An LOPCOW-OPTBIAS-based integrated approach for cobot selection in manufacturing assembly operations

摘要

Nowadays, collaborative robots (cobots) have gained much popularity in manufacturing industries to assist in various assembly operations. However, selecting the most suitable cobot can be challenging due to abundance of many viable options in the market. In this paper, an integrated approach combining logarithmic percentage change-driven objective weighting (LOPCOW) and ordering preference targeting at bi-ideal average solutions (OPTBIAS) methods is proposed. Based on a real-time illustrative example consisting of 13 alternatives and 6 evaluation criteria, OPTBIAS method identifies Elfin-P as the most approsite cobot model for the considered assembly operation. The effectiveness of this integrated approach is validated against other popular multi-criteria decision making (MCDM) techniques and objective criteria weighting methods. A sensitivity analysis with respect to variations in the criteria weights also proves robustness of the adopted approach. Thus, it can act as a potent MCDM tool in effectively selecting the most suitable assembly cobot for a given application.