Tuesday, August 29, 2017

Operation Analysis - Methods Efficiency Engineering

Operation Analysis and Method Study are the two popular methods in Process Industrial Engineering. Japanese industrial engineering improvements brought out new techniques like SMED, Poka Yoke, 5S and Seven Waste model etc.

The term 'Operations Analysis" was used by James Anderson in his book on Industrial Engineering published in 1928. He said operation analysis is the short form for long form "Job Standardization, Motion Study and Time Study." H.B. Maynard has authored a full book on operation analysis. The job standardization implies what Taylor did with machine tools before he undertook study of operator's activities and movements.

The First Step

The first step in the study of any process/job is to make a thorough analysis by resolving it into its component parts or elements. Each part or element may then be considered separately, and the study of the process thus becomes a series of fairly simple problems.

A process consists of operations. In process analysis, each operation is examined to rationalize it for doing it as well as doing it at that step in the sequence of operations.  Eliminate, combine, and rearrange (ECR) analysis is done for each operation of the process. In a way, it is an examination of the division of a process into operations to improve the efficiency of the process.

During primary analysis of an operation, the operation is broken down into such general factors as material, inspection requirements, equipment & tools, man  and working conditions. Each one of these factors is then examined minutely and critically in order to discover possibilities for improvement. This kind of analytical work of the operation is covered by the term " operation analysis."

For examining the factors that go into an operation, more detailed methods are available. Motion study, for example,  is 'focused on the method of the operator.

Approach to Operation Analysis

To conduct analysis work successfully, a distinctive mental attitude must be developed. .  In order to improve an operation, it must be approached with the idea that it can be improved. Otherwise, progress is not made in the improvement effort. During the training for operation analysis, number of examples of operation analysis and consequent improvement of the operations have to be given to develop favorable attitude in operation analysts and its team members.

If a job has previously been carefully studied, the best method may conceivably have been devised, and no further improvement may be possible, immediately. Experience has shown, however, that there are few established methods which cannot be improved at a later point in time. In, this connection, the history of a certain bench operation furnishes an excellent and by no means uncommon illustration of this point (Maynard). The job originally was done on daywork, and past production records showed that the time taken per part was 0.0140 hour, or slightly less than 1 minute. The job was time-studied and put on an incentive basis with an allowance of 0.0082 hour. The operator worked made a fair bonus on this job, and the feeling existed for some tune that the proper method was being followed.

After the operation had been set up for 6 months, however, a suggestion for improvement was advanced say by the foreman. The suggestion was not based upon systematic analysis but rather was the result of inspiration. The suggestion was put into effect;  the job was restudied, an allowance of 0.0062 hour was set. This last method was followed for 6 months more, when another suggestion, also of the inspirational type, was advanced. It was adopted, and a new time value of 0.0044 hour was established.

The job was a prominent one, and the improvements attracted considerable attention. The job was selected for detailed motion study. A completely new method was devised which followed the principles of correct motion practices. The new method was time-studied and standard time of 0.0013 hour was set.

The operation was thus improved to an extent where the time required was only approximately one-eleventh of that taken at first on the old daywork basis.   An improvement of such great magnitude justifies the statement that the latest method is a very good method; but in view of the past history of the job, it would be unwise to say that the best method has been attained.

As the result of many similar experiences, methods engineers are using the terms  "the best method yet devised"  implying recognition of the fact that further improvement may be possible (Even Gilbreth stressed this point). Carrying this thought to a logical conclusion, the .best method of doing an operation from a labor-economy standpoint is reached only when the man-machine time required has been reduced to zero. Until this point has been reached, further improvement is always possible.

This example  furnishes a foundation for the approach to operation analysis. If it is clearly recognized, it insures an open mind. Such mental obstacles as "it won't work' "it can't be done" and "it was tried before and didn't work"  are cleared away at the outset. Lack of success in improving any job is not interpreted to mean that the job cannot be improved, but rather that no way of improving it has yet been discovered. There is a vast difference in the two interpretations. The first induces contentment with things as they are and leads to stagnation; the second inspires further attacks from different angles and leads to progress.

The Questioning Attitude.

An open mind paves the way for successful analytical work, but it is not sufficient in itself. One can be open-minded in the passive sense of being receptive to suggestions, but this will not lead to accomplishment. The analyst must take the initiative in originating suggestions himself if he wishes to get results.

Other things being equal, the greatest amount of originality, or what passes for originality in a world where it is often said that there is nothing new, is evinced by those who have an inquiring turn of mind. The man who constantly asks questions and takes nothing for granted is often a disturbance to the contentment of those who are willing to accept things as they are, but he is the one who originates new things. Improvements come from first examining what is with an open mind and then inquiring into what might be.

This point should be clearly understood, and what is known as the " questioning attitude" should conscientiously be developed. In making an investigation of a job, nothing should be taken for granted, and everything should be questioned. Then the answers should be determined on the basis of facts, and the influence of emotions, likes and dislikes, or preconceived prejudices should be guarded against.

One who is successful in bringing about improvements in operating methods has few deep-seated convictions. He accepts little or nothing as being right because it exists. Instead, he asks questions and gathers answers which he evaluates in the light of his knowledge and experience. He questions methods, tools, and layouts. He investigates all phases of every job he studies, in so far, at least, as he has time. He even asks questions when the answers appear obvious, if he thinks he can bring out something by so doing.

The questions asked take the general form of "what," "why," "how," "who," "where," and "when. " What is the operation? Why is it performed? How is it done? Who does it? Where is it done? When is it done in relation to other operations? These questions, in one form or another, should be asked about every factor connected with the job being analyzed. Typical questions that arise during the study of industrial operations are as follows:

If more than one operator is working on the same job, are all operators using the same method? If not, why not? Is the operator comfortable? Sitting down as much as possible? Has the stool or chair being used a comfortable back and a seat that is wide enough? Is the lighting good? Is the temperature of the work station right? Are there no drafts? Are there arm-rests for the operator? If the operation can be done either seated or standing, is the height of the chair such that the elbows of the operator are the same distance from the floor in either case?

Can a fixture be used? Are the position and height of the fixture correct? Is the fixture the best available? Is the fixture designed in accordance with the principles of motion economy? Would a fixture holding more than one piece be better than one holding a single piece? Can the same fixture be used for more than one operation? Can a clamp, a vise, or a fixture be substituted for the human hand for holding? Are semiautomatic tools such as ratchet or power-driven wrenches or screw drivers applicable?

Is the operator using both hands all the time? If so, are the operations symmetrical? Do the hands move simultaneously in opposite directions? Can two pieces be handled at one time to better advantage than one? Can a foot device be arranged so that an operation now performed by hand can be done by foot?

Are raw materials properly placed? Are there racks for pans of material and containers for smaller parts? Can the parts be secured without searching and selecting? Are the most frequently used parts placed in the most convenient location? Are the handling methods and equipment satisfactory? Would a roller or a belt conveyer facilitate handling? Can the parts be placed aside by means of a chute?

Is the design of the apparatus the best from the viewpoint of manufacturing economy? Can the design be changed to facilitate machining or assembly without affecting the quality of the apparatus? Are tools designed so as to insure minimum manipulation time? Can eccentric clamps or ejectors be used?

Is the job on the proper machine? Are the correct feeds and speeds being used? Are the specified tolerances correct for the use to which the part is to be put? Is the material the most economical for the job? Can the operator run more than one machine or perform another operation while the machine is making a cut? Would a bench of special design be bettor than a standard bench? Is the work area properly laid out?

This list of questions could be extended almost indefinitely, but enough have been given to illustrate the sort of questions that should be asked during a methods efficiency study. The importance of asking such questions is paramount. The chief difference between a successful analyst and one who seldom accomplishes
much is that the former has developed the questioning attitude to a high degree. The latter may be capable of making the same improvements as the former, but they do not occur to him as possibilities because he accepts things as they are instead of questioning them.

Operation Analysis Need Not Be Confined to Methods Engineers. Although the questioning attitude is developed by the methods engineer as an aid to thorough analysis, it need not be and should not be solely his property. The other shop supervisors will find it equally useful for attacking their particular problems and finding solutions for them. If they focus it on operating methods, they will be able to make many improvements in the course of their daily work. Thus, methods-improvement work will progress more rapidly than it would if it were left entirely to the methods engineer.

If a plant is small and has insufficient activity to justify employing anyone in the capacity of methods engineer, it will be particularly desirable for all members of the supervisory force to develop the questioning attitude. It is extremely easy to view things without seeing them when they are supposedly familiar. Those most familiar with the work are the least likely to see opportunities for improvement, unless they consciously try to remain as aware of their surroundings as they would be were they new to the plant. Where the supervisory group does not change often, the cultivation of the questioning attitude is almost essential to progress.

Questions should not be asked at random, although this would be better than asking no questions at all. Rather, it is better to proceed systematically, questioning points in the order in which they should be acted upon. It would be unwise, for example, to question the tools, setup, and method used on a certain job before the purpose of the operation was considered. Better tools might be devised, and the method might be changed ; but if it were later found upon examination of the purpose of the operation that it need not be done at all, the time and money spent on tool and methods changes would be wasted.

The systematic job analysis will be discussed in this knol book in sufficient detail to give a thorough understanding.

Making Suggestions for Improvement. 

When a job is examined in all its details with an open mind and when all factors that are related to it are questioned, possibilities for improvement are almost certain to be uncovered if the job has not been studied in this way before. The action that is taken upon the possibilities will depend upon the position of the one who uncovers them. If he has the authority to take action and approve expenditures, he will undoubtedly go ahead and make the improvements without further preliminaries. If, however, he does not have that authority, he must present his ideas in the form of suggestions to the one who does.

In the first place, the true worth of each suggestion should be carefully evaluated before it is offered. If he establishes a reputation for offering only suggestions of real merit, one will find it easier to secure an attentive hearing than if he is continually advancing suggestions that have to be examined to separate the good from the impractical.

The quickest way to prove the merit of any suggestion is to make or obtain estimates of the cost of adopting it and of the total yearly saving it may be expected to effect. These two figures will show just how much must be spent and how long it will be before the expenditure will be returned. If a suggestion costs $1,000 to adopt and will save $100 per year, it is not worth presenting unless there are unusual circumstances. If, on the other hand, the expenditure will be returned within a reasonable length of time, the suggestion is worthy of careful consideration.

When it has been definitely decided that the suggestion is sound and valuable, it should be presented to the proper authorities for approval. Here, again, estimates of expenditure and return will prove valuable. The statement that much time will be saved or even that a saving of 0.0050 hour per piece can be made is not likely to mean so much as figures showing a saving of a certain number of dollars per year. A complete presentation which includes cost and savings totals will be appreciated, for if they are not furnished, they must be requested anyway, and this will only postpone final action.

An example of a good presentation of a labor-saving idea is as follows :

Works Manager:

By analyzing the cork-tube winding operation in the Cork Department, it has been found that one-third of the winder's time is spent in doing work requiring a high degree of skill and the remaining two-thirds in doing work that could be satisfactorily performed by unskilled labor.

The time consumed by the portion of the cycle that requires high skill is almost exactly one-half of that required for the balance. Therefore, it will be entirely feasible to place four winding machines in a group, using one skilled man with two unskilled helpers to run them. In this manner, the average production of three skilled workers running three machines will be obtained at a greatly reduced cost.

Under the proposed setup, the skilled worker will apply the cork to the cloth core which has been set up by one helper and will then move to another machine which the other helper has set up. Each helper will tie the ends of a finished cork-covered tube, will remove the tube, and will set up another while the skilled man is busy at other machines.

The skilled man receives 60 cents per hour and the unskilled men 40 cents per hour each. The labor cost per tube will therefore be approximately 0.76 cent as compared with the present cost of 1 cent each.

On the basis of present activities, this will amount to a yearly saving of $2,361.55. There will be a certain amount of idle machine time under the proposed arrangement; but since we have more machine equipment than we require for our present volume of business, this need not be considered.

This matter has been discussed with the foreman,  and he believes that the arrangement will work satisfactorily. In order to proceed with the proposed change, it will be necessary to relocate 12 machines.  Maintenance Department estimates that this can be done for a cost of $480.

In view of the savings that can be made, the suggestion is recommended for acceptance by you


In this report, enough details are given to explain the general nature of the suggestion. The total yearly saving of $2,361.55 is shown, as also are the cost of adopting the suggestion and the source of the estimate. The fact that the suggestion meets with the approval of the foreman of the department, always a most important point, is also clearly stated. As a result, all questions that are likely to arise in the mind of the manager are answered in advance, and there is a good likelihood that he will give immediate approval.

Occasionally, ideas occur which appear to possess advantages to the originator other than those which can be measured in dollars and cents. In presenting suggestions of this nature, advantages and disadvantages should be presented in tabulated form, so that a decision can be quickly made.

Source: Maynard's Operation Analysis

Full Knol Book - Method Study: Methods Efficiency Engineering - Knol Book
Next Article on the Topic - Scope and Limitations of Methods Efficiency Engineering

Process analysis is an examination of the division of a process into operations to improve the efficiency of the process. Process analysis examines the sequence of steps specified to convert inputs into outputs.

Process analysis now is extended to analyzing the process in other dimensions.

Journal of Intelligent Manufacturing
October 2006, Volume 17, Issue 5, pp 571-583
Evaluation of techniques for manufacturing process analysis
J. C. Hernandez-Matias, A. Vizan, A. Hidalgo, J. Rios

Updated 30 July 2017,  28 June 2015
First posted 16 Feb 2014

Sunday, August 27, 2017

TRIZ - Creative Thinking for Inventing and Innovating

New Books and Articles on TRIZ
2016 to

Systematic Innovation Toolkit
March 25, 2016


40 Inventive principles of TRIZ

Described in Part 2-3 of the Book  The Innovation Algorithm

Also See

40 Principles: TRIZ Keys to Innovation

Genrich Altshuller, Lev Shulyak, Steven Rodman
Technical Innovation Center, Inc., 2002 - 135 pages

The book has one page for each principle with pictures illustrating the explanation of the principle.

Principle 1: Segmentation:

Principle 2: Taking out or Extraction:

Principle 3: Local quality: development; local anaesthesia.

Principle 4: Asymmetry:

Principle 5: Merging, Consolidation or combining:

Principle 6: Universality:

Principle 7: Nested doll:

Principle 8: Anti-weight:

Principle 9: Preliminary anti-action:

Principle 10: Preliminary action:

Principle 11: Beforehand cushioning:

Principle 12: Equipotentiality:

Principle 13: The other way round:

Principle 14: Spheroidality – Curvature:

Principle 15: Dynamics:

Principle 16 : Partial or Excessive actions:

Principle 17: Another dimension:

Principle 18: Mechanical vibration:

Principle 19: Periodic action:

Principle 20: Continuity of useful action:

Principle 21: Skipping or Rushing Through:

Principle 22 : Blessing in disguise - Harm into benefit:

Principle 23: Feedback:

Principle 24: Intermediary/Mediator:

Principle 25: Self-Service:

Principle 26: Copying:

Principle 27: Cheap short-living objects:

Principle 28: Mechanics substitution:

Principle 29: Pneumatics and hydraulics:

Principle 30: Flexible shells and thin films:

Principle 31: Porous materials:

Principle 32: Color changes:

Principle 33: Homogeneity:

Principle 34: Rejecting, Discarding – Recovering, Regeneration:

Principle 35: Parameter Changes:

Principle 36 : Phase transitions:

Principle 37: Thermal expansion:

Principle 38 : Accelerated oxidation:

Principle 39 : Inert atmosphere:

Principle 40: Composite materials:

40 Principles - Pdf List

Examples of 40 principles - from automotive sector



TRIZ: Systematic Innovation in Manufacturing

Yeoh Teong San, Yeoh Tay Jin, Song Chi Li
Firstfruits Publishing, 2009 - Engineering - 180 pages

The Ideal Result: What It Is and How to Achieve It

Jack Hipple
Springer Science & Business Media, 26-Jun-2012 -  208 pages

The Ideal Final Result introduces the TRIZ Inventive Problem Solving Process in a way that allows readers to make immediate use of its most basic concepts. The Ideal Final Result reviews the basics of this left brained, but at the same time, very creative process for problem solving that uses a basic algorithm developed through the study of millions of patents. As opposed to psychologically based tools relying on the generation of hundreds of ideas to be sorted through to find the few of value, TRIZ rigorously defines the problem and assists the problem owner in identifying the existing inventive principles that are already known to solve that class of problems. This book reviews the most basic of the TRIZ algorithm tools and provides templates for readers to use in analyzing their difficult problems and provides a mental framework for their solution. It also describes TRIZ techniques for basic strategic planning in a business sense.

TRIZ for Engineers: Enabling Inventive Problem Solving

Karen Gadd
John Wiley & Sons, 11-Feb-2011 - 504 pages

TRIZ is a brilliant toolkit for nurturing engineering creativity and innovation. This accessible, colourful and practical guide has been developed from problem-solving workshops run by Oxford Creativity, one of the world's top TRIZ training organizations started by Gadd in 1998. Gadd has successfully introduced TRIZ to many major organisations such as Airbus, Sellafield Sites, Saint-Gobain, DCA, Doosan Babcock, Kraft, Qinetiq, Trelleborg, Rolls Royce and BAE Systems, working on diverse major projects including next generation submarines, chocolate packaging, nuclear clean-up, sustainability and cost reduction.

Engineering companies are increasingly recognising and acting upon the need to encourage successful, practical and systematic innovation at every stage of the engineering process including product development and design. TRIZ enables greater clarity of thought and taps into the creativity innate in all of us, transforming random, ineffective brainstorming into targeted, audited, creative sessions focussed on the problem at hand and unlocking the engineers' knowledge and genius to identify all the relevant solutions.

For good design engineers and technical directors across all industries, as well as students of engineering, entrepreneurship and innovation, TRIZ for Engineers will help unlock and realise the potential of TRIZ. The individual tools are straightforward, the problem-solving process is systematic and repeatable, and the results will speak for themselves.
This highly innovative book:

Satisfies the need for concise, clearly presented information together with practical advice on TRIZ and problem solving algorithms
Employs explanatory techniques, processes and examples that have been used to train thousands of engineers to use TRIZ successfully
Contains real, relevant and recent case studies from major blue chip companies
Is illustrated throughout with specially commissioned full-colour cartoons that illustrate the various concepts and techniques and bring the theory to life
Turns good engineers into great engineers.

TRIZ - Systematic Innovation in Business & Management

Yeoh Teong San
First Fruits Sdn. Bhd., 01-Oct-2014 - Business & Economics - 238 pages

TRIZ (Theory of Inventive Problem Solving) is a powerful methodology which is able to improve a company's top-line and bottom-line. The top-line refers to a company's gross sales or revenues, whereas the bottom-line is a company's net earnings or net profits. The uniqueness of TRIZ is its ability to provide a structured and systematic approach, coupled with a suite of tools to enhance both top-line and bottom-line results. TRIZ can be used for creating new products to generate sales or making processes more efficient and effective to reduce operating costs and expenses.

TRIZ also enhances management capabilities by transforming a good manager to a great manager by acquiring tools to recognize contradictions when they arise and solve them without compromise.

In summary, TRIZ is a philosophy, process, and suite of tools. A total of 11 TRIZ tools (Function Analysis, Cause & Effect Chain Analysis, Perception Mapping, Ideality, S-curve, Trends of Engineering System Evolution, Trimming, Feature Transfer, Function Oriented Search, 9-Windows, and Engineering Contradiction) are discussed in detail.

Numerous examples and case studies are used to illustrate TRIZ applications in accelerating the ability to predict product, process, and service trends; identify unique value propositions for new products or services; circumvent patents of competitors; and solve age-old or chronic problems in both business and management fields.

Innovation Management System - Presentation - Simon Tong
Hong Kong Society for Quality

Updated on  28 August 2017,  17 February 2017,  22 October 2016

Saturday, August 26, 2017

Productivity Science - Some Hypothesis like Statements

"When large companies get Agile right, the results can be stunning. Productivity can improve by a factor of three. Employee engagement, measured in quantitative surveys, increases dramatically too. New product features can be released within weeks or months rather than quarters or years. Rates of innovation rise, while the number of defects and do-overs declines. In the first year after going Agile, one bank’s development team increased the value delivered per dollar spent by 50%, simultaneously cutting development time in half and improving employee engagement by one-third."

Five Secrets to Scaling Up Agile
FEBRUARY 19, 2016 by Kaj Burchardi, Peter Hildebrandt, Erik Lenhard, Jérôme Moreau, and Benjamin Rehberg

Wednesday, August 23, 2017

Six Sigma - Contribution to GE - 1997

Excerpts from  GE Annual Report 1997

The centerpiece of our dreams and aspirations "the drive for Six Sigma quality.

 “Six Sigma” is a disciplined methodology, led and taught by highly trained GE employees
called “Master Black Belts” and “Black Belts,” that focuses on moving every process that touches our
customers — every product and service — toward near-perfect quality.

Six sigma projects usually focus on improving our customers’ productivity and reducing their capital outlays,
while increasing the quality, speed and efficiency of our operations.

We didn’t invent Six Sigma — we learned it.

Motorola pioneered it and AlliedSignal successfully embraced it. The experiences of these two
companies, which they shared with us, made the launch of our initiative much simpler and faster.

GE had another huge advantage that accelerated our quality effort: we had a Company that was
open to change, hungry to learn and anxious to move quickly on a good idea.

At GE today —finding  the better way, the best idea, from whomever will share it with us, has become our central focus.

Nowhere has this learning environment, this search for the better idea, been more powerfully
demonstrated than in our drive for Six Sigma quality. Twenty-eight months ago, we became con-
vinced that Six Sigma quality could play a central role in GE’s future; but we believed, as well, that it
would take years of consistent communication, relentless emphasis and impassioned leadership
move this big Company on this bold new course.

We were wrong!
 Projections of our progress in Six Sigma, no matter how optimistic, have had to be junked every few months as gross underestimates. Six Sigma has spread like wildfire across the
Company, and it is transforming everything we do.

We had our annual Operating Managers Meeting — 500 of our senior business leaders
from around the globe — during the first week of January 1998, and it turned out to be a wonderful
snapshot of the way this learning Company — this new GE — has come to behave; and now, with Six Sigma, how it has come to work.

Today, in the uncountable number of business meetings across GE — both organized and “in-
the-hall” — the gates are open to the largest flood of innovative ideas in world business. These ideas
are generated, improved upon and shared by 350 business segments — or, as we think of them, 350
business laboratories. Today, these ideas center on spreading Six Sigma “best practices” across our
business operations.

At this particular Operating Managers Meeting, about 25 speakers, from across the Company and
around the world, excitedly described how Six Sigma is transforming the way their businesses work.

They shared what they had learned from projects such as streamlining the back room of a credit card
operation, or improving turnaround time in a jet engine overhaul shop, or “hit-rate” improvements
in commercial finance transactions. Most of the presenters focused on how their process improve-
ments were making their customers more competitive and productive:

• Medical Systems described how Six Sigma designs have produced a 10-fold increase in the life of CT scanner x-ray tubes — increasing the “uptime” of these machines and the profitability and level of patient care given by hospitals and other health care providers.

• Superabrasives — our industrial diamond business — described how Six Sigma quadrupled
its return on investment and, by improving yields, is giving it a full decadeÕs worth of capacity despite growing volume — without spending a nickel on plant and equipment capacity.

• Our railcar leasing business described a 62% reduction in turnaround time at its repair shops: an enormous productivity gain for our railroad and shipper customers and for a business that’s now two to three times faster than its nearest rival because of Six Sigma improvements. In the next phase, spread across the entire shop network, Black Belts and Green Belts, working with their teams, redesigned the overhaul process, resulting in a 50% further reduction in cycle time.

• The plastics business, through rigorous Six Sigma process work, added 300 million pounds of new capacity (equivalent to a “free plant”), saved $400 million in investment and will save another $400 million by 2000.

At our meeting, zealot after zealot shared stories of customers made more competitive, of credit
card and mortgage application processes streamlined, of inventories reduced, and of whole facto-
ries and businesses performing at levels never believed possible.

The sharing process was repeated at another level two weeks later in Paris, as 150 Master Black
Belts and Black Belts, from every GE business throughout Europe, came together to share and
learn quality technology. This learning is done in the boundaryless, transcultural language of Six
Sigma, where “CTQ’s” (critical to quality characteristics) or “DPMO’s” (defects per million oppor-
tunities) or “SPC” (statistical process control) have exactly the same meaning at every GE operation
from Tokyo to Delhi and from Budapest to Cleveland and Shanghai.

The meeting stories are anecdotal; big companies can make great presentations and impressive
charts. But the cumulative impact on the Company’s numbers is not anecdotal, nor a product of
charts. It is the product of 276,000 people executing ... and delivering the results of Six Sigma to our
bottom line.

Operating margin, a critical measure of business efficiency and profitability, hovered around
the 10% level at GE for decades.  With Six Sigma embedding itself deeper into Company operations, GE in 1997 went through the “impossible” 15% level — approaching 16% — and we are optimistic about the upside.

Six Sigma, even at this relatively early stage, delivered more than $300 million to our 1997
operating income. In 1998, returns will more than double this operating profit impact.
Six Sigma is quickly becoming part of the genetic code of our future leadership. Six Sigma
training is now an ironclad prerequisite for promotion to any professional or managerial position
in the Company — and a requirement for any award of stock options.

Senior executive compensation is now heavily weighted toward Six Sigma commitment and suc-
cess — success now increasingly defined as “eatable” financial returns, for our customers and for us.
There are now nearly 4,000 full-time, fully trained Black Belts and Master Black Belts: Six
Sigma instructors, mentors and project leaders. There are more than 60,000 Green Belt part-time
project leaders who have completed at least one Six Sigma project.

Already, Black Belts and Master Black Belts who are finishing Six Sigma assignments have become
the most sought-after candidates for senior leadership jobs in the Company, including vice presidents and chief financial officers at some of our businesses. Hundreds have already moved upward
through the pipeline. They are true believers, speaking the language of the future, energized by
successful projects under their belts, and drawing other committed zealots upward with them.

In the early 1990s, we efined ourselves as a company of boundaryless people with a thirst for learning and a compulsion to share

Now it is Six Sigma that is  permeating much of what we do all day.

We are feverish on the subject of Six Sigma quality as it relates to products, services and people — maybe a bit unbalanced —  because we see it as the ultimate way to make real our dreams of
what this great Company could become.

Six Sigma has turned up the voltage in every GE business across the globe, energizing and
exciting all of us and moving us closer than ever to what we have always wanted to become: more than a hundred-billion-dollar global enterprise with the agility, customer focus and fire in the belly of a small company.

In our 1994 letter to you, we addressed the perennial question put to management teams, which is “how much more can be squeezed from the lemon?” We claimed, then, that there was in fact unlimited juice in this “lemon,” and that none of this had anything to do with “squeezing” at all.
We believed there was an ocean of creativity and passion and energy in GE people that had no bottom and no shores. We believed that then, and we are convinced of it today. And when we said that
there was an “infinite capacity to improve everything,” we believed that as well — viscerally — but
there was no methodology or discipline attached to that belief. There is now. It’s Six Sigma quality,
along with a culture of learning, sharing and unending excitement.


Six Sigma is based on the following basic principles.

1. Y=f(X) + ε: All outcomes and results, the dependent variable (the Y) are determined by inputs (the Xs) with some degree of uncertainty (ε).

2. To change or improve results (the Y), you have to focus on the inputs (the Xs), modify them. (In the six sigma method, values of different variables X are changed systematically and resulting output is recorded and analyzed to find the best combination of values.

3. Variation is everywhere, and it degrades consistent, good performance. Your job is to find it and minimize it!

4. You get minimum variation for a particular combination Xs for given set of X and some times by including more input variables.

5. Valid measurements and data are required foundations for consistent, breakthrough improvement.

6. Only a critical few inputs have significant effect on the output. Concentrate on the critical few. There is some effort involved in determining the set of Xs that have significant effect on the output.

Philosophy – Process inputs control the outputs and determine their level of quality.

Focus – An unending quest for improving business processes.

Methods – Known as DMAIC (define, measure, analyze, improve, and control) and DMADV (define, measure, analyze, design, verify).

Measure of Success – Ultimately reducing defects to 3.4 per one million opportunities, through iterative application of six sigma methodology to understand the process better.

Updated 24 August 2017, 3 March 2012

Tuesday, August 22, 2017

Data Analytics Period in Productivity Improvement - Productivity Engineering and Management


The wave of productivity driven by data and analytics - McKinsey senior partners

"You had the wave of lean, you had the wave of outsourcing, and now we’re seeing the wave of productivity driven by data and analytics, enabling organizations to refine the way that people work together, the way that processes perform, and the way assets are productive. If you think about an oil well, for example, you’ve got more than 300 sensors downhole that are spewing out data at the rate of about a gigabit a second, in some cases." - Bill Wiseman, McKinsey senior partner

How advanced analytics can drive productivity
Podcast August 2016
Podcast transcript

How Data Analytics Increases Productivity?

Technology and innovation drive productivity.  But transaction costs of new technology implementation are considerable.  Innovation requires capital and labor investment incurring transaction costs to build infrastructure and grow the market.

Analytics and decision science could provide the means to reduce the transaction costs and increase innovations to  improve productivity in the economy.

Analytics provide a process to monitor, measure, and benchmark performance. By integrating diverse datasets from remote monitoring (IoT), measuring, and benchmarking can be accomplished automatically and economically. Reporting by anomaly and exception could free resources and thereby reduce costs and improve productivity.

Application of analytics to monitoring energy through sensors resulted in 17% reduction in energy costs for the NJ DOT main office complex. In another application, propensity models were constructed from customer profile and behavior data to identify candidates with highest conversion rates for sending sales promotion communications. Such examples are now many, to illustrate applying analytics to reduce costs and improve operations.

Low cost cloud computing together with large, diverse, and growing datasets, from the web to internal sources, and available statistical visualization tools, have dramatically changed the cost of data analytics. The low cost of data analytics is allowing more companies to use analytics and improve the productivity.

Source: Onoly Analytics and Analytics 2 Insight - White Paper
Analytics at the Speed of Insight: Simple, Fast and Actionable Tools to Improve Productivity


Further Developments


Ops 4.0: Fueling the next 20 percent productivity rise with digital analytics
By Mercedes Goenaga, Philipp Radtke, Kevin Speicher, and Rafael Westinner
Article April 2017

Be agile, Be focused on results and Take up manageable data analytics projects

Digital transformation-driven productivity
Don't underestimate the incredible power of DX turned inward, toward enhancing internal organizational productivity.

Digital Transformation Can Resolve the Productivity Paradox
EITN MALAYSIA, April 27, 2017
By Hu Yoshida, Chief Technology Officer, Hitachi Data Systems

How digital transformation improves productivity in manufacturing
By Alex Walker and Arnd Simon, Senior Directors, Industry Services, Global Manufacturing Practice, Microsoft Corporation; Contributor: Dr. Lei Liu, Digital Advisor, Microsoft Deutschland GmbH on May 5, 2017

Increasing Chemical Industry Productivity through Digital Transformation

May 12, 2017 | Showcase
Learn how Capgemini's ChemPath SAP – Certified Business All-in-One (BAIO) solution, will help your organization streamline and synchronize the operations, while achieving greater visibility and control over your core business processes.

IoT use cases with 2 year pay back period in global auto company mentioned.

Microsoft Workplace Analytics helps managers understand worker productivity



November 2016

Smart data is the way to boost mining productivity

2 September 2016

Improving dragline productivity and increasing reliability using big data

August 2016

Mining operations produce an enormous amount of data through numerous parallel, though diverse, monitoring systems. Data mining and analytics can be a major part of a successful mining improvement process.

In this case, the goal is to find a single target variable and its value that will drive operator behaviour to operate the dragline at maximum production capacity and speed while not exceeding machine fatigue.


Production Data Analytics – To identify productivity potentials
Master Thesis - 2015
Department of Product and Production Development


Data Analytics and Continuous Productivity
September 18, 2013

July 2013

Big-data analytics as a productivity tool McKinsey Global Institute

Sectors across the economy can harness the deluge of data generated by transactions, medical and legal records, videos, and social technologies, sensors, cameras, bar codes, and transmitters embedded in the world around us. Advances in computing and analytics can transform this sea of data into insights that create operational efficiencies.

By 2020, the wider adoption of big-data analytics could increase annual GDP in retailing and manufacturing by up to $325 billion.

Additionally as much as $285 billion savings can occur in the cost of health care and government services.



MIT professor Erik Brynjolfsson discusses how companies can increase their productivity by making better use of their data.
by David Talbot  February 16, 2011

MIT professor Erik Brynjolfsson
Book Chapter: Business practices that enhance productivity along with IT investments.

Updated 23 August 2017,  16 August 2017,  10 July 2017,  30 June 2017, 22 June 2017

Industrial Engineering - Foundation of Toyota Production System

Toyota Production System or Lean Philosophy

Elimination of Waste
Low Inventory
Low Order to Delivery Period using low cycle time.

Toyota Production System - Lean Tools or Techniques

Poka Yoke
Value stream mapping to find cycle time and processing time.
TIE - Total Industrial Engineering.
TQM – Zero defects
TPM – High OEE
TPMgmt – Annual Planned Cost Reduction

Shigeo Shingo

A Study of Toyota Production System from an Industrial Engineering Viewpoint by Shigeo Shingo

Book published by Productivity Press
Components of Lean System

Shigeo Shingo said
80% of the lean system (TPS) is waste elimination that is industrial engineering,
15% - production management and
5% - kanban (sign board) communications

What is Industrial Engineering?

Industrial Engineering is eliminating Muda, Muri and Mura (Japanese explanation).

IE is developing science that explains productivity (Productivity Science development)

IE is improving technical processes  for cost reduction (Machines and Men) (Fundamental - Productivity Engineering).

IE is improving management processes of planning, organizing, resourcing, executing (accepting and releasing orders, leading, directing, communicating) and controlling (associated activity - Productivity Management).

IE is improving business processes (Augmented).

For some more details visit:  Functions of Industrial Engineering

In Preface to the Japanese Edition

Shigeo Shingo had written that management consultants were not allowed to disclose any confidential or proprietary information. Taiichi Ohno authored two books describing Toyota Production System (TPS).  That allowed Shigeo Shingo, to use the published material as the basis to explain industrial engineering principles behind TPS.

Shigeo had as his objectives in writing the book:

1. Explaining the principles of the Toyota Production System.
2. Explanation of the system of practicing these principles.
3. Description of the practical application of the methods following these principles.

Chapter 1 Introduction

Production is a network of processes and operations.
Process – transforming material into product is accomplished through a series of operations.
Process – flow of material in time and space.
Process analysis examines the flow of material or product.

In an operation a transformation occurs.
Process analysis questions whether that transformation is required.
Operation Analysis
Operation analysis examines the work performed on products by workers, machines and tools.
Process analysis, operation analysis, motion study and time study form part of methods efficiency engineering.
Process analysis and operation analysis are engineering activities specific to each branch of engineering.

Chapter 2 Improving Process

Improve process before improving individual operations.
Process is flow of material through operations.

Process Chart - Gilbreth

Processing operation
Inspection operation
Transport operation
Storage operation – Temporary, Permanent (Delay operation)

Process Improvement
Process can be improved in two ways.
The first improves the product itself through design efficiency engineering (value engineering, design for manufacture, design for assembly, and design optimization techniques).
The second improves manufacturing method through methods efficiency engineering, motion studies and production optimization and variability reduction methods.

ECR Method of Process Improvement

Eliminate the operation – sometimes it is found to be not necessary or sometimes it is due to improvement of earlier operation.
Combine operations with earlier one or latter one.
Rearrange the sequence of operations

Processing Operations Analysis

Examples in the book
Manufacturing operations can be improved by alternatives related to proper melting or forging temperatures, cutting speeds or tool selection.
Examples related to vacuum molding, plating and plastic resin drying are given in the book.
Eliminating Flashing in Castings (Die)
Flashing in die castings occurs due to escape of air.
Removing the air in mould with a vacuum pump eliminated flashing.
Removing Foam in High-Speed Plating
Spraying or showering the surface to be painted resulted in a 75% reduction.
Drying Plastic Resin
Letting the resin dry a little at a time by allowing it to float to the surface resulted in a 75% reduction of electric power consumption.

Analysis of Inspection Operations

Shingo said normal inspection is judgment inspection.
It separates good and defective items.
Rework done on defective items if possible
Informative inspection asks for process improvement.
It is like medical examination that leads to treatment.
Statistical Process Control
SPC is sampling based informative inspection.
But Shingo says even it is not sufficient to assure zero defects.
To assure zero defects we need to inspect every item but at low cost per item.
Shingo’s Suggestions
Informative Inspections

Self Inspection
Successive Inspection
Enhanced Self Inspection – Inspection enhanced with devices  - poka-yoke

Example 2.4 – Vacuum Cleaner Packing
Cleaner along with attachments and leaflets to be packed.
When a leaflet is taken from the pile,  a limit switch is operated.
When attachments are taken from the container, a limit switch is operated.
Then only, the full package is allowed to be sealed.
The purpose of inspection is prevention of the defect.
Quality can be assured when it is built in at the process and when inspection provides immediate and accurate feedback at the source to prevent the defective item to go further.
Self Inspection
It provides the most immediate feedback to the operator.
He can improve the process and also rework on the item.
Disadvantage inherent.
There is potential for lack of objectivity.
He may accept items that ought to be rejected.
Successive Inspection
The operator inspects the item for any defect in the previous operation before processing it.
Shingo says, when this was introduced defects dropped to 0.016% in Moriguchi Electric Company in television production
Inspection enhanced by Poka Yoke
Human operation and inspection can still make errors unintentionally.
Poka Yoke will take care of such errors.
Ex: Left and right covers are to be made from similar components with a hole in different places.
The press was fitted with a poka yoke which does right cover pressing only when the hole is in proper place.
Source Inspection
This is answering the question: What is the source of the defect in the process/operation?
Two types proposed.
Source Inspection – Vertical, Horizontal
Vertical source inspection traces problems back through the process flow to identify and control conditions external to the operation that affect quality.
Horizontal source inspection identifies and controls conditions within an operation that affect quality.
Poka-yoke Inspection Methods
Poka-yoke achieves 100% inspection through mechanical or physical control.
Poka-yoke can either be used as a control or a warning.
As a control it stops the process so the problem can be corrected.
As a warning, a buzzer or flashing lamp alerts the worker to a problem that is occurring.

Three types of control poka-yoke
Contact method - identify defects by whether or not contact is established between the device and some feature of the product's shape or dimension
Fixed value method - determines whether a given number of movements have been made

Motion step method - determines whether the established steps or motions of a procedure are followed

Choosing/Designing  Poka Yoke
First decide stage of inspection – Self or Successive
Second – Type of regulation
Control or warning.
Third decide Error Sensing type – Contact, fixed number or motion step

Analysis of Transport Operations

Transport within the plant is a cost that does not add value.
Hence real improvement of the process eliminates the transport function as much as possible.
This involves improving the layout of process.

Ex – 7. Transport Improvement
Tokai Iron Works – process layout -  presses, bending machines, embossing
Layout Change: Flow based layout.
A 60 cm wide belt conveyor with ten presses on either side.
WIP reduced. Production time shortened. Delays disappeared.
200% increase in productivity.
Only after opportunities for layout improvement have been exhausted should the unavoidable transport work that remains be improved through mechanization.

Eliminating - Storage Operations (Delay)

Process Delay – Permanent storage – Whole lot is waiting
Lot Delays – Temporary storage – One item is being processed. Other items in the lot waiting.
Another classification is storage on the factory floor and storage in a controlled store.
Eliminating - Storage Operations (Delay)
There are three types of accumulations between processes:

E storage - resulting from unbalanced flow between processes  (engineering)
C storage - buffer or cushion stock to avoid delay in subsequent processes due to machine breakdowns or rejects (control)
S storage - safety stock; overproduction beyond what is required for current control purposes

Eliminating E-Storage

E-storage is due to engineering/planning/design of the production-distribution  system
This can be eliminated through leveling quantities, which refers to balancing flow between high and low capacity processes and synchronization.

Leveling would mean running high-capacity machines at less than 100% capacity, in order to match flow with lower capacity machines that are already running at 100% on short interval basis.
At Toyota, the quantity to be produced is determined solely by order requirements (Takt time).

Presence of high capacity machines should not be used to justify large lot processing and resulting inventory.
Process capacity should serve customer requirements/production requirements and should not determine them
The lots especially one piece lot is processed without delay in a flow.
It is efficient production scheduling that ensures that once quantities are leveled (output is matched), inventories do not pile at any stage due to scheduling conflicts.
Synchronize the entire process flow.

Eliminating C storage - Cushion

Cushion stocks compensate for:
machine breakdowns,
defective products,
downtime for tool and die changes and
sudden changes in production scheduling.

Eliminate Cushion Storage
Prevent machine breakdowns:
Determining the cause of machine failure at the time it occurs, even if it means shutting down the line temporarily.
Total Productive Maintenance movement.

Eliminate Cushion Storage
Zero Defect Movement.
Total quality management.
Use better inspection processes:
Self Inspection.
Successive Inspection.
Enhancement to inspection through Poka Yoke
Eliminate Cushion Storage
Eliminate Lengthy setups and tool changes
Implement SMED to eliminate long set-up times and tool changes
Running smaller batch sizes to allow for quick changes in production plans

Eliminate Cushion Storage
Absorb Change in Production Plan
Running smaller batch sizes allows for quick changes in production plans without disturbing flow production to significant extent.

Eliminating Safety (S) storage

Safety stock is kept not to take care of any predicted problem but to provide additional security
It may guard against delivery delays, scheduling errors, indefinite production schedules, etc.
Ex. 10 Delivery to stores
In example 2.10 Shingo mentions a company wherein vendors supply to store and from store components are supplied to assembly line.
Shingo suggested that vendors should directly supply the day’s requirements to assembly floor and in case of any problem, components in the store can be used.
Less Need for Safety Stock Observed
That practice led to the observation that very less safety stock is needed in the store.

Shingo recommends keeping a small controlled stock that is only used when the daily or hourly scheduled delivery fails or falls behind.
In case of unexpected defects also it can be used.

The safety stock can then be replenished when the scheduled materials arrive, but the supply of materials due for the process go directly to the line, rather than normally going into storage first.
This is the essence of the just-in-time supply method.

Eliminating lot delays
While lots are processed, the entire lot, except for the one piece being processed, is in storage (is idle).
The greatest reduction in production time can be achieved when transport lot sizes are reduced to just one; the piece that was just worked on.

Using SMED (single-minute exchange of dies), set up time is decreased so large lot sizes are no longer necessary to achieve machine operating efficiencies.
SMED facilitates one item lot sizes.

Layout Improvement - Flow
Transportation changes can be accomplished through flow  layout and using gravity feed Chutes which result in shorter production cycles and decreases in transport man-hours.

Reducing Cycle Time
Generally, semi-processed parts are held between processes 80% of the time in a production cycle time.
It quantity leveling is used and synchronization of flow is created, the cycle time can be reduced by 80%.
By shifting to small lot sizes will further reduce cycle time.

TPS – Reduction of Delays or Storage
Methods of reducing production time delays (JIT) is the foundation of Toyota Production System.
It clearly brings down production cycle time and thereby offers small order to delivery time.

Process Improvements in Toyota
Mixed model small lot production was attempted in Toyota to compete with American manufacturers.
First, inefficiencies in processing operations, inspection operations and transport operations were removed.
Then storage operations were attacked and inventories eliminated.
Toyota surpassed American manufacturers.

Now TPS is promoted as Lean System

Chapter 2 End

Ch. 3 Improving Operations

Operation may be classified as follows:

Set up operations - preparation
Principal operations - performance
Margin allowances - machine breaks
Personal allowances - worker breaks

Improving Setup

Improving principal operations
The easiest way to improve principal operations is to separate the worker from the machine.
Reduce involvement of man in machine running and production.
This involves the "one worker, many process" theory.
One worker attends 5-6 machines,
The principle is that cost reduction is more important than high machine operating rates.
Machines should not unnecessarily function and produce excess inventory.
But the operable time of the machine should be high.
Whenever needed machine must be ready for production.

Machine detects problem and stops.
Workers correct the problem.
The next step is to make the machine correct the problem

Improving margin allowances

Main operations are automated by marginal activities like removing chips, feeding materials and stocking products are still done by hand by men.
They also need to be automated.
Lubrication: Consider automatic lubrication, use of oil impregnated metals etc.
Cutting oil – Consider automatic oiling or cutting without oil.
Chip removal – Consider powdering chips or automatic lubrication and chip removal.

Workshop allowances

Automate the following:
Automate feeding for materials.
Automate product storage.
By adopting the SMED system, Toyota achieved dramatic reductions in setup time and inventory cost.
Adding multi-machine handling and autonomation further increased productivity.

Summary of Remaining Chapters of the Book


Updated 22 August 2017,  9 Sep 2015
First published 9 Sep 2014

Behavioral Approach to Productivity - Behavioral Variables and Productivity

"Behavioral strategies to improve productivity"
Gary P.Latham, Larry L.Cummings, and Terence R.Mitchell,
Organizational Dynamics
Volume 9, Issue 3, Winter 1981, Pages 5-23

Hum Resour Manage. 1983 Jan-Feb;13(1):1-5.
"Behavioral science approaches to improving productivity."

Shortell SM.

We have suggested that improving the productivity of an individual or of one group of workers is not the same thing as improving the productivity of the organization overall. Further, because work units in hospitals are interdependent, attempts to improve productivity ultimately involve a reexamination of the organization's values and culture. Until this fundamental realization occurs, little can be done to improve the organization's productivity. As such, productivity is not simply a day-to-day managerial issue as a long-term leadership issue. Thus, we ought to begin mapping out productivity strategies for the long run. Some of the elements of such a strategy have been highlighted.

Aubrey C. Daniels "Performance management: The behavioral approach to productivity improvement"
Global Business and Organizational Excellence
Volume 4, Issue 3, Summer 1985, Pages 225–236

S.K. Srivastava & Kailash Chandra Barmola
SMS Varanasi,  Vol. VII, No. 1; June, 2011

Evidence-Based Productivity Improvement: A Practical Guide to the Productivity Measurement and Enhancement System (ProMES)
Robert D. Pritchard, Sallie J. Weaver, Elissa Ashwood
Routledge, 04-May-2012 - Psychology - 316 pages
This new book explains the Productivity Measurement and Enhancement system (ProMES) and how it meets the criteria for an optimal measurement and feedback system. It summarizes all the research that has been done on productivity, mentioning other measurement systems, and gives detailed information on how to implement this one in organizations. This book will be of interest to behavioral science researchers and professionals who wish to learn more about the practical methods of measuring and improving organizational productivity.


Enhancing Strategies to Improve Workplace Performance
Thesis by Francine Williams Richardson
Walden University

Nudge management: applying behavioural science to increase knowledge worker productivity
Philip Ebert and Wolfgang Freibichler
Journal of Organization Design2017  6:4
Published: 21 March 2017


Culture and Productivity - Bibliography

Seven Wastes Model

Seven Wastes - Taiichi Ohno - page 19 - Toyota Production System

   Waste                          -                   Method

Waste of overproduction - One cannot produce without a production Kanban

Waste of time on hand (waiting)  - Multiple machines to an operator, all producing as per tact time.

Waste in transportation - Machines in line or flow placed close together

Waste of processing itself - Standardized Methods

Waste of stock on hand (inventories) - JIT system - low inventory

Waste of movement (of workers) - Machine layout changes so that an operator handling multiple machines does not waste movement. Can there be control unit for all the machines at one place only?

Waste of making defective products - Problem solving approach to produce zero defects. 5 Why approach to find where the problem or defect occurred in the earliest stage. Educating and training operators by other team members and management.

Seven Waste Model is also expressed as TIMWOOD

T – Transport – Movement of material, people
I – Inventory – Stock of materials, parts, and finished items
M – Motion – movement of hands and other body parts in operating machines of hand tools
W – Waiting – Men and machines waiting for parts or instructions
O – Over production – Making more than is IMMEDIATELY required
O – Over processing – Tighter tolerances or higher grade materials than are necessary
D – Defects – Items scrapped and rework

Compare the seven waste model with flow process chart

Flow process chart recommends recording and examining 5 items.

Process -   will examine  1.Waste of processing itself,  2. Waste of overproduction

Inspection -  3. Waste of making defective products  - The inspection is only shown as a stage in flow process chart, It needs to be augmented with a record of defects or defectives found during inspection.

Transport - 4. Waste in transportation, 5. Waste of movement (of workers)

Temporary delay - 6. Waste of time on hand (waiting)

Permanent storage - 7. Waste of stock on hand (inventories)

Thus we can see, flow process charts has provided the foundation for analyzing the seven wastes proposed by Taiichi Ohno.

But subsequent persons have indicated Eighth Waste.

Wastage of physical and mental skills of people.

Alan Mogensen identfied this gap in industrial engineering theory and introduced work simplication workshops to involve operators and supervisors in productivity improvement. Subsequently, suggestions scheme became popular. Japanese managers brought more improvements and made operators given large number of suggestions and provided forums for participation.

Narayana Rao proposed Ninth waste.

9th Waste - Wastage of Machine Potential, Capability and Power - Wasting Machine's Potential Productivity

Industrial engineering has ignored wastage of potential of machines and equipment even though Taylor has advocated right from his piece rate system paper that for productivity improvement both machine and man are to be analyzed and improved.

9th Waste - Wasting Machine's Potential Productivity -- Elimination - Essential Industrial Engineering Activity


Seven Wastes

Seven Wastes Tool

Lean for Government: Eliminating the seven wastes

Lean in Government

Seven Wastes in Preventive Maintenanee Programs

Updated 23 August 2017, 15 November 2013

Sunday, August 20, 2017

Poka-Yoke - Shigeo Shingo

For Zero defects, Shigeo Shingo came up with an industrial engineering solution. Industrial engineering needs efficiency sense and focus. They have to use engineering knowledge to improve the efficiency of engineering systems and reduce costs. The solution proposed by Shingo for zero defect production is Poka-Yoke. The features built into the machine and associated devices that prevent defects from happening.  The features inform the operator that a mistake has happened and provide him an opportunity to correct the mistake.

Familiar examples of Poka Yoke

1) Warning about missing attachment file you get while composing email using Gmail.

2) Websites showing password strength indicator to show password strength. So weak passwords are avoided.

3) Google search engine feature to auto-suggest spelling corrections for user search query. This helps uses to avoid making inadvertent mistakes during search.



Iris D. Tommelein
Director, Project Production Systems Laboratory, http://p2sl.berkeley.edu/, and Professor,
Engineering and Project Management Program, Civil and Environmental Engineering Department,
215-A McLaughlin Hall, University of California, Berkeley, CA 94720-1712,


2008 Paper on Shingo System


Mistake-Proofing for Operators: The ZQC System

Shigeo Shingo, Productivity Press Development Team
Productivity Press, 01-Jan-1997 - Business & Economics - 80 pages

The Zero Quality Control System (ZQC) is a mistake-proofing approach that prevents defects by monitoring processing conditions at the source and correcting errors that cause defects. Since it is human nature to make mistakes, ZQC does not blame people for errors, but instead finds ways to keep errors from becoming defects. In this breakthrough approach, mistake-proofing devices called poka-yoke are used to check and give feedback about each product or operation in the process, not just a sample. This book introduces operators and assembly workers to the basic methodology of ZQC in an easy-to-read format that covers all aspects of this important manufacturing improvement strategy.

Mistake-Proofing for Operators includes the instructional features that are the signature of the Shopfloor Series. In this series Productivity Press has taken the lead in adult education by teaming with instructional designers to develop complete programs for frontline learning. The goal: to place powerful and proven improvement tools such as ZQC and mistake-proofing in the hands of your company's entire workforce.

Winner of the 1990 Shingo Prize for Excellence in Manufacturing, Mistake-Proofing for Operators is based on Zero Quality Control: Source Inspection and the Poka-Yoke System by Shigeo Shingo

Poka-Yoke: Improving Product Quality by Preventing Defects
Nikkan Kogyo Shimbun, Factory Magazine
Productivity Press, 1988 - Business & Economics - 282 pages

If your goal is 100% zero defects, here is the book for you — a completely illustrated guide to poka-yoke (mistake-proofing) for supervisors and shop-floor workers. Many poka-yoke ideas come from line workers and are implemented with the help of engineering staff or tooling or machine specialists. The result is better product quality and greater participation by workers in efforts to improve your processes, your products, and your company as a whole.

The first section of the book uses a simple, illustrated format to summarize many of the concepts and main features of poka-yoke. The second section shows 240 examples of poka-yoke improvements implemented in Japanese plants.

The book:

Organizes examples according to the broad issue or problem they address.
Pinpoints how poka-yoke applies to specific devices, parts and products, categories of improvement methods, and processes.
Provides sample improvement forms for you to sketch out your own ideas.
Use Poka-yoke in study groups as a model for your improvement efforts. It may be your single most important step toward eliminating defects completely. (For an industrial engineering perspective on how source inspection and poka-yoke can work together to reduce defects to zero, see Shigeo Shingo's Zero Quality Control.)

Training Programmes

Shingo Institute of Japanese Management, Bangalore and Hyderabad


Updated   21 August 2017,  25 February 2017,  21 December 2013

Friday, August 18, 2017

UK Productivity


The UK currently lags behind its G7 competitors’ average productivity levels by an average of 18% - and 35% behind Germany. Poor management is estimated to cost the UK £84bn in lost productivity a year.


Chartered Management Institute (CMI) proposed a management manifesto to improve management in UK and reclaim the 84 billion pounds lost in productivity due to poor management.

You can download the manifesto document from:


Tuesday, August 15, 2017

Productivity Improvement Through Smart Machines

IIOT, Industry 4.0, 4IR (Fourth industrial revolution) etc. are  frameworks to merge the operational technology (OT) with the information technology (IT) to provide new solutions for automating and networking industrial machines and systems for performance and productivity improvement.

What is a Smart Machine?

It is self-­aware, reacts autonomously and provides information about the product being produced, production parameters utilized, production time taken production quantity in unit time periods, production history,  configuration, condition, quality and Overall Equipment Efficiency (OEE) to other machines.

Smart Machine Control
Machine vision and advanced motion control are key components of smart automation. Engineers can increase throughput and build highly efficient modern machines that sharpen accuracy and easily adapt to new products and processes.

Today, the keys to smart machine control are gaining insight into the machine’s operation and the ability to adjust control outputs. Engineers rely on sensor information to monitor the condition of mechanical parts, which gives them the ability to observe the process for quality control or closed-control loops for applications like force feedback or precise positioning.

Today, LabVIEW (of NI.Com) graphical programming helps leading machine builders master this increasing system complexity with add-on modules for motion control, machine vision, and control design and simulation.


Leonardo Smart Rotational Moulding Machine

Smart Machine
Bringing intelligence into the milling process is the intended aim of "smart machine".

Optimization of the Machining Process


Patented: The Original OSS
The intelligent Operator Support System optimises the machining process according to the specifications of the workpiece. The target variables – speed, accuracy and surface quality – as well as the workpiece weight and the complexity of the machining application can be selectively defined and modified at any time via an intuitive user interface.

Setting priorities
The user can define the machine settings via the OSS, depending on the operation. He can choose from 12 predefined settings or extend them as desired.

Priority: Time

Only the time is of interest when roughing. If the operator selects the time as the highest priority, then OSS extends the tolerance band. In addition to this, the control system adapts the speed profile to the geometry that is to be processed.

Priority: Surface quality

In order to maintain the best possible surface quality despite poor NC program quality, the tolerance band is enlarged and the transitions are smoothed

Priority: Accuracy

If the workpiece demands extremely high precision, the tolerance band selected is narrower, in order to achieve the required accuracy. The control system is configured in such a way that the best possible geometrical accuracy is guaranteed.

User-defined setting

Additional settings can be saved in a library and can then be used again at any time. Several positions can be selected between the extremes (surface quality, accuracy, time).

Productivity & Precision

Your benefit
The intelligent system sets the dynamic behaviour of the machine exactly according to the workpiece requirements
Shorter machining times
Better surface quality
Intuitive handling of complex settings
Reduced complexity when setting up a workpiece


Cat (Caterpillar) Connect Technology: Hardware and software available for equipment to arm customers with information designed to help them optimize their operations. Specific construction technologies include:

        o  LINK, a solution that captures vital performance and product health data and makes that data available on the web to guide decision-making.

        o  GRADE and COMPACT, two productivity solutions that help operators move material faster, more accurately and with fewer passes.

        o  PAYLOAD, an on-board system for trucks and loading tools that drives higher efficiency, shorter cycle times and lower cost per ton.


Smart Asphalt Compaction


Caterpillar’s new B-Series tandem vibratory asphalt roller models include a range of advancements in intelligent compaction technology to deliver higher quality compaction. These models — the CB64B, CB66B, and CB68B — feature technological improvements made possible through Cat Compaction Control, Caterpillar’s intelligent compaction suite. The suite consists of dual air-purged, infrared temperature sensors that are integrated into the front and rear of the machine.


Smart Food Processing

A Cisco project involving Sugar Creek Packing Co. , Washington Court House, Ohio is making machines and processes smarter. The company recently commissioned a brownfield project in Cambridge City, Ind., Harvesting large amounts of data and feeding it back as actionable information is used for  for establishing a high-performance work team structure at the plant. “High-performance work teams are semi-autonomous teams work with little supervision, with production, maintenance and HR issues handled by team members. They need meaningful feedback and they get it from the smart features of the system. A sous vide cooking system is an illustration of it. It is a disruptive cooking technology and a highly automated system, with hundreds of sensors to control the process. To access the data, team members use a Cisco mobile app called Jabber, “essentially an IP phone. This feature substitutes installing the system based on ordinary mobiles with a booster system that would have added $300-500 million to project cost. Jabber radios essentially function like a desk phone and integrate easily with plant software. The wireless network also will track worker locations within one meter via RFID tags embedded on protective headgear.



“Smart” ProSlab 155 Automated Turf Harvester

National Instruments Corporation, Austin, Texas describes the machine as smart machine.

The machine uses LabVIEW software and CompactRIO hardware supplied by National Instruments. The smart machine harvests turf 20 percent faster, and uses half the diesel fuel than other turf harvesting machines on the market. It uses more electric systems. FireFly engineers can also remotely monitor, diagnose, update (and control) the sensor-laden ProSlab 155





The technologies for building a large-scale and diverse scope of smart machines are coalescing and being tested by "first movers." Once they offer significant  cost reduction and productivity improvement, companies will embrace them by employing smart machines in place of humans.

IT cost is typically about four percent of annual revenue of the companies, whereas the labor costs that can be rationalized by smart machines are as high as 40 percent of revenue in some knowledge and service industries. This gives considerable scope for deploying further IT systems.

The firms that have not begun to develop programs and policies for a "digital workforce" by 2015 will not perform in the top quartile for productivity and operating profit margin improvement in their industry by 2020. As a direct result, the careers of CIOs who do not begin to champion digital workforce initiatives with their peers in the C-suite by 2015 will be cut short by 2023.


Books on Smart Machines

Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation: Methods for System Self-Organization, Learning, and Adaptation

Zhou, Zude
IGI Global, 31-Mar-2010 - Computers - 407 pages

The manufacturing industry has experienced dramatic change over the years with growing advancements, implementations, and applications in technology.

Manufacturing Intelligence for Industrial Engineering: Methods for System Self-Organization, Learning, and Adaptation focuses on the latest innovations for developing, describing, integrating, sharing, and processing intelligent activities in the process of manufacturing in engineering. Containing research from leading international experts, this publication provides readers with scientific foundations, theories, and key technologies of manufacturing intelligence.

Manufacturing in Real Time: Managers, Engineers and an Age of Smart Machines

Gian F. Frontini, Scott Kennedy, Scott L. Kennedy
Butterworth-Heinemann, 2003 - Business & Economics - 206 pages

The development of self-operating machines is the foundation of modern manufacturing. This current manufacturing environment is based on automation and smart machines that have the ability to make things with a level of accuracy and consistency that humans cannot match. In order to maximize efficiency, engineers and managers need to change their outlooks, processes and strategies and as a result, adopt new methods and management systems.

The authors demonstrate what is needed by first presenting a brief history of manufacturing and the changes we have already seen and then make their way into the current manufacturing environment. Topics covered include supply chain management, product streams, the role of automation in the supply chain, the relationships between machines and people in automated product streams (looking at what machines do best and what humans do best), variation and quality control, statistical process control, the flow of information in a supply chain and how all of these elements are effected by new technologies and need to be changed to allow for maximum efficiency as we move more toward automation in factories.

*Discover the impact of new technologies on the future shape on the manufacturing industry
*Excellent examples used throughout to demonstrate each idea and process
*Includes a CD with lectures, slides, tutorials, dynamic models and much more!




High Productivity Through Smart Factories

Updated 16 August 2017, 13 July 2017