Multi-Objective Optimization of Cutting Parameters for Polyethylene Thermoplastic Material by Integrating Data Envelopment Analysis and SWARA-Based CoCoSo Approach

Abstract

This paper presents a comprehensive study on the multi-objective optimization of cutting parameters for Polyethylene (PE) thermoplastic material utilizing a CO2 laser. Recognizing the pivotal role of precise and efficient cutting in various sectors, from packaging to biomedical engineering, we integrate two potent analytical methodologies - Data Envelopment Analysis (DEA) and Step-Wise Weight Assessment Ratio Analysis (SWARA)-based Comprehensive Criteria Score Optimization (CoCoSo) approach. The cutting parameters chosen for the study were material thickness, power, and cutting speed. The experiments were conducted according to the Taguchi L18 orthogonal array. Measurements of surface roughness and kerf width were performed to examine the cutting quality. Additionally, another response variable, material removal rate, was calculated. By integrating Data Envelopment Analysis and SWARA-Based CoCoSo approach, the experimental condition that yielded the lowest surface roughness, kerf width, and the highest material removal rate was determined. The optimum experimental condition was found to be 4 mm material thickness, 80 W laser power, and 15 mm/s cutting speed. This work, therefore, paves the way for the innovative application of these combined methodologies in enhancing the production processes of PE and other thermoplastic materials, with clear implications for cost-effectiveness and sustainability in the manufacturing sector.