A Performance-Based Evaluation of Human and Cobot Collaboration in Cellular Manufacturing System

Abstract

The increasing demand for agile, efficient, and cost-effective production systems has made the integration of collaborative robots (cobots) in Cellular Manufacturing Systems (CMS) a growing area of interest. This study addresses the challenge of optimizing production performance in CMS by comparing three distinct configurations: human-only operation, full cobot deployment, and a hybrid system involving one cobot and one human operator. A case-based computational model was developed using real machining data for thirteen job types across six machine processes. Key performance indicators—Total Production Time (TPT), Workload Imbalance (WI), Worker Productivity (WP), and Flexibility (F)—were evaluated under each configuration. The methodology includes processing time reduction modeling for cobots (20% efficiency gain), workload distribution analysis, and objective value comparison across scenarios. Results show that the two-cobot configuration achieved the lowest TPT (362.2 mins) and WI (45.6 mins), while the hybrid system showed moderate improvements (TPT = 377.8 mins; WI = 81.8 mins) over the human-only setup (TPT = 389 mins; WI = 104 mins). The study concludes that while full cobot integration offers the highest efficiency, hybrid systems can still provide substantial gains in flexibility and productivity with reduced dependence on human operators. These insights are vital for manufacturers planning strategic cobot adoption to enhance CMS performance while managing human resource utilization effectively.