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Publications (10 of 151) Show all publications
Danielsson, O., Ettehad, M. & Syberfeldt, A. (2024). Augmented Reality Smart Glasses for Industry: How to Choose the Right Glasses. In: Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning (Ed.), Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024). Paper presented at 11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024 (pp. 289-298). IOS Press
Open this publication in new window or tab >>Augmented Reality Smart Glasses for Industry: How to Choose the Right Glasses
2024 (English)In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024) / [ed] Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning, IOS Press, 2024, p. 289-298Conference paper, Published paper (Refereed)
Abstract [en]

Augmented reality smart glasses (ARSG) have been available as a commercial product since 2015. Many potential usage areas have been identified, including industrial use. The needs from industry have evolved, with more emphasis being put on sustainability. While ARSG can help improve efficiency and sustainability, there are also similarly associated costs to their implementation and use. This paper aims to present a process for how to choose ARSG for specific use cases as assembly operator support while considering the sustainability of their implementation. A narrative review of the literature was made to identify the current understanding of the environmental impact of ARSG, as well as what has been considered in regards to ARSG being integrated into a manufacturing environment. The analysis of the literature resulted in a proposed decision process. The decision process serves as a baseline for how to guide the decision of whether ARSG could be a suitable solution and, if so, what aspects to consider in the choosing of the ARSG model. Future work includes collaboration with industry to further improve the decision process based on empirical input. 

Place, publisher, year, edition, pages
IOS Press, 2024
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 52
Keywords
Augmented reality smart glasses, cyber-physical systems, operator support, smart production, sustainability, Cyber Physical System, Embedded systems, Environmental impact, Glass, Sustainable development, Associated costs, Augmented reality smart glass, Commercial products, Cybe-physical systems, Decision process, Industrial use, Smart glass, Augmented reality
National Category
Production Engineering, Human Work Science and Ergonomics Other Engineering and Technologies not elsewhere specified
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-23828 (URN)10.3233/ATDE240173 (DOI)001229990300024 ()2-s2.0-85191332013 (Scopus ID)978-1-64368-510-6 (ISBN)978-1-64368-511-3 (ISBN)
Conference
11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024
Note

CC BY-NC 4.0 DEED

© 2024 The Authors

Correspondence Address: O. Danielsson; University of Skövde, Sweden; email: oscar.danielsson@his.se

Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-07-08Bibliographically approved
Iriondo Pascual, A., Högberg, D., Syberfeldt, A. & Brolin, E. (2024). Development and initial usability evaluation of a digital tool for simulation-based multi-objective optimization of productivity and worker well-being. Advanced Engineering Informatics, 62, Article ID 102726.
Open this publication in new window or tab >>Development and initial usability evaluation of a digital tool for simulation-based multi-objective optimization of productivity and worker well-being
2024 (English)In: Advanced Engineering Informatics, ISSN 1474-0346, E-ISSN 1873-5320, Vol. 62, article id 102726Article in journal (Refereed) Published
Abstract [en]

Engineers use modelling and simulation techniques to efficiently create, evaluate, and optimize design solutions.In an industrial production context, engineers often need to consider requirements related to both productivityand worker well-being in order to find successful design solutions. However, simulations related to productivityand worker well-being respectively, are typically carried out by different engineering roles, using different digitaltools. This lack of integrated work procedure could lead to inefficient development processes and suboptimaldesign solutions. Additionally, since performing multi-objective optimizations is likely to be seen as a complicated task by engineers in areas such as design engineering, production engineering, and ergonomics, requiringspecific knowledge and skills, such tasks are typically performed by engineers specialized on optimization. Thispaper presents the development and usability evaluation of a digital tool that supports engineers not specializedin optimization to define and perform simulation-based multi-objective optimizations of requirements related toboth productivity and worker well-being in an automated and simultaneous manner. The digital tool is the resultof research carried out over a period of four years, following an iterative development and assessment process bythe means of use cases, done in close collaboration with potential users of the digital tool, i.e. engineers at severalcompanies. The usability evaluation of the digital tool shows that potential users in the industry view the tool asa promising support for performing their engineering tasks in a more efficient and integrated manner.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Ergonomics, Digital human modelling, Productivity, Simulation, Optimization
National Category
Information Systems Production Engineering, Human Work Science and Ergonomics
Research subject
Virtual Production Development (VPD); User Centred Product Design
Identifiers
urn:nbn:se:his:diva-24410 (URN)10.1016/j.aei.2024.102726 (DOI)001279828600001 ()2-s2.0-85199261046 (Scopus ID)
Note

CC BY 4.0

Corresponding author: Aitor Iriondo Pascual

University of Skövde, School of Engineering Science, 541 28 Skövde, Sweden.

E-mail address: aitor.iriondo.pascual@his.se

Available from: 2024-08-05 Created: 2024-08-05 Last updated: 2024-10-09Bibliographically approved
Elango, V., Hedelin, S., Hanson, L., Sandblad, J., Syberfeldt, A. & Forsman, M. (2024). Evaluating ERAIVA - a software for video-based awkward posture identification. International Journal of Human Factors and Ergonomics, 11(6), 1-16
Open this publication in new window or tab >>Evaluating ERAIVA - a software for video-based awkward posture identification
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2024 (English)In: International Journal of Human Factors and Ergonomics, ISSN 2045-7804, E-ISSN 2045-7812, Vol. 11, no 6, p. 1-16Article in journal (Refereed) Published
Abstract [en]

The convergence of the focus of Industry 5.0 on human well-being and the prevalent problem of work-related musculoskeletal disorders necessitates advanced digital solutions due to limitations in manual risk assessment methods. This research aimed to compare usability of a newly developed video-based awkward posture identification software, the ergonomist assistant for evaluation (ERAIVA) with a conventional manual method. The risk assessment tool utilised in this study, integrated into the ERAIVA digital platform, is the risk management assessment tool for manual handling proactively (RAMP). Four assessors evaluated video-recorded tasks using both methods (manual and ERAIVA). The usability was assessed through the post-study system usability questionnaire, time consumption, number of video replays and video annotation deletions. The impact on identification of awkward posture durations was also studied. ERAIVA exhibited the highest usability score; it showed a higher number of video replays of specific sequences and annotations without significant differences in time consumption.

Place, publisher, year, edition, pages
InderScience Publishers, 2024
Keywords
awkward postures, software, work-related musculo skeletal disorder, video-based, Industry 5.0, ergonomist assistant for evaluation, ERAIVA, risk management assessment tool for manual handling proactively, RAMP
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-24844 (URN)10.1504/ijhfe.2024.143861 (DOI)001396246500001 ()2-s2.0-85215393615 (Scopus ID)
Note

CC BY 4.0

Veeresh Elango: veeresh.elango@scania.com

Available from: 2025-01-16 Created: 2025-01-16 Last updated: 2025-02-04Bibliographically approved
Birtic, M., Senington, R. & Syberfeldt, A. (2024). Exploring Production System Knowledge Graph Applications Using a Simulation Framework. In: Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning (Ed.), Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024). Paper presented at 11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024 (pp. 268-279). IOS Press
Open this publication in new window or tab >>Exploring Production System Knowledge Graph Applications Using a Simulation Framework
2024 (English)In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024) / [ed] Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning, IOS Press, 2024, p. 268-279Conference paper, Published paper (Refereed)
Abstract [en]

Knowledge graphs are generating significant interest in industry and research. These graphs can be enriched with data to represent aspects of production systems such as their structure, component interrelationships, and conditions. This provides opportunities to gain insights into system behavior, performance, and states. Such insights could potentially be leveraged by a wide range of technologies for a multitude of purposes and applications such as system control, process optimization, and informed decision making. However, the existing literature addressing industrial applications of knowledge graphs related to production systems remains limited in scope and depth. This underscores the importance of developing methods for exploring the potential use and implementation of knowledge graphs in such systems. The primary focus of this study centers on facilitating such exploration by developing a virtual commissioning simulation framework. A modular production system is modelled that leverages physics, moving product dynamics, and incorporates authentic PLC and robot programs. A knowledge graph is integrated and enriched with data representing various aspects of the system. An application is developed to facilitate product routing and prioritization. A service-oriented approach is used that leverages graph data processing and exchange for service registration and matching. System simulations are conducted and subsequently the framework is evaluated for outcomes and findings. This study demonstrates the successful design and implementation of a production system simulation framework that uses knowledge graphs for system functionality. It demonstrates the exploration of knowledge graph applications through the development of a modular and service-oriented system that includes system functionality supported by the graph. The results highlight the potential of simulation suggesting its capacity for valuable exploration regarding potential applications of knowledge graphs within production systems. 

Place, publisher, year, edition, pages
IOS Press, 2024
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 52
Keywords
Industrial Applications, Knowledge Graphs, Manufacturing Simulation, System Representation, Data handling, Decision making, Graphic methods, Optimization, Virtual reality, Condition, Production system, Simulation framework, Structure component, System functionality, System knowledge, System simulations, Knowledge graph
National Category
Computer Systems Computer Sciences Production Engineering, Human Work Science and Ergonomics
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-23825 (URN)10.3233/ATDE240171 (DOI)001229990300022 ()2-s2.0-85191346183 (Scopus ID)978-1-64368-510-6 (ISBN)978-1-64368-511-3 (ISBN)
Conference
11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024
Note

CC BY-NC 4.0 DEED

© 2024 The Authors

Correspondence Address: M. Birtic; School of Engineering Science, University of Skövde, Skövde, Högskolevägen, Box 408, 541 28, Sweden; email: martin.birtic@his.se

Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-07-08Bibliographically approved
Birtic, M., Morilla Cabello, P., Muñoz Rocha, Á. & Syberfeldt, A. (2024). Exploring the Synergies of Modularization, Interface Standardization, and Service-Orientation in Production System Simulation. In: Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning (Ed.), Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024). Paper presented at 11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024 (pp. 185-195). IOS Press
Open this publication in new window or tab >>Exploring the Synergies of Modularization, Interface Standardization, and Service-Orientation in Production System Simulation
2024 (English)In: Sustainable Production through Advanced Manufacturing, Intelligent Automation and Work Integrated Learning: Proceedings of the 11th Swedish Production Symposium (SPS2024) / [ed] Joel Andersson; Shrikant Joshi; Lennart Malmsköld; Fabian Hanning, IOS Press, 2024, p. 185-195Conference paper, Published paper (Refereed)
Abstract [en]

Production systems of the future may be in constant flux and reconfiguration, continuously adapting to changing production conditions. Digital models and simulation are powerful tools that can be used for their design and operation. These models must co-evolve with the physical system to sustain their usefulness and relevance. This poses a significant barrier, given the complexities involved in their efficient creation and maintenance. To understand whether certain system design concepts make the simulation process easier, this study aims to investigate a combination of concepts that promote reconfigurability and flexibility to explore whether they can positively influence the simulation process. By integrating modularization, interface standardization, and a service-oriented architecture it is believed to support faster and easier creation and updates of digital models. Modularization enhances flexibility by decomposing complex systems into independent, interchangeable modules. Standardizing interfaces ensures uniformity and compatibility among modules. Using a service-oriented architecture entails the encapsulation of various functionalities within modules as services, which can be dynamically requested. Shedding light on the advantages arising from modeling and simulating systems adhering to the mentioned concepts the research also aims to lay the groundwork for further investigation into the potential synergies of these promising production concepts. The study’s methodology includes modeling and programming of industrial robotic production modules adhering to predefined physical and logical interfaces. Interoperability and service orchestration are achieved through a service-oriented architecture. A simulated Manufacturing Execution System is integrated to facilitate handling of module services, product data and service requirements. Finally, a specialized software plugin was developed to support rapid module instantiation into a production system for evaluation. Results suggest that using a modular approach may ease modelling and simulation efforts and could be supported further by developing tailored tools for rapid system development. 

Place, publisher, year, edition, pages
IOS Press, 2024
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 52
Keywords
Digital Twins, Industry 4.0, Modular production system, Rapid model development, Simulation, Information services, Interoperability, Modular construction, Robot programming, Service oriented architecture (SOA), Digital modeling, Model and simulation, Modularizations, Production system, Service orientation, Simulation process, Soa (serviceoriented architecture), Standardization
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-23821 (URN)10.3233/ATDE240164 (DOI)001229990300015 ()2-s2.0-85191355103 (Scopus ID)978-1-64368-510-6 (ISBN)978-1-64368-511-3 (ISBN)
Conference
11th Swedish Production Symposium, SPS 2024 Trollhättan 23 April 2024 through 26 April 2024
Note

CC BY-NC 4.0 DEED

© 2024 The Authors

Correspondence Address: M. Birtic; School of Engineering Science, University of Skövde, Skövde, Högskolevägen, Box 408, 541 28, Sweden; email: martin.birtic@his.se

Available from: 2024-05-13 Created: 2024-05-13 Last updated: 2024-07-08Bibliographically approved
Andersson, M. & Syberfeldt, A. (2024). Improved interaction with collaborative robots - evaluation of event-specific haptic feedback in virtual reality. Paper presented at 5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 Lisbon 22 November 2023 through 24 November 2023. Procedia Computer Science, 232, 1055-1064
Open this publication in new window or tab >>Improved interaction with collaborative robots - evaluation of event-specific haptic feedback in virtual reality
2024 (English)In: Procedia Computer Science, E-ISSN 1877-0509, Vol. 232, p. 1055-1064Article in journal (Refereed) Published
Abstract [en]

Industry 5.0 adopts a human-centric approach that views humans as a natural part of introducing new technology, such as collaborative robots. However, one of the main challenges in implementing collaborative robots is safety, including the sense of safety. Trust is also a primary challenge when establishing functional collaboration. Influencing factors includes experience and expertise, and research shows that Virtual Reality has the potential to perform such training. This research aims to investigate whether using virtual reality with appropriate feedback can be an effective platform for familiarization and training. In our experiment, we utilized haptic feedback from commercial Virtual Reality controllers to simulate physical interactions with collaborative robots. The experiment involved the participation of fifteen individuals. The results showed that participants regarded haptic feedback while moving as the most appropriate representation. This research aims to identify whether Virtual Reality with suitable feedback can serve as a familiarization and training platform.

Place, publisher, year, edition, pages
Elsevier, 2024
Keywords
Collaborative robots, Haptic feedback, Human-Robot Collaboration, Industry 4.0, Industry 5.0, Virtual Reality
National Category
Human Computer Interaction Robotics and automation Interaction Technologies
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-23730 (URN)10.1016/j.procs.2024.01.104 (DOI)001196800601008 ()2-s2.0-85189815786 (Scopus ID)
Conference
5th International Conference on Industry 4.0 and Smart Manufacturing, ISM 2023 Lisbon 22 November 2023 through 24 November 2023
Note

CC BY-NC-ND 4.0 DEED

© 2024 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0)

Correspondence Address: A. Syberfeldt; University of Skövde, Skövde, Högskolevägen 3, 541 45, Sweden; email: anna.syberfeldt@his.se

Available from: 2024-04-18 Created: 2024-04-18 Last updated: 2025-02-05Bibliographically approved
Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning. Processes, 12(11), Article ID 2379.
Open this publication in new window or tab >>Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning
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2024 (English)In: Processes, E-ISSN 2227-9717, Vol. 12, no 11, article id 2379Article in journal (Refereed) Published
Abstract [en]

Planning and designing factory layouts are frequently performed within virtual environments, relying on inputs from various cross-disciplinary activities e.g., product development, manufacturing process planning, resource descriptions, ergonomics, and safety. The success of this process heavily relies on the expertise of the practitioners performing the task. Studies have shown that layout planning often hinges on the practitioners’ knowledge and interpretation of current rules and requirements. As there is significant variability in this knowledge and interpretation, there is a risk that decisions are made on incorrect grounds. Consequently, the layout planning process depends on individual proficiency. In alignment with Industry 4.0 and Industry 5.0 principles, there is a growing emphasis on providing practitioners involved in industrial development processes with efficient decision support tools. This paper presents a digital support function integrated into a virtual layout planning tool, developed to support practitioners in considering current rules and requirements for space claims in the layout planning process. This digital support function was evaluated by industry practitioners and stakeholders involved in the factory layout planning process. This initiative forms part of a broader strategy to provide advanced digital support to layout planners, enhancing objectivity and efficiency in the layout planning process while bridging cross-disciplinary gaps.

Place, publisher, year, edition, pages
MDPI, 2024
Keywords
factory layout, digital support, Industry 4.0–5.0, space claims, rules and regulations
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-24639 (URN)10.3390/pr12112379 (DOI)001365889700001 ()2-s2.0-85210245876 (Scopus ID)
Note

CC BY 4.0

Published: 29 October 2024

(This article belongs to the Special Issue Process Automation and Smart Manufacturing in Industry 4.0/5.0)

Correspondence: andreas.lind@scania.com

This research was funded by Scania CV AB and the Knowledge Foundation via the University of Skövde, the research project Virtual Factories with Knowledge‐Driven Optimization (2018‐0011), and the industrial graduate school Smart Industry Sweden (20200044).

Available from: 2024-10-29 Created: 2024-10-29 Last updated: 2025-01-14Bibliographically approved
Lind, A., Iriondo Pascual, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2024). Multi-objective optimisation of a logistics area in the context of factory layout planning. Production & Manufacturing Research, 12(1), Article ID 2323484.
Open this publication in new window or tab >>Multi-objective optimisation of a logistics area in the context of factory layout planning
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2024 (English)In: Production & Manufacturing Research, ISSN 2169-3277, Vol. 12, no 1, article id 2323484Article in journal (Refereed) Published
Abstract [en]

The manufacturing factory layout planning process is commonly supported by the use of digital tools, enabling creation and testing of potential layouts before being realised in the real world. The process relies on engineers’ experience and inputs from several cross-disciplinary functions, meaning that it is subjective, iterative and prone to errors and delays. To address this issue, new tools and methods are needed to make the planning process more objective, efficient and able to consider multiple objectives simultaneously. This work suggests and demonstrates a simulation-based multi-objective optimisation approach that assists the generation and assessment of factory layout proposals, where objectives and constraints related to safety regulations, workers’ well-being and walking distance are considered simultaneously. The paper illustrates how layout planning for a logistics area can become a cross-disciplinary and transparent activity, while being automated to a higher degree, providing objective results to facilitate informed decision-making.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2024
Keywords
factory layout, logistics area, multi-objective optimisation, simulation
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-23640 (URN)10.1080/21693277.2024.2323484 (DOI)001175090400001 ()2-s2.0-85186422081 (Scopus ID)
Funder
Knowledge Foundation, 20200044Knowledge Foundation, 2018-0011
Note

CC BY 4.0

CONTACT Andreas Lind andreas.lind@his.se Global Industrial Development, Scania CV AB, Södertälje, Sweden

The authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimisation (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.

The work was supported by the Stiftelsen för Kunskaps- och Kompetensutveckling [20200044]; Stiftelsen för Kunskaps- och Kompetensutveckling [2018-0011].

Available from: 2024-02-29 Created: 2024-02-29 Last updated: 2024-11-21Bibliographically approved
Lind, A., Elango, V., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling Tool. IISE Transactions on Occupational Ergonomics and Human Factors, 12(3), 175-188
Open this publication in new window or tab >>Multi-Objective Optimization of an Assembly Layout Using Nature-Inspired Algorithms and a Digital Human Modeling Tool
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2024 (English)In: IISE Transactions on Occupational Ergonomics and Human Factors, ISSN 2472-5838, Vol. 12, no 3, p. 175-188Article in journal (Refereed) Published
Abstract [en]

OCCUPATIONAL APPLICATIONS

In the context of Industry 5.0, our study advances manufacturing factory layout planning by integrating multi-objective optimization with nature-inspired algorithms and a digital human modeling tool. This approach aims to overcome the limitations of traditional planning methods, which often rely on engineers’ expertise and inputs from various functions in a company, leading to slow processes and risk of human errors. By focusing the multi-objective optimization on three primary targets, our methodology promotes objective and efficient layout planning, simultaneously considering worker well-being and system performance efficiency. Illustrated through a pedal car assembly station layout case, we demonstrate how layout planning can transition into a transparent, cross-disciplinary, and automated activity. This methodology provides multi-objective decision support, showcasing a significant step forward in manufacturing factory layout design practices.

TECHNICAL ABSTRACT

Rationale: Integrating multi-objective optimization in manufacturing layout planning addresses simultaneous considerations of productivity, worker well-being, and space efficiency, moving beyond traditional, expert-reliant methods that often overlook critical design aspects. Leveraging nature-inspired algorithms and a digital human modeling tool, this study advances a holistic, automated design process in line with Industry 5.0. Purpose: This research demonstrates an innovative approach to manufacturing layout optimization that simultaneously considers worker well-being and system performance. Utilizing the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Particle Swarm Optimization (PSO) alongside a Digital Human Modeling (DHM) tool, the study proposes layouts that equally prioritize ergonomic factors, productivity, and area utilization. Methods: Through a pedal car assembly station case, the study illustrates the transition of layout planning into a transparent, cross-disciplinary, and automated process. This method offers objective decision support, balancing diverse objectives concurrently. Results: The optimization results obtained from the NSGA-II and PSO algorithms represent feasible non-dominated solutions of layout proposals, with the NSGA-II algorithm finding a solution superior in all objectives compared to the expert engineer-designed start solution for the layout. This demonstrates the presented method’s capacity to refine layout planning practices significantly. Conclusions: The study validates the effectiveness of combining multi-objective optimization with digital human modeling in manufacturing layout planning, aligning with Industry 5.0’s emphasis on human-centric processes. It proves that operational efficiency and worker well-being can be simultaneously considered and presents future potential manufacturing design advancements. This approach underscores the necessity of multi-objective consideration for optimal layout achievement, marking a progressive step in meeting modern manufacturing’s complex demands.

Place, publisher, year, edition, pages
Taylor & Francis Group, 2024
Keywords
Multi-objective, optimization, assembly, industry 5.0, factory layouts
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
User Centred Product Design; Virtual Production Development (VPD); VF-KDO
Identifiers
urn:nbn:se:his:diva-23938 (URN)10.1080/24725838.2024.2362726 (DOI)001247664700001 ()38865136 (PubMedID)2-s2.0-85195777525 (Scopus ID)
Funder
Knowledge Foundation, 2018-0011
Note

CC BY 4.0

Taylor & Francis Group an informa business

CONTACT Andreas Lind andreas.lind@scania.com, alt. andreas.lind@his.se Scania CV AB, Södertälje, Sweden

The authors appreciatively thank the support of Scania CV AB, the research school Smart Industry Sweden (20200044) and the research project Virtual Factories with Knowledge-Driven Optimization (2018-0011) funded by the Knowledge Foundation via the University of Skövde. With this support the research was made possible.

Available from: 2024-06-12 Created: 2024-06-12 Last updated: 2024-11-21Bibliographically approved
Syberfeldt, A. & Aslam, T. (2024). Simulation-Generated Training Data for Improved Performance of AI-Based Industrial Vision Systems. In: Philippe Geril; Satyajeet Bhonsale (Ed.), Industrial Simulation Conference: . Paper presented at 22nd Industrial Simulation Conference, ISC 2024, June 3-5, 2024, Valencia, Spain (pp. 83-87). EUROSIS-ETI
Open this publication in new window or tab >>Simulation-Generated Training Data for Improved Performance of AI-Based Industrial Vision Systems
2024 (English)In: Industrial Simulation Conference / [ed] Philippe Geril; Satyajeet Bhonsale, EUROSIS-ETI , 2024, p. 83-87Conference paper, Published paper (Refereed)
Abstract [en]

Quality inspections are essential in almost all manufacturing processes and can be undertaken using an automatic vision system. The main challenge when using AI-based vision systems is gathering enough training data for the AI to perform well. This study investigates the use of simulationgenerated data to address this challenge. A real-world industrial case study evaluates the feasibility of simulationgenerated images for training an AI to be used in an industrial vision system for quality inspection. Results from the study show that the approach has potential, but that simulationgenerated images cannot be used solely. However, real-world images must be mixed into the training data set to achieve satisfactory results. 

Place, publisher, year, edition, pages
EUROSIS-ETI, 2024
Keywords
AI, industrial vision system, quality inspection, simulation-generated images, Simulation-generated training data, Automatic vision system, Industrial vision systems, Manufacturing process, Performance, Real-world, Simulation-generated image, Training data, Vision systems, Inspection
National Category
Computer graphics and computer vision Production Engineering, Human Work Science and Ergonomics Other Computer and Information Science
Research subject
Virtual Production Development (VPD)
Identifiers
urn:nbn:se:his:diva-24464 (URN)2-s2.0-85201284678 (Scopus ID)978-9-492859-30-3 (ISBN)
Conference
22nd Industrial Simulation Conference, ISC 2024, June 3-5, 2024, Valencia, Spain
Note

© 2024, EUROSIS-ETI. All rights reserved.

Available from: 2024-08-29 Created: 2024-08-29 Last updated: 2025-02-05Bibliographically approved
Projects
Co-production of knowledge [2013-02489_Vinnova]; University of SkövdeAutonomous Refuse Trucks [2016-02609_Vinnova]; University of SkövdeAutomated quality inspection in assembly lines through low-cost vision system (VISION) [2018-01592_Vinnova]; University of Skövde; Publications
Syberfeldt, A. & Vuoloterä, F. (2020). Image Processing based on Deep Neural Networks for Detecting Quality Problems in Paper Bag Production. Paper presented at 53rd CIRP Conference on Manufacturing Systems, July 1-3, 2020. Procedia CIRP, 93, 1224-1229
MOSIM – Modular Simulation of Natural Human Motions; ; Publications
Hanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871. Iriondo Pascual, A. (2023). Simulation-based multi-objective optimization of productivity and worker well-being. (Doctoral dissertation). Skövde: University of SkövdeIriondo Pascual, A., Lind, A., Högberg, D., Syberfeldt, A. & Hanson, L. (2022). Enabling Concurrent Multi-Objective Optimization of Worker Well-Being and Productivity in DHM Tools. In: Amos H. C. Ng; Anna Syberfeldt; Dan Högberg; Magnus Holm (Ed.), SPS2022: Proceedings of the 10th Swedish Production Symposium. Paper presented at 10th Swedish Production Symposium (SPS2022), Skövde, April 26–29 2022 (pp. 404-414). Amsterdam; Berlin; Washington, DC: IOS PressIriondo Pascual, A., Smedberg, H., Högberg, D., Syberfeldt, A. & Lämkull, D. (2022). Enabling Knowledge Discovery in Multi-Objective Optimizations of Worker Well-Being and Productivity. Sustainability, 14(9), Article ID 4894. Iriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E., Perez Luque, E., Hanson, L. & Lämkull, D. (2022). Multi-objective Optimization of Ergonomics and Productivity by Using an Optimization Framework. In: Nancy L. Black; W. Patrick Neumann; Ian Noy (Ed.), Proceedings of the 21st Congress of the International Ergonomics Association (IEA 2021): Volume V: Methods & Approaches. Paper presented at 21st Congress of the International Ergonomics Association (IEA 2021), 13-18 June, 2021 (pp. 374-378). Cham: SpringerIriondo Pascual, A., Högberg, D., Lämkull, D., Perez Luque, E., Syberfeldt, A. & Hanson, L. (2021). Optimization of Productivity and Worker Well-Being by Using a Multi-Objective Optimization Framework. IISE Transactions on Occupational Ergonomics and Human Factors, 9(3-4), 143-153Iriondo Pascual, A., Högberg, D., Syberfeldt, A., García Rivera, F., Pérez Luque, E. & Hanson, L. (2020). Implementation of Ergonomics Evaluation Methods in a Multi-Objective Optimization Framework. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020, Skövde, Sweden (pp. 361-371). Amsterdam: IOS PressLjung, O., Iriondo Pascual, A., Högberg, D., Delfs, N., Forsberg, T., Johansson, P., . . . Hanson, L. (2020). Integration of Simulation and Manufacturing Engineering Software - Allowing Work Place Optimization Based on Time and Ergonomic Parameters. In: Lars Hanson; Dan Högberg; Erik Brolin (Ed.), DHM2020: Proceedings of the 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020. Paper presented at 6th International Digital Human Modeling Symposium, August 31 - September 2, 2020, Skövde, Sweden (pp. 342-347). Amsterdam: IOS PressIriondo Pascual, A., Högberg, D., Syberfeldt, A., Brolin, E. & Hanson, L. (2020). Optimizing Ergonomics and Productivity by Connecting Digital Human Modeling and Production Flow Simulation Software. In: Kristina Säfsten; Fredrik Elgh (Ed.), SPS2020: Proceedings of the Swedish Production Symposium, October 7–8, 2020. Paper presented at Swedish Production Symposium, October 7–8, 2020 (pp. 193-204). Amsterdam: IOS Press
Virtual factories with knowledge-driven optimization (VF-KDO); University of Skövde; Publications
Perez Luque, E., Iriondo Pascual, A., Högberg, D., Lamb, M. & Brolin, E. (2025). Simulation-based multi-objective optimization combined with a DHM tool for occupant packaging design. International Journal of Industrial Ergonomics, 105, Article ID 103690. Nourmohammadi, A., Fathi, M. & Ng, A. H. C. (2024). Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration. Computers & industrial engineering, 187, Article ID 109775. Lidberg, S. (2024). Decision Support Architecture: Improvement Management of Manufacturing Sites Through Multi-Level Simulation-Based Optimization. (Doctoral dissertation). Skövde: University of SkövdeHanson, L., Ljung, O., Högberg, D., Vollebregt, J., Sánchez, J. L. & Johansson, P. (2024). Enabling Manual Workplace Optimization Based on Cycle Time and Musculoskeletal Risk Parameters. Processes, 12(12), Article ID 2871. Lind, A., Elango, V., Bandaru, S., Hanson, L. & Högberg, D. (2024). Enhanced Decision Support for Multi-Objective Factory Layout Optimization: Integrating Human Well-Being and System Performance Analysis. Applied Sciences, 14(22), Article ID 10736. Redondo Verdú, C., Sempere Maciá, N., Strand, M., Holm, M., Schmidt, B. & Olsson, J. (2024). Enhancing Manual Assembly Training using Mixed Reality and Virtual Sensors. Paper presented at 17th CIRP Conference on Intelligent Computation in Manufacturing Engineering - CIRP ICME '23, Gulf of Naples, Italy, 12 - 14 July 2023. Procedia CIRP, 126, 769-774Lind, A., Hanson, L., Högberg, D., Lämkull, D., Mårtensson, P. & Syberfeldt, A. (2024). Integration and Evaluation of a Digital Support Function for Space Claims in Factory Layout Planning. Processes, 12(11), Article ID 2379. Jiang, Y., Wang, W., Ding, J., Lu, X. & Jing, Y. (2024). Leveraging Digital Twin Technology for Enhanced Cybersecurity in Cyber–Physical Production Systems. Future Internet, 16(4), Article ID 134. Smedberg, H., Bandaru, S., Riveiro, M. & Ng, A. H. C. (2024). Mimer: A web-based tool for knowledge discovery in multi-criteria decision support. IEEE Computational Intelligence Magazine, 19(3), 73-87Lind, A., Iriondo Pascual, A., Hanson, L., Högberg, D., Lämkull, D. & Syberfeldt, A. (2024). Multi-objective optimisation of a logistics area in the context of factory layout planning. Production & Manufacturing Research, 12(1), Article ID 2323484.
Enabling REuse, REmanufacturing and REcycling Within INDustrial systems (REWIND); Publications
Despeisse, M., Chari, A., González Chávez, C. A., Chen, X., Johansson, B., Igelmo Garcia, V., . . . Polukeev, A. (2021). Achieving Circular and Efficient Production Systems: Emerging Challenges from Industrial Cases. In: Alexandre Dolgui; Alain Bernard; David Lemoine; Gregor von Cieminski; David Romero (Ed.), Advances in Production Management Systems. Artificial Intelligence for Sustainable and Resilient Production Systems: IFIP WG 5.7 International Conference, APMS 2021, Nantes, France, September 5–9, 2021, Proceedings, Part IV. Paper presented at IFIP WG 5.7 International Conference, APMS 2021, Nantes, France, September 5–9, 2021 (pp. 523-533). Cham: Springer
Smart body-close technology for increased safety and health in the process industry [2019-02513_Vinnova]; University of SkövdeSurvey of Maker Space in Sweden with relevance to production [2019-05537_Vinnova]; University of Skövde
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ORCID iD: ORCID iD iconorcid.org/0000-0003-3973-3394

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