A Novel Logistic Regression-Embedded 0-1 Mixed-Integer Probabilistic Robust Design Model to Obtain Optimum Sustainable Factor Settings

Abstract

Quality by design (QbD) focuses on satisfying the needs of products or processes when aiming for variance reduction. On the other side, sustainability is associated with carrying on to conduct so over time. The research gap is also addressed in sustainability and QbD in this paper. Next, robust design (RD) is a suitable approach to QbD to reduce the process or product variation regarding quantitative and qualitative design factors. For a number of situations, a binomial random response variable is considered to decrease the variability of the production process. Thus, this paper is four-fold. First of all, a modified distance-based criterion is developed to generate the design matrix when dealing with quantitative and qualitative design factors. Second, a logistic regression technique is presented for modeling responses when the random response variable is binomial. Third, a new logistic regression-based 0-1 mixed-integer probabilistic RD model is proposed to find optimum sustainable design factors. Fourth, an Industry 4.0 associated case study is performed in order to design sustainable process development, and the comparison and verification studies are also presented to show the effectiveness of the proposed probabilistic model. Further, managerial insights are provided based on the sustainable development goals (SDGs).