Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools

Work-related musculoskeletal disorders (WMSDs) are often associated with high costs for manufacturing companies and society, as well as negative effects on sustainable working life of workers. To both ensure workers’ well-being and reduce the costs of WMSDs, it is important to consider worker well-being in the design and operations of production processes. To facilitate the simulation of humans in production and improve worker well-being, there are numerous digital human modelling (DHM) tools available on the market. Besides simulation of humans in production, there are numerous production simulation software to simulate production flows of factories, robots and workstations that offer the possibility of improving the productivity of the stations, optimizing the layout and the configuration of the production lines. Despite of the capabilities of DHM and production flow simulation software, there is a lack of tools that can handle an overall optimization perspective, where it is possible to concurrently treat aspects related to both worker well-being and productivity within one tool. This study presents a prescribed tool that enables concurrent multi-objective optimization of worker well-being and productivity in DHM tools by analyzing the impact of different design alternatives. The tool was assessed in a workstation layout optimization use case. In the use case, risk scores of an ergonomics evaluation method was used as a measure of well-being, and total walking distance and workstation area were used as measures of productivity. The results show that the optimized solutions improve both total walking distance, workstation area and ergonomic risk scores compared to the initial solution. This study suggests that the concurrent multi-objective optimization of worker well-being and productivity could generate more optimal solutions for industry and increase the likelihood for a sustainable working life of workers. Therefore, further studies in this field are claimed to be beneficial to industry, society and workers.CC BY-NC 4.0aitor.iriondo.pascual@his.seThis work has been supported by ITEA3 in the project MOSIM, the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde, within the Virtual Factories with Knowledge-Driven Optimization (VF-KDO) research profile and the Synergy Virtual Ergonomics (SVE) project, and by the participating organizations. Their support is gratefully acknowledged.