OCTOBER 19-20, 2012 - YMCA University of Science & Technology

4.1 Contributions of Taguchi methods
Proceedings of the National Conference on
Trends and Advances in Mechanical Engineering,
YMCA University of Science & Technology, Faridabad, Haryana, Oct 19-20, 2012
Taguchi has made a very influential contribution to industrial statistics. Key elements of his quality philosophy
include the following:
Taguchi loss function (Ross 1996), used to measure financial loss to society resulting from poor quality;
The philosophy of off-line quality control ( Logothetis and Wynn1989), designing products and processes so that
they are insensitive ("robust") to parameters outside the design engineer's control; and
Innovations in the statistical design of experiments Atkinson, Donev, and Tobias, (2007), notably the use of an
outer array for factors that are uncontrollable in real life, but are systematically varied in the experiment. Taguchi
proposed a standard 8-step procedure for applying his method for optimizing any process.
4.2 Taguchi's rule for manufacturing
Taguchi realized that the best opportunity to eliminate variation is during the design of a product and its
manufacturing process. Consequently, he developed a strategy for quality engineering that can be used in both
contexts. The process has three stages:
• System design
• Parameter design
• Tolerance design
System design
This is design at the conceptual level, involving creativity and innovation.
Parameter design
Once the concept is established, the nominal values of the various dimensions and design parameters need to be
set, the detail design phase of conventional engineering. This is sometimes called robustification.
Tolerance design
With a successfully completed parameter design, and an understanding of the effect that the various parameters
have on performance, resources can be focused on reducing and controlling variation in the critical few
dimensions.
5. Mathematical modeling:
“ORTHOGONAL ARRAYS “(OAs) experiments Using OAs significantly reduces the number of experimental
configurations to be studied (Montgomery1991). The effect of many different parameters on the performance
characteristic in a process can be examined by using the orthogonal array experimental design proposed by
Taguchi. Once the parameters affecting a process that can be controlled have been determined, the levels at
which these parameters should be varied must be determined. Determining what levels of a variable to test
requires an in-depth understanding of the process, including the minimum, maximum, and current value of the
parameter. If the difference between the minimum and maximum value of a parameter is large, the values being
tested can be further apart or more values can be tested. If the range of a parameter is small, then less value can
be tested or the values tested can be closer together.
Array Selector
6. Taguchi’s design of experiments
DOE's Planning
1. Design and Communicate the Objective
2. Define the Process
3. Select a Response and Measurement System
4. Ensure that the Measurement System is Adequate
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