Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework

Rationale: Simulation technologies are used widely in industry as they enable efficient creation, testing, and optimization of the design of products and production systems in virtual worlds. Simulations of productivity and ergonomics help companies to find optimized solutions that maintain profitability, output, quality, and worker well-being. However, these two types of simulations are typically carried out using separate tools, by persons with different roles, with different objectives. Silo effects can result, leading to slow development processes and suboptimal solutions. Purpose: This research is related to the realization of a framework that enables the concurrent optimization of worker well-being and productivity. The framework demonstrates how digital human modeling can contribute to Ergonomics 4.0 and support a human factors centered approach in Industry 4.0. The framework also facilitates consideration of anthropometric diversity in the user group. Methods: Design and creation methodology was used to create a framework that was applied to a case study, formulated together with industry partners, to demonstrate the functionality of the noted framework. Results: The framework workflow has three parts: (1) Problem definition and creation of the optimization model; (2) Optimization process; and (3) Presentation and selection of results. The case study shows how the framework was used to find a workstation design optimized for both productivity and worker well-being for a diverse group of workers. Conclusions: The framework presented allows for multi-objective optimizations of both worker well-being and productivity and was successfully applied in a welding gun use case.

Automated summary

The research aimed to develop a framework for the concurrent optimization of worker well-being and productivity, supporting Ergonomics 4.0 and a human-centered approach in Industry 4.0. The framework allows for consideration of anthropometric diversity in the user group and was successfully demonstrated in a case study scenario with industry partners.