Product and Process Design Improvement Using the Taguchi Approach

Course Description:

This 4-day seminar will prepare you for immediate application of the Taguchi technique to your projects. Basic steps of experiment designs using the Taguchi orthogonal arrays will be discussed in detail. You will understand how improvement in consistency is measured in statistical terms and how experiments can be designed to improve it. The Taguchi Robust Design strategy, which deals with treatment of the uncontrollable factors and how to make the performance insensitive to the influence of the uncontrollable factors by controlling those factors that can be controlled, will also be covered in this course. Major emphasis will be placed on how to apply the method. Practical application steps, including brainstorming, team approach, and consensus decisions, are demonstrated through example project applications. Discussions of theory and mathematical treatments are kept to a minimum. Concepts covered in class lectures are practiced and tested using numerous class exercises. A large number of review questions in the reference handout provides opportunities to test what is learned in the class. Reviews of advance techniques and analysis of experimental results are covered during the last two days of the sessions. The participants are encouraged to attend as a team and bring their own projects to the class.

Who Should Attend:

Product/Process Design Engineer, R&D Scientists, or QA Personnel, Manufacturing. Manager, Director or Senior Engineer (who wish to lead, teach, and introduce this technique within your organization), Instructor in academic institution, Consultant and Trainer (who wish to help their clients work with interdisciplinary teams and optimize product designs and solve production problems).

Why should you consider our seminar?

Attendees to this session learn hands-on, how to apply the Taguchi experimental technique. 80% of class discussions deal with applications. Attendees learn how to apply the technique immediately to

	Optimize product/process designs
	Lay out efficient validation test plan
	Resolve technical & production problems cost effectively
	Build robust products, processes, recipes & formulations
	Increase response from conventional and web based advertisements
	Increase response from conventional or web based advertisements

Deliverables:

This 4-day seminar will prepare you for immediate applications. The goal is to make you ready to apply the technique in your performance improvement and variation reduction projects. You will know how to plan, and lay out experiments.

Prerequisites:

There is no minimum educational background requirement for this seminar. However, two or more years of college education in any field of science or engineering are helpful.

Program Length: 4 days.

1.	Overview of the Taguchi concepts of quality engineering
	New philosophy and Definition of Quality Loss to the society from poor quality Standardized technique
2.	Measuring cost of quality by Loss Function
3.	Review basic concepts in experimental design
	Types of factors and levels Common experiment designs Orthogonal array vs. one-factor-at-a-time experiments
4.	Project objective and Overall Evaluation Criteria
	Need for combining multiple evaluation criteria into a single index
5.	Experiments designed using orthogonal arrays
	Experiments with all factors at the same level Experiments involving factors at mixed levels
6.	Experiments to study interaction
	Trade off between factors and interactions Test for presence of interactions Test for relative influence of interaction
7.	Basic analysis and strategy for experimentation

1.	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
2.	Combination Design (special design tool)
3.	Strategy for Robust Designs
	New attitude toward uncontrollable factors Outer array for robust design

1.	An overview of Systems with Dynamic Response
	Understanding dynamic systems
2.	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
3.	Brainstorming for experimental design
	TEAM - the new disciplines in the workplace Order of discussions in the planning session Participants and facilitation of planning
4.	Computation of cost/ LOSS FUNCTION
5.	Reference and Application assistance
	Project application guidelines
6.	Design and analysis using computer software

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