A conceptual hybrid framework for industrial process improvement: integrating Taguchi methods, Shainin System and Six Sigma

Abstract

Design of Experiments (DoE) has evolved as powerful industrial statistics tool for managing and improving processes in diverse industries. The three broad approaches of DoE in practice: classical or traditional methods, Taguchi methods and Shainin System (SS), have their merits and demerits for a extensive industrial experimentation. Nonetheless, the power of these DoE approach is not fully harnessed in established process improvement frameworks in industries. On the other side, Six Sigma DMAIC is a well-accepted methodology for improving process capability through focus on customer’s requirement (CTQ). The use of DoE in traditional DMAIC framework is limited to quantification of influence factors on CTQ. To offer a contribution to this paucity, this paper proposed a conceptual Six Sigma/DOE hybrid framework aiming to integrate SS, Taguchi methods and Six Sigma DMAIC for process improvement in complex industry environment. A case on improving DF generation process in shock absorber assembly was developed to validate the effectiveness of the framework for intricate problem-solving.