Design of Experiments - An Approach to Robust Product & Process Quality with Real Life Examples - IMTMA/Q018



Programme Background

Product Quality issues either resulting from design or from manufacturing process or from service; not only results in repair & re-work, re-calls & replacements, but also leads to erosion of profit apart from causing significant damage to credibility and reputation of the organisation. This will result in competitive edge and loss of business in Global economy.

Current day products / processes are very complex and are involving the out puts from many subsystems / components or sub-processes and activities. Hence, any product / process quality issue can not be attributed due to a single factor. Therefore, Instead of a "Quick-Fix" solution as a convenient / conventional approach, it is absolutely essential to understand the root cause of issues, with a deep dive approach of understanding the significant factors and their interactions. Thus the structured approach not only helps in resolving the issue, but ensures that the same issue is not repeated in the future and the solutions arrived can be explored to be adopted to similar variants of the products / process of the organisation.

Design of Experiments (DoE) is one of the most successful structured approach in understanding the real life issues in identifying the critical factors and interactions in causing the issue. DoE also helps in delivering an effective solution by controlling them. Many techniques and approaches by utilising DoE in finding out those inputs which have maximum influence on the output through an minimum set of experiments. DoE saves considerable time & efforts in trouble shooting, identifying quality inputs and in rectifying the total system.

This programme will focus on providing over view of various approaches like factorial, fractional factorial DoE, DoE in Taguchi Method, benefits of applying and practical applications in designing a robust product / process.

Focus Areas
  • Overview – DoE, Structure and its elements
  • Understand – Full Factorial over Fractional Factorial Designs
  • PLAN – Understanding of DoE Designs, Terminology, benefits and plan for DoE
  • PERFORM – Decision on DoE Model and setting-up and performing a DoE, Aliasing and Confounding Effects of Factors
  • POST PROCESS – Analysis and interpretation of results
  • Analysis of DoE Results, Understanding transfer functions
  • Correlations and effects of factors on response, Graphical interpretations
  • Overview of Taguchi Method, Benefits & Limitations
  • Overview of Orthogonal Array Designs for DoE in Taguchi Method
  • Benefit & Structure of Inner and Outer Array
  • Interpretation of results from Factor effects
  • Examples.. Examples.. Examples..

The dates of this programme is not yet announced. For more information please click below button.

 

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