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Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (User Centred Product Design (UCPD))ORCID iD: 0000-0002-3129-7076
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Production and Automation Engineering)ORCID iD: 0000-0003-3124-0077
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (User Centred Product Design (UCPD))ORCID iD: 0000-0003-4596-3815
University of Skövde, School of Engineering Science. University of Skövde, Virtual Engineering Research Environment. (Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
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2022 (English)In: Sustainability, E-ISSN 2071-1050, Vol. 14, no 9, article id 4894Article in journal (Refereed) Published
Abstract [en]

Usually, optimizing productivity and optimizing worker well-being are separate tasks performed by engineers with different roles and goals using different tools. This results in a silo effect which can lead to a slow development process and suboptimal solutions, with one of the objectives, either productivity or worker well-being, being given precedence. Moreover, studies often focus on finding the best solutions for a particular use case, and once solutions have been identified and one has been implemented, the engineers move on to analyzing the next use case. However, the knowledge obtained from previous use cases could be used to find rules of thumb for similar use cases without needing to perform new optimizations. In this study, we employed the use of data mining methods to obtain knowledge from a real-world optimization dataset of multi-objective optimizations of worker well-being and productivity with the aim to identify actionable insights for the current and future optimization cases. Using different analysis and data mining methods on the database revealed rules, as well as the relative importance of the design variables of a workstation. The generated rules have been used to identify measures to improve the welding gun workstation design.

Place, publisher, year, edition, pages
MDPI, 2022. Vol. 14, no 9, article id 4894
Keywords [en]
ergonomics, digital human modeling, productivity, simulation, optimization, knowledge discovery
National Category
Production Engineering, Human Work Science and Ergonomics Computer Sciences
Research subject
User Centred Product Design; Production and Automation Engineering; VF-KDO
Identifiers
URN: urn:nbn:se:his:diva-21112DOI: 10.3390/su14094894ISI: 000794536700001Scopus ID: 2-s2.0-85129143963OAI: oai:DiVA.org:his-21112DiVA, id: diva2:1655523
Part of project
MOSIM – Modular Simulation of Natural Human Motions, VinnovaSynergy Virtual Ergonomics (SVE), Knowledge FoundationVirtual factories with knowledge-driven optimization (VF-KDO), Knowledge Foundation
Funder
Vinnova, 2018-02227Knowledge Foundation, 2018-0167
Note

CC BY 4.0

Correspondence: aitor.iriondo.pascual@his.se

Funding: This work has received support from ITEA3/Vinnova in the project MOSIM (2018-02227), and from Stiftelsen för Kunskaps- och Kompetensutveckling within the Synergy Virtual Ergonomics (SVE) project (2018-0167) and the Virtual Factories–Knowledge-Driven Optimization (VF-KDO) research profile (2018-0011). This support is gratefully acknowledged.

Available from: 2022-05-02 Created: 2022-05-02 Last updated: 2024-02-22Bibliographically approved
In thesis
1. Simulation-based multi-objective optimization of productivity and worker well-being
Open this publication in new window or tab >>Simulation-based multi-objective optimization of productivity and worker well-being
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

In industry, simulation software is used to simulate production, making it possible to predict events in production, calculate times and plan production, even in the early phases of the production development process. Software known as digital human modelling (DHM) tools can also be used to simulate humans working in production. When simulating digital human models, ergonomics evaluations can be carried out to assess whether workstation designs offer appropriate ergonomic conditions for the workers. However, simulations performed to predict and plan production are usually done separately from the human simulations performed to evaluate ergonomics. This can lead to suboptimal solutions in which a factory is optimized to improve either productivity or ergonomics. This thesis outlines the hypothesis that more optimal solutions for workstation design, layout and line balancing can be obtained in simulations by optimizing productivity and ergonomic factors simultaneously instead of considering them separately. Hence, the aim is to carry out research on the development of a simulation-based multi-objective optimization method for productivity and ergonomic factors and to realize the method as a software tool in order to test and communicate it. From an application and societal-impact perspective, the overall objective is to offer a new approach for designing production systems that focuses on both over-all system performance and the well-being of workers, reduces the effort of engineers and helps industry create more productive and sustainable workspaces.

Abstract [sv]

Simuleringsverktyg används i industrin för att simulera produktion. Det gör det möjligt att förutsäga händelser, uppskatta tider och planera produktionen, även i tidiga stadier av produktionsutvecklingsprocessen. På motsvarande vis används ergonomisimuleringsverktyg för att simulera människor som arbetar i produktionen. Ergonomisimulering kan till exempel utföras för att bedöma om utformningen av arbetsstationen erbjuder lämpliga ergonomiska förhållanden för arbetarna. Emellertid görs produktionssimuleringar vanligtvis separat från ergonomisimuleringar. Det kan leda till bristfälliga lösningar där en fabrik är optimerad för att förbättra antingen produktivitet eller ergonomi. Denna avhandling utgår från hypotesen att mer optimala lösningar för arbetsstationsutformning, layout och linje-balansering kan uppnås i simuleringar genom att samtidigt optimera produktivitetsfaktorer och ergonomiska faktorer istället för att beakta dem separat. Målet är därför att utforska utvecklingen av en simulerings- och flermålsbaserad optimeringsmetod för produktivitetsfaktorer och ergonomiska faktorer och att realisera metoden som ett mjukvaruverktyg för att testa och beskriva den. Ur ett tillämpnings- och samhällspåverkansperspektiv är det övergripande målet att erbjuda ett nytt tillvägagångssätt för att utforma produktionssystem som fokuserar på både systemprestanda och människans välbefinnande, som stödjer ingenjörer i deras dagliga arbete för att hitta goda lösningar, och hjälper industrin att skapa mer produktiva och hållbara arbetsplatser.

Place, publisher, year, edition, pages
Skövde: University of Skövde, 2023. p. xii, 79, [125]
Series
Dissertation Series ; 56
Keywords
Ergonomics, Productivity, Optimization, Simulation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; VF-KDO
Identifiers
urn:nbn:se:his:diva-23360 (URN)978-91-987907-0-2 (ISBN)
Public defence
2023-12-21, ASSAR Industrial Innovation Arena (stora scenen/main stage) & online, Skövde, 09:00 (English)
Opponent
Supervisors
Note

Ett av fem delarbeten (övriga se rubriken Delarbeten/List of papers):

E.     Development and Evaluation of a Digital Tool for Simulation-based Multi-objective Optimization of Productivity and Worker Well-being. Aitor Iriondo Pascual, Dan Högberg, Anna Syberfeldt, Erik Brolin. Journal paper. (Submitted to Advanced Engineering Informatics).

Available from: 2023-11-20 Created: 2023-11-14 Last updated: 2024-03-21Bibliographically approved

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Iriondo Pascual, AitorSmedberg, HenrikHögberg, DanSyberfeldt, AnnaLämkull, Dan

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