Applying the Mahalanobis–Taguchi System to Improve Tablet PC Production Processes

TLDR

Tablet PC manufacturing relies on product testing, which raises costs and demands higher quality, and the Mahalanobis–Taguchi System offers a multivariate diagnostic approach that has improved quality in many engineering domains. The study aimed to enhance the tablet PC product testing process by applying the Mahalanobis–Taguchi System alongside logistic regression and neural network models. The authors employed the Mahalanobis–Taguchi System to identify and eliminate insignificant test items, comparing its performance with logistic regression and neural network models. The Mahalanobis–Taguchi System achieved 98 % predictive power, outperforming logistic regression (93.3 %) and neural network (94.7 %) models, and its application reduced test items from 56 to 14, thereby shortening testing time, lowering tester and equipment costs, and stabilizing test site configurations.

Abstract

Product testing is a critical step in tablet PC manufacturing processes. Purchases of testing equipment and on-site testing personnel increase overall manufacturing costs. In addition, to improve manufacturing capabilities, manufacturers must also produce products with higher quality and at a lower cost than their competitors if they are to attract consumers and gain a competitive edge in their industry. The Mahalanobis–Taguchi System (MTS) is a novel technique proposed by Genichi Taguchi for performing diagnoses and forecasting with multivariate data. The MTS can be used to select important factors and has been applied in numerous engineering fields to improve product and process quality. In the present study, the MTS, logistic regression, and a neural network were used to improve the tablet PC product testing process. The results indicated that the MTS attained 98% predictive power after insignificant test items were eliminated. The MTS performance was superior to those of the conventional logistic regression and neural network, which attained 93.3% and 94.7% predictive power, respectively. After the testing process was improved using the MTS, the number of test items in the tablet PC product testing process was reduced from 56 to 14. This facilitated the development of more stable test site configurations and effectively reduced the testing time, number of testers required, and equipment costs.