Takahiro Fujimoto

Dec 21 2011

Cellular manufacturing at Loral Space

Via Scoop.it – lean manufacturing
Loral uses cells to improve productivity in making satellites.
Via www.industryweek.com

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By Michel Baudin • Press clippings • 0 • Tags: Cellular manufacturing, Lean manufacturing

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