Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization FrameworkShow others and affiliations
2021 (English)In: IISE Transactions on Occupational Ergonomics and Human Factors, ISSN 2472-5838, Vol. 9, no 3-4, p. 143-153Article in journal (Refereed) Published
Abstract [en]
OCCUPATIONAL APPLICATIONS
Worker well-being and overall system performance are important elements in the design of production lines. However, studies of industry practice show that current design tools are unable to consider concurrently both productivity aspects (e.g., line balancing and cycle time) and worker well-being related aspects (e.g., the risk of musculoskeletal disorders). Current practice also fails to account for anthropometric diversity in the workforce and does not use the potential of multi-objective simulation-based optimization techniques. Accordingly, a framework consisting of a workflow and a digital tool was designed to assist in the proactive design of workstations to accommodate worker well-being and productivity. This framework uses state-of-the-art optimization techniques to make it easier and quicker for designers to find successful workplace design solutions. A case study to demonstrate the framework is provided
TECHNICAL ABSTRACT
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.
Place, publisher, year, edition, pages
Taylor & Francis, 2021. Vol. 9, no 3-4, p. 143-153
Keywords [en]
ergonomics, digital human modeling, productivity, simulation, optimization
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Production and Automation Engineering; VF-KDO
Identifiers
URN: urn:nbn:se:his:diva-20699DOI: 10.1080/24725838.2021.1997834ISI: 000716285800001PubMedID: 34724884Scopus ID: 2-s2.0-85118760617OAI: oai:DiVA.org:his-20699DiVA, id: diva2:1611513
Part of project
Synergy Virtual Ergonomics (SVE), Knowledge FoundationMOSIM – Modular Simulation of Natural Human Motions, VinnovaVirtual factories with knowledge-driven optimization (VF-KDO), Knowledge Foundation
Funder
Vinnova
Note
CC BY 4.0
CONTACT Aitor Iriondo Pascual aitor.iriondo.pascual@his.se
Published online: 09 Nov 2021
This work has received support from ITEA3/Vinnova in the project Modular Simulation of Natural Human Motions (MOSIM), and from the Knowledge Foundation and the associated INFINIT research environment at the University of Skövde, within the Virtual Factories–Knowledge-Driven Optimization (VF-KDO) research profile and the Synergy Virtual Ergonomics (SVE) project, and from the participating organizations. This support is gratefully acknowledged.
10.1080/24725838.2021.1997834
2021-11-152021-11-152024-06-19Bibliographically approved
In thesis