Optimal scheduling in a Collaborative robot environment and evaluating workforce dynamic performance

After the emergence of industry 4.0 and continuous technological development, it became vital for industries to transfer mass production expertise into personalized products in small batches. Clients more aware their needs start basing decision on specific quality requirements, lower cost, shortest delivery date. This is where collaborative robots intervene, these structures can work hand with operators take charge hard, long, or repetitive tasks a fast, precise, robust manner. Although have great potential, they lack flexibility adaptability, aspects only be found humans. The workforce competencies performance are ultimate precursors any proper industrial evolution. Performances must go further than standard definitions attributed them. paper addresses scheduling problem, our proposition relies assumption that final programs divided sub- programs. Based similarities between sub-programs help propose schedule reduces significantly wasted time developing new going from one program another. will also address dissociation human robots’ performances context humans very dependent proximity. Finally, we definition workload while highlighting its dynamic aspect terms fatigue, motivation, correlation repetition learning process.