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Robust Product and Process Designs with Dynamic Characteristics
(5-day Onsite Seminar with Application Workshop)

This session is for specialist in engineering design, research and development who have advance engineering thinking and wish to proactively initiate or mentor the organization in efforts to robust product and process designs. 

How to schedule   Course materials   Who should attend?  
Method & Session overviews   How you will benefit   Course description   Learning objectives  References   Course instructor  Seminar Topics and agenda   Cost   Why consider our seminar   Background-Taguchi Approach   Equipment needs

Dollar for dollar, the return on investment is maximum when design improvement efforts are invested in analysis phase of the engineering activities. One of the effective ways to improve product and process quality is to reduce variation in performance that potentially results in reduced rework and rejects downstream. To assure minimum performance variation requires building robustness into the design. Use of the Design of Experiment (DOE) technique, in particular, the standardized version of DOE and robust design strategies proposed by Dr. Genechi Taguchi, is a proactive way to achieve robust design. In this seminar, Dr. Roy of Nutek, Inc. will take you through the basic steps of experiment designs, Taguchi parameter design, robust design strategies for static and dynamic systems. The goal of this seminar with hands-on application workshop will be to prepare the participants with knowledge and confidence to apply the techniques leaned for immediate applications in their own projects.

Our onsite seminar/workshop offers your project team the proven skill they need to tackle the problems on the production floor and build robustness in product or process designs. The attendees to these sessions learn how to apply the Taguchi experimental design technique to (1) Optimizing product/process designs, and (2) Solve production problems .


Location: This seminar/workshop are held onsite, at your facility.

How to schedule: Classes are generally scheduled 12 weeks in advance. Call or write us (1-248-812-2071 ) for a formal cost proposal in electronic or hardcopy format.

Session Format: The 5-day seminar can also be split into a 3-day and a  2-day sessions when attendees have projects for immediate applications.

Course Materials:  As a session sponsor you will receive our handout materials consist of approximately over 250 pages. You may duplicate these materials for use during this and any future session at your facility. You will also receive one complimentary copy of our Qualitek-4 software (1 user/installation). Optionally, you may consider purchasing the textbooks by the instructor to the workshop participants.

ABOUT THE TECHNIQUE - Taguchi experiment design technique allows simultaneous study of multiple factors which influence the performance. It is an experimental strategy in which the number of experiments is minimum and the method for analysis of results is standardized. Most often the experiments are done using experimental hardware. But it can also be applied to analytical simulation if available. When applied to product or process optimization, the technique helps improve consistency of performance. Reducing variations can solve most production problems that are caused by higher rejects and warranty. The robust design strategies for products or processes with dynamic characteristics have the potential for most cost savings in the long term.


Method & Session Overviews
Design of experiment (DOE) is a powerful statistical technique for engineering, quality and scientific professionals engaged in design, development, and manufacturing of products. In the Taguchi approach a much-standardized DOE is utilized in a special way to optimize product/process design while simultaneously improving the consistency of performance.

In this application-oriented seminar, emphasis is put on teaching Taguchi philosophy and his experimental methodologies rather than the math. The attendees learn the basic application techniques of Taguchi experimental design. The course teaches application technique through actual case studies. Some theory and analysis techniques are covered, as well as methods for accomplishing major analysis tasks using computer software.

The last two days of the session are dedicated to helping attendees learn how to apply and analyze the results using Qualitek-4 computer software. All attendees are encouraged to bring their own projects to the class and when possible attend the seminar as a group with other project team members. The workshop portion (last two days) of the session allows attendees to learn applications with hands-on exercises. All software necessary for the conduct of the workshop is provided by the instructor.

WHO SHOULD ATTEND?
This session is designed to prepare the attendees for immediate applications. It covers time-proven methodologies and takes attendees through hands-on application exercises related to setting up experiments and analysis procedures. Attend if you wish to learn how to apply yourself confidently, or send the potential mentor or local expert within your organization. If your involve one or more of the following activities, you would benefit from this seminar/workshop.

HOW YOU WILL BENEFIT
The seminar is intended for application minded professionals. Upon completion of the seminar, the attendees will
understand TAGUCHI'S quality improvement PHILOSOPHY and learn how to SETUP EXPERIMENTAL STUDIES using the Taguchi method right away. They will learn how to ANALYZE the experimental results and quickly carry out most of the necessary calculations. The attendees also will learn how to QUANTIFY DESIGN improvement by using the Taguchi LOSS FUNCTION.

By completing this session and applying the technique, you will expect to:

  • Improve product and process performance
  • Design product and process such that their performance is immune to the influence of
  • uncontrollable variables (Robust Designs)
  • Reduce needs for reworks and rejects in production processes
  • Economically solve production and design problems that are hard to fix by adjusting a single item
  • Reduce expected warranty cost and estimate savings in terms of dollars achievable from the design improvement.

WHAT ARE THE TEACHING METHODS? Communicating the application philosophy and basic techniques are the main objectives. The emphasis is on showing how it is applied, rather than teaching the theory and the math. Practical application methods including brainstorming session for application case studies are discussed in details.

DETAILED COURSE DESCRIPTION

Overview of Taguchi concepts of quality engineering
Understanding what Design of Experiment (DOE) is and what’s new with the Taguchi approach is essential for developing application expertise. Although, detail statistical theory of DOE is beyond the scope of this seminar, basic principles of DOE and the standardized steps practiced today are covered in detail. You will understand: - How quality is defined as consistency and the statistical terms used to measure it  - Standardization introduced by Taguchi  - How a team approach can be beneficial to application effort

Measuring cost of quality by Loss Function
Conventionally, the cost of lack of quality is measured by cost of rejection at production. In the Loss Function, the ill effects of poor quality when the product is in use, is included in the cost. You will learn how the Loss Function is used to quantify the dollar benefits from improved designs.

Review basic concepts in experimental design
Experimental designs for simultaneous study of multiple two level factors introduces the basic principles in DOE. Types of factors, effects of factor level on the size of experiments, and the desired qualities of the orthogonal arrays are discussed in detail. You will understand: - Types of factors - Multiplicity of levels - Orthogonal array vs. one factor at a time experiments

Project objective and Overall Evaluation Criteria
When project objectives are numerous, it is likely that they are measured using subjective as well as objective evaluation criteria with different units of measurements. When the goal is to seek a design that is overall best, it becomes necessary to combine all evaluation criteria into a single number. A popular scheme is to define an Overall Evaluation Criterion (OEC). You will get an insight into: - Why it is difficult to combine engineering measurements into a single quantity - What is the need for combining multiple evaluation criteria into a single index - Rationale behind the scheme to combine subjective and objective evaluations into one number

Experiments designed using orthogonal arrays
Orthogonal arrays present opportunities to handle numerous experimental situations using a few simple guidelines. A small number of arrays, each of which can be used for multiple experimental situations, can also be used for: - Experiments with all factors having two, three or four levels - Experiments involving factors at mixed level - Example analysis for Main Effect and Optimum Condition.

Experiments to study interaction
The use of standard orthogonal arrays, although it keeps experiment design process simple, may not always produce satisfactory results. For better accuracy, the study of interaction effects and subsequent corrections may be necessary. Detailed treatment of interaction design and study will help you understand: - Trade off between factors and interactions - Testing for presence of interactions without sacrificing columns - Testing for relative  influence of interaction - Necessary condition for test of significance - Influence of interaction on experimental strategy

Basic analysis and strategy for experimentation
Compromising what you would like to study and what you can afford to study is a key decision in planning the experiment. Because interaction between factors under investigation is inevitable, and since the size of the experiment becomes prohibitively large when all interactions are included in the study, a balance between the number of factors and the interaction becomes extremely important. Knowledge about how to test for presence of interaction allows you to make a practical compromise between the two.

Experiments with mixed level factors
Factors selected for studies may not all have the same number of levels. Mixed levels (2, 3 and 4) factors can often be handled by using the standard 2-level arrays such as L-8, L-16 and L-32. To enhance your experiment design capabilities, you will learn how to:  - Upgrade 2-level columns into a 4-level column - Downgrade (dummy treatment) a 4-level column into a 3-level column - Downgrade (dummy treatment) a 3-level column into a 2-level column - Design 15 different experiments using an L-8 array.

Combination Design (special design tool)
I
n some experimental situation, conventional design approach makes the experiment too large; some special technique could potentially save experiments and time. Combination Design is such a special technique.

Strategy for Robust Designs
Variation in sample performances is due to uncontrollable, or "Noise" factors. To reduce variation is to minimize the influence of the uncontrollable factors. Conventional approach has been to investigate the uncontrollable factors and attempt to control their influence. But Taguchi offers revolutionary Robust Design concept which, instead of going after the uncontrollable factors, attempts to reduce their influence by adjusting the controllable factors. As part of this new experiment design strategy, you will learn: - New attitudes toward uncontrollable factors - How to design an experiment with Outer array  - How to achieve more "bang for the buck" from your experiment.

Experiment layout for Systems with Dynamic Response (if time is available)
Although common DOE projects under investigations are static in nature, there are some that exhibit response, which changes (Dynamic) depending on a specific factor (Signal). A quick review of the topic is intended to provide understanding of: - The nature of dynamic systems - How the response characteristics are determined - Procedure for carrying out the experiments.

Analysis of Results 
Although detail analysis of less importance in this seminar, complete statistical calculations are presented through five separate example experiments. Review of analysis steps through these examples will provide better understanding of the: - Main effect study for influence of factors - ANOVA for relative influence of factors - Optimum condition for estimation of performance improvement  - Cost savings expected from the improvement - Conservative predictions - Confidence level and confidence interval (C.I.) - Transformation of S/N data into measured units.

Brainstorming for experimental designs
Although, experiment planning is the first step in the application process, its full value cannot be realized until one is completely familiar with the experiment design and analysis techniques. Thus a final summary of the planning process is presented to reaffirm: - the role of the new disciplines in the workplace - Order of discussions in the planning session - Considerations for selecting participants for the planning session.

Computation of Savings using the LOSS FUNCTION
Consistent with the intent of the project, reduction of variation is the primary improvement desired. When analysis is performed using Signal to Noise Ratio (S/N) of the results, quantified improvement in terms of variation reduction can be computed. More than variation reduction, management generally value information in terms of cost benefit (return on investment) achievable from the improved design.

Strategy for Robust Designs
Variation in sample performances is due to uncontrollable, or "Noise" factors. To reduce variation is to minimize the influence of the uncontrollable factors. Conventional approach has been to investigate the uncontrollable factors and attempt to control their influence. But Taguchi offers revolutionary Robust Design concept which, instead of going after the uncontrollable factors, attempts to reduce their influence by adjusting the controllable factors. As part of this new experiment design strategy, you will learn: - New attitudes toward uncontrollable factors - How to design an experiment with Outer array  - How to achieve more "bang for the buck" from your experiment.

Experiment layout for Systems with Dynamic Response (if time is available)
Although common DOE projects under investigations are static in nature, there are some that exhibit response, which changes (Dynamic) depending on a specific factor (Signal). A quick review of the topic is intended to provide understanding of: - The nature of dynamic systems - How the response characteristics are determined - Procedure for carrying out the experiments

Analysis of Results 
Although detail analysis of less importance in this seminar, complete statistical calculations are presented through five separate example experiments. Review of analysis steps through these examples will provide better understanding of the: - Main effect study for influence of factors - ANOVA for relative influence of factors - Optimum condition for estimation of performance improvement  - Cost savings expected from the improvement - Conservative predictions - Confidence level and confidence interval (C.I.) - Transformation of S/N data into measured units.

Dealing with Dynamic Characteristics
Many products and processes do not have a fixed level of performance or a target. Instead, such desired results are expected to be in proportion to a key input (signal) factor. Such responses are said to posses dynamic characteristic. A common examples is the design of an electrical transformer, say, to step down voltage by 50% which reduces voltage in a ratio of 2:1 no matter what the input voltage is. Another example will be the mechanism for a weighing scale which will show the reading of a subject weight regardless of its magnitude. The materials covered in this part of the seminar covers strategies for designing robust products and processes with dynamic characteristics.

Design and analysis using computer software
Attendees will work as a group to apply the technique in their own project. The steps involved in real life applications, from experiment planning to run confirmation tests are traced. For the sake of class projects, results are assumed and analysis performed as if they were real results. All attendees learn how to analyze results using Qualitek-4 software. Instructor provides the software for the class.

YOUR LEARNING OBJECTIVES
The objective of the seminar is to prepare the attendees for immediate applications. The seminar content and instruction level are targeted toward practicing engineers. Discussions of practical application concerns and the rationale for selection of experimental parameters consume a major portion of class discussion. A college education or background in statistics is not necessary.

  • Understand Taguchi philosophy and Definition of quality
  • Learn what Loss Function is and how to it can help us determine savings
  • Recognize the need for working as a team and decide things by consensus
  • Learn how to combine multiple criteria of evaluation into a single index
  • Be aware of how to select factors and their levels for the experiment
  • Lay out the most efficient experiments using Taguchi Orthogonal arrays
  • Learn to examine and interpret results of statistical analysis. Recognize when to repeat experiments and when to plan experiments all over again
  • Determine variation reduction and learn to express the improvement in terms of dollar savings
  • Learn how to facilitate experiment-planning session for successful outcome.

 

REFERENCE TEXT FOR THE SEMINAR
I. Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement by Ranjit Roy , Hardcover (January 2001) John Wiley & Sons; ISBN: 0471361011, (How to order)

I. A Primer on the Taguchi Method by Ranjit Roy, Hardcover - 247 pages 1 edition (Available from WWW.AMAZON.COM )
 

ROOM AND FACILITIES FOR THE CLASS
A room that provides comfortable seating and more space for the attendees is preferable. PADDED CHAIRS and reduced outside noise make the learning process much easier.

BACKGROUND REQUIREMENTS
There are no minimum educational background requirements for this seminar. However, two or more years of college education in any field of science or engineering are helpful. The course is taught at a level easily understood by the practicing engineers, scientists and managers without a background in statistics.

TRAINING MATERIALS
The handout material consists of approximately 250 pages of typewritten documents. (Includes a text book and Qualitek-4 software when included in the seminar)

SEMINAR INSTRUCTOR
Ranjit K. Roy,
Ph.D., P.E. (Mechanical Engineering, president of NUTEK, INC.), Is an internationally known consultant and trainer specializing in the Taguchi approach of quality improvement. Dr. Roy has achieved recognition for his down-to-earth style of teaching of the Taguchi experimental design technique to industrial practitioners. Based on his experience with a large number of application case studies, Dr. Roy teaches an application-oriented training seminar and has developed a number of computer software programs, including the Qualitek-4
software for use with the design of experiments using the Taguchi technique.

Dr. Roy began his career with The Burroughs Corporation following the completion of graduate studies in engineering at the University of Missouri-Rolla in 1972. He then worked for General Motors Corp. (1976-1987) assuming various engineering responsibilities, his last position being that of reliability manager. While at GM, he consulted on a large number of documented Taguchi case studies of significant cost savings.

Dr. Roy established his own consulting company, Nutek, Inc. in 1987 and currently offers consulting, training, and application workshops in the use of design of experiments using the Taguchi approach. He is the author of A PRIMER ON THE TAGUCHI METHOD - published by the Society of Manufacturing Engineers in Dearborn, Michigan and Design of Experiments Using the Taguchi Approach: 16 Steps to Product and Process Improvement published (January 2001) by John Wiley & Sons, New York. Dr. Roy is a fellow of the American Society for Quality and an adjunct professor at Oakland University, Rochester, Michigan. Dr. Roy is listed in the Marquis Who’s Who in the world.

Seminar Schedule and Discussion Topics

Day 1

Day 2 & 3

Day 4&5

Overview of the Taguchi concepts of quality engineering
 -  New philosophy and Definition of   - Quality Loss to the society from poor quality
-Standardized technique
- Measuring cost of quality by Loss Function
-Review basic concepts in experimental design

  • Types of factors and levels

  • Common experiment designs

  • Orthogonal array vs. one-factor-at-a-time experiments

  - Project objective and Overall Evaluation Criteria

  • Need for combining multiple evaluation criteria into a single index

  - Experiments designed using orthogonal arrays

  • Experiments with all factors at the same level

  • Experiments involving factors at mixed levels

  -  Experiments to study interaction

  • Trade off between factors and interactions

  • Test for presence of interactions

  • Test for relative influence of interaction

  - Basic analysis and strategy for experimentation

- Experiments with mixed level factors
  • Upgrading 2-level columns into a 4-level array

  • Downgrading (dummy treatment) columns

  • 15 different experiments using an L-8 array

- Combination Design (special design tool)

- Strategy for Robust Designs

  • New attitude toward uncontrollable factors

  • Outer array for robust design

  • Dealing with Dynamic Characteristics

  • Ideal function, P-Diagram, System parameters, Experimental setup, etc

 


ATTENDEES EVALUATION

"Excellent presentation and approach to all with or without Taguchi background."

"Dr. Roy has a unique way delivering complex information in a common sense language."

"It’s a great relief to know that there are software packages available to do all of the number crunching and prepare the reports."

- An overview of Systems with Dynamic Response
-
Understanding dynamic systems

- Analysis of Results

  • Main effect study for influence of factors

  • ANOVA for relative influence of factors

  • Performance at optimum condition

  • Confidence level and interval (C.I.)

  • Transformation of S/N data

- Brainstorming for experimental design

  • TEAM - the new disciplines in the workplace

  • Order of discussions in the planning session

  • Participants and facilitation of planning

- Computation of cost/ LOSS FUNCTION
- References and Application assistance
- Project application guidelines

- Design and analysis using computer software

Day  5
- Group reviews and exercise
- Computer Software (Qualitek-4)
- Class project & presentation by the groups
- Class Evaluation and Adjournment

EQUIPMENT AND COMPUTER NEEDS FOR THE SEMINAR

  1. One overhead projector (+ a computer projection device when available)
  2. One flip-chart (Pens and Masking Tape)
  3. IBM AT/Compatible computers. One computer for every one to three attendees for the last two days of the 5-day session)
  4. Seminar binders (Nutek will provide a master copy to the host for duplication and distribution to all attendees)
  5. Text books (Optional item)

COST (Guidelines only): The cost for this 5-day Seminar with Hands-on Application Workshop varies depending on the number of attendees and number of sessions requested.  Call or write us for a fixed price quote for seminar at your facility. (* 5-day seminar/workshop entitles you to a complimentary Single User Copy of our Qualitek-4 software.)

Is 5-day Seminar with Workshop right for You?
If majority of your attendees have 4 or more years of college, they would benefit from detailed methodologies. If you have participants who hope to apply immediately, are interested in Robust Design strategies, and expect to have fairly larger projects, then you should consider our 5-day seminar.  Be aware that, this sessions include hands-on computer exercise, homework and group project application.   The attendees must be willing to work as groups and carry out a number of assignments.

If most your prospective attendees prefer simpler applications, are not interested yet about Robust Design, but hope to apply the technique in production problem solving applications, then you should consider our 2-day production problem solving seminar

WHY YOU SHOULD CONSIDER OUR ON-SITE SEMINAR
- Rated highly by seminar attendees. We are generally rated between 5 and 6 in a scale of 0 to 6.
- Those who attend our seminar learn how to apply the technique in their own projects immediately.
- Attendees to our seminar are encouraged to bring their own projects to the class and may indeed complete experiment design during the course of the seminar.
- Our instructor is the author of the popular text book (optional for seminar) A PRIMER ON THE TAGUCHI METHOD, and the designer of QUALITEK-4 software used in the seminar.
- Our seminar is focused primarily on applications. Data analysis is handled using the computer software. Attendees gain hands-on experience in experiment design and result analysis using the computer.
- Our client lists include: AT&T, FORD, Chrysler, GM, TRW, UNISYS, John Deere, Navistar International and many other automotive and non-automotive companies.
- Instructor Dr. Roy also teaches DOE/Taguchi courses offered by Oakland University, Rochester, MI, Univ. of Michigan, SAE, SME, etc.

- To date, Nutek has conducted over 25 sessions with FORD manufacturing plant personnel alone.


BACKGROUND OF THE TAGUCHI METHOD
Taguchi method (or approach) as it is popularly known in the United States, goes by the name of the author and researcher Dr. Genichi Taguchi of Japan. As the head of research department for Electronic Control Laboratory of Nippon Electric Company in the late 1940's, Dr. Taguchi performed extensive research with utilizing the DESIGN OF EXPERIMENT (DOE) technique
to improve the quality of manufactured products. DOE is a statistical experimental strategy introduced by R. A.. Fisher in England in 1920's. Fisher wanted to study the influence of rain, water, sunshine, fertilizer, etc. simultaneously on the growth of the agricultural produce. Since its introduction, there has been much improvement of the technique by the academic environment, but its use by the manufacturing industry has been rare. By early 1960's Dr. Taguchi introduced a standardized version of DOE along with a definite set of guidelines for improving consistency of performance and relating the same to cost savings through resulting reduced rejects and reworks. His technique was extensively used by engineers in TOYOTA, NIPPON DENZO, and many other Japanese companies. The Taguchi method was introduced to the USA in early 1980's by companies like FORD MOTOR , IBM, BELL LABORATORIES. Today engineers in most manufacturing companies in North America use this technique for manufacturing product and process optimization.

Quality as customers perceive it, has many elements such as PERFORMANCE, DURABILITY, RELIABILITY, SERVICE, DELIVERY, etc. Among these quality elements which are directly influenced by the engineering activities, most important is the performance. Use of Taguchi technique attempts to improve consistency in the performance. For most products, improved consistency goes a long way to improve the customer perception of the performance. Thus Taguchi method is generally credited with improving quality when consistency is indeed improved.

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EQUIPMENT AND COMPUTER NEEDS FOR THE SEMINAR:

  1. A computer screen projection device. 
  2. One flip chart
  3. Tent card or name tag for all attendees.
  4. Laptop computers (IBM/Compatible, one computer for every three or four attendees needed for the last three of the 5-day seminar/workshop)
  5. Seminar binders (Purchased from Nutek, or Nutek will provide a master copy for the host to duplicate and distribute to all attendees)
  6. Text books -Optional (Hosts may buy directly from the publisher)