14. Optimization Comparison Between Conference Matrices and Current Method with Temperature Control System

When optimizing using an orthogonal array, it is desirable to consider the various relationships between factors and assign many factors. Two-level orthogonal array can be assigned many factors. Three-level orthogonal array has the advantage of obtaining intermediate information on the level. For this reason, mixed type orthogonal arrays L₁₈ (2¹3⁷), L₃₆ (2¹¹3¹³), etc. are still used today (Bose and Bush in Ann Mathe Stat 23:208–524, 1952). The response of these mixed type orthogonal arrays is logarithmically converted to the SN ratio and sensitivity for optimization. This way also is called Taguchi methods (Taguchi, 1984, 1988). Parameter design with a two-step procedure for predicting the optimum conditions is performed from this SN ratio and sensitivity with factor effect graph. However, this method has two problems (1) and (2).

The confirmation value (b) had been expected as the optimum condition with minimized variation. But, there are the problems that this confirmation value (b) is worse than the best value (a) of the SN ratio of the orthogonal array used for estimation will appear for 62% of cases (Mori, 2018, 2020). So, the prediction accuracy for the optimum conditions is poor. In order to improve these problems (1) and (2), this paper report will propose a new method to apply the conference matrices to the layout and the coefficient figure to the analysis to the row data. This report provides an easy-to-understand explanation that the conference matrices reduces the number of experiments and improves prediction accuracy using the coefficient of variation, especially for researchers. We are sure our proposed ways to reduce the experimental number and the period and cost almost to 1/3–1/2 with the higher accuracy for optimizing, so we will recommend as the specific ways to solve the subjects of the Sustainable Development Goals. Especially it will contribute to create the effective countermeasures to Global Warning that has been requested immediately to take the actions to reduce the increasing temperature.