The alpha error of the Taguchi method with L16 array for the LTB response variable using simulation

Taguchi's quality engineering concepts are of great importance in designing and improving product quality and process. However, most of the controversy and mystique have been centred on Taguchi's tactics. This research proposes an extension to the on-going research by investigating the probability of identifying insignificant factors as significant, or the so-called alpha error, with L₁₆ orthogonal array for the larger-the-better type response variable using simulation. The response variables in the L₁₆ array are generated from a normal distribution with the same mean and standard deviation. Consequently, the null hypothesis that all factors in the L₁₆ array will be identified as insignificant is true. Simulation results, however, reveal that some insignificant factors are wrongly identified as significant with a very high probability, which may provide a risky parameter design. Therefore, efficient and more valid statistical tactics should be developed put out Taguchi's important quality engineering concepts into practice.