Optimization parameters for the cotton swab process using hybrid MCDM methods based on response surface methodology

Optimization parameters for the cotton swab process using hybrid MCDM methods based on response surface methodology

Productivity improvement is a more complicated and challenging issue to resolve. There is a solution to the multi-response optimization problem. This study proposes a novel approach to optimizing parameters in the cotton swab process using a hybrid Multiple criteria decision-making (MCDM) method based on Response surface methodology (RSM). Simultaneously enhance decision-making efficiency by integrating Technique for order preference by similarity to ideal solution (TOPSIS) and Weighted aggregated sum product assessment (WASPAS) methodology. The optimal conditions were a speed rate of 1300 rpm, a thickness of 1.5 g/m, and a slidver gap of 20 cm, while the defect and downtime were 2.54 kg and 360.67 mins, respectively. The confirmation demonstrates that the actual practical and predicted results were similar. The proposed method's total cost improves from condition A to condition B by 33.86% and 2.45%, respectively. Furthermore, the energy consumption of cotton was found to be 6,208.08 MJ. The total energy consumption may be divided into three main categories: electric energy, thermal energy, and manual energy, which account for 43.12%, 55.73%, and 1.15%, respectively. The entropy reaches its maximum value in the drying and packaging units, which have inefficiencies of 91.24% and 4.35%, respectively, while the combined inefficiencies in the other five units are only 4.41%. This study contributes to advancing decision-making processes and offers insights for enhancing operational efficiency in the pharmaceutical or other manufacturer sector.