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Tolerance design

Taguchi and Design of Experiments

Taguchi has taken agricultural techniques for the design of experiments and adapted them to an industrial context. The greatest benefits are achieved when Taguchi methods are used during development to prevent problems from occurring later, but they are also used with success in problem solving. We place the emphasis on engineering understanding rather than detailed statistical analysis.

Typical analysis which allows an optimum design to be identified

Course information

A two day, introductory course is aimed at managers, engineers and technicians in design, development, production and quality areas. It will be relevant to anyone who is involved with trials. We will prepare longer or shorter courses to meet your specific needs - the current record is a 2 minute explanation over the telephone!

No knowledge of statistics is needed, but familiarity with a basic scientific calculator will save time on the course.

Course content - two day introduction
The course is liberally illustrated with case studies and there are many exercises which participants undertake in small groups. We select examples and exercises or write new ones which are relevant to your business. Excel spreadsheet software is provided free.
• Application in the problem solving sequence and the design process
• Basic requirements before performing any experiments
• First principles for design and analysis of Taguchi trials
• Graphical methods to test for significance
• Prediction of performance
• Manipulation of arrays to suit real conditions
• Engineering and statistical techniques to deal with interactions
• Alternative methods for analysis
• Control and noise factors
• Taguchi parameter design as a practical tool
• Analysis and interpretation of trials for robustness

Expected results
The aim is practical throughout with the purpose of giving the participants a working understanding of a powerful tool. Delegates will have sufficient information by the end of the course to plan, execute, analyse and interpret their own experiments.