Page 226 - DMGT524_TOTAL_QUALITY_MANAGEMENT

Unit 14: Statistical Process Control

14.5.2 Various Terms used in Experimentation Notes

In the context of discussion on experimental designs, the common frequently used terms are:
Factor

Level
Treatment combination
Response
Effect
Interaction

14.5.3 Traditional Approach

The traditional approach to product and process optimization is to conduct one variable
at-a-time experiments. This approach though simple to plan and execute, suffers from several
drawbacks. For instance, varying factor ‘A’ from its nominal value ‘A1’ to some other value ‘A2’
may produce a given change in the quality of the product, when other factor ‘B’ is at a value ‘B1’.
However a different change in the quality of the product will result, when factor ‘B’ is at a value
‘B2’. This effect known as interaction effect cannot be detected under traditional approach.

14.5.4 Statistically Designed Experiments

A statistically designed experiment permits simultaneous consideration of all the possible factors
that are suspected to have a bearing on the response under investigation and as such even if
interaction effects exist, a valid evaluation of the main effect can be made. Scanning a large
number of variables is one of the ready and simpler objectives that a statistically designed
experiment would fulfill in many problem situations. Even a limited number of experiments
would enable the experimenter to uncover the vital factors as to which further trials would yield
useful results. The approach has a number of merits, namely it is quick, reliable and efficient.

14.5.5 Planning for Experimentation

The various steps to be followed in this direction are listed below:

Selection of area of study: Pareto analysis
Proof of the need for experimentation
Brain storming and Cause & Effect diagram: To list all the possible factors
Classification of factors

Interactions to be studied
Response and type of model for analysis
If the problem is of chronic nature and there is stability in the process, then it establishes the
need for experimentation. Before deciding to carry out experimentation the need for
experimentation must be established.

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