Data-Driven Quality Improvement: Handling Qualitative Variables

Abstract A data-based methodology for improving product quality is proposed. Referred to as Data-Driven Quality Improvement (DDQI), the proposed method can cope with qualitative as well as quantitative variables, determine the operating conditions that can achieve the desired product quality, optimize operating condition under constraints, and also evaluate the validity of the results. The desired yield is specified instead of the quality for a qualitative quality variable. This paper aims to formulate DDQI and demonstrate its usefulness with an illustrative example. In addition, possible extensions and remaining problems are discussed based on the authors' experience of suceeding in improving product quality by applying DDQI to several industrial processes.