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Challenges of Simulation-based Optimization in Facility Layout Design of Production Systems
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0003-4180-6003
Innovation and Product Realisation, Mälardalen University.ORCID iD: 0000-0003-0798-0753
Division of Industrial Engineering and Management, Uppsala University.ORCID iD: 0000-0001-5100-4077
University of Skövde, School of Engineering Science. University of Skövde, The Virtual Systems Research Centre. (Production and Automation Engineering)ORCID iD: 0000-0003-3973-3394
2019 (English)In: Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK / [ed] Yan Jin, Mark Price, Amsterdam: IOS Press, 2019, Vol. 9, p. 507-512Conference paper, Published paper (Refereed)
Abstract [en]

Facility layout design (FLD) is becoming more challenging than ever. In particular, modern day manufacturing industry requires advancing from a traditional approach of mass production to one of mass customization including increased flexibility and adaptability. There are several software tools that can support facility layout design among which simulation and optimization are the most powerful – especially when the two techniques are combined into simulation-based optimization (SBO). The aim of this study is to identify the challenges of SBO in FLD of production systems. In doing so, this paper uncovers the challenges of SBO and FLD, which are so far addressed in separate streams of literature. The results of this study present two novel contributions based on two case studies in the Swedish manufacturing industry. First, that challenges of SBO in FLD, previously identified in literature, do not hold equal importance in industrial environments. Our results suggest that challenges in complexity, data noise, and standardization take precedence over challenges of SBO in FLD previously reported in literature. Second, that the origin of challenges of SBO in FLD are not technological in nature, but stem from the increased complexity of factories required in modern day manufacturing companies.

Place, publisher, year, edition, pages
Amsterdam: IOS Press, 2019. Vol. 9, p. 507-512
Series
Advances in Transdisciplinary Engineering, ISSN 2352-751X, E-ISSN 2352-7528 ; 9
Keywords [en]
Simulation-based Optimization, Facility Layout Design, Challenges
National Category
Other Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
INF201 Virtual Production Development; Production and Automation Engineering
Identifiers
URN: urn:nbn:se:his:diva-17707DOI: 10.3233/ATDE190089ISBN: 978-1-64368-008-8 (print)ISBN: 978-1-64368-009-5 (electronic)OAI: oai:DiVA.org:his-17707DiVA, id: diva2:1352865
Conference
17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, September 10–12, 2019, Queen’s University Belfast, UK
Available from: 2019-09-20 Created: 2019-09-20 Last updated: 2020-12-07Bibliographically approved
In thesis
1. Facility layout design with simulation-based optimization: A holistic methodology including process, flow, and logistics requirements in manufacturing
Open this publication in new window or tab >>Facility layout design with simulation-based optimization: A holistic methodology including process, flow, and logistics requirements in manufacturing
2020 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

Adaptability and flexibility are becoming key concepts in manufacturing. Today manufacturing companies often have to deal with random disruptive events, which necessitates significantly more complex manufacturing systems. Mass customization (manufacturing customized products with mass production efficiency) has also considerably increased the complexity of facility layouts, that is, the physical arrangement of the different aspects required to create products in a factory. Design and improvement of facility layouts is considered a major industrial problem as it affects so many aspects of business. Even in industrialized countries with a long manufacturing history, it is common to find facility layouts that lack optimized flows of materials and products. The main reason for this state of affairs is usually a lack of long-term planning, commonly due to continuous changes and adaptations of the production systems in the layout. These problems are exacerbated by today’s shortened product life cycle.Simulation and optimization are well suited to improve complex manufacturing systems in which several events occur at the same time with unpredictable situations. Thus this thesis aims to investigate how simulation and optimization, and their combination – called simulation-based optimization – can support the redesign and improvement process for existing facility layouts. A literature review shows there is a gap in the field relating to a holistic approach to optimizing facility layouts taking into account production processes and internal logistics. “Holistic” as used here refers to the consideration of the processes and flows occurring in the facility layout, namely machining, assembly, and internal logistics. The aim of this thesis thus includes proposing a holistic methodology based on discrete-event simulation to optimize processes, flows, and internal logistics related to the facility layout.A methodology is defined as a logical set of methods, and in this thesis the methodology has been developed using a case study method with a design and creation strategy. This approach has been successful in identifying and overcoming both theoretical and empirical challenges in simulation-based optimization of facility layout design. The methodology was evaluated using functional resonance analysis method and industrial case studies, and it has proven to be effective for optimizing facility layouts. These results can thus serve as a guideline for engineers and staff involved in this type of layout project, and as a guideline for managers and stakeholders to support strategic decisions.

Abstract [sv]

Anpassningsförmåga och flexibilitet är nyckelbegrepp för konkurrenskraft i den tillverkningsindustrin. Tillverkande företag står inför en ständigt förändrad omvärld som kräver betydligt mer komplexa produktionssystem än tidigare. Massiv kundanpassning av produkter (dvs. tillverkning av skräddarsydda produkter med massproduktionseffektivitet) är en av de faktorer som bidrar till en ökad komplexitet, inte minst i fabrikslayouterna. Framtagning och förbättring av fabrikslayouter anses vara en stor utmaning inom tillverkningsindustrin eftersom det påverkar så många olika aspekter av verksamheten. Även i länder med en lång tradition av industriell tillverkning är det vanligt att fabrikslayouter inte är optimerade med avseende på flödet av material och produkter. Den främsta orsaken till detta är ofta brist på långsiktig planering, vanligtvis på grund av kontinuerliga förändringar och anpassningar av produktionssystemen. Med alltjämt kortare produktlivscykler ökar problemen än mer.Simulering och optimering är väl lämpade för att hantera komplexa tillverkningssystem där flera händelser oförutsägbart inträffar samtidigt. Denna avhandling syftar till att undersöka hur simulering och optimering, och deras kombination – så kallad simuleringsbaserad optimering - kan stödja omdesign och förbättringar av befintliga fabrikslayouter. En genomgång av litteraturen visar att det finns få studier särskilt vad gäller en helhetssyn på optimering av fabrikslayouter, i denna avhandling benämnt med begreppet ”holistisk”. Med en holistisk ansats avses en samtidig inkludering av de processer och flöden som uppstår i fabrikslayout, produktion och intern logistik. Syftet med denna avhandling är att föreslå en holistisk metodologi baserad på diskret händelsestyrd simulering för att optimera fabriklayouter med hänsyn till processer, flöden och intern logistik.I avhandlingen har metodologin utvecklats baserats på fallstudier med en så kallad ”design and creation strategy”. Detta tillvägagångssätt har framgångsrikt lyckats identifiera och överbrygga både teoretiska och empiriska utmaningar i simuleringsbaserad optimering av fabrikslayouter. Metodiken har utvärderats med hjälp av funktionell resonansanalys och industriella fallstudier, och den har visat sig vara effektiv för att optimera fabrikslayouter. Resultaten från avhandlingen kan fungera som en riktlinje för ingenjörer och personal som är involverade i layoutprojekt, och som ett stöd för chefer och andra intressenter som tar strategiska beslut.

Place, publisher, year, edition, pages
Skövde: University of Skövde, Sweden, 2020. p. 97
Series
Dissertation Series ; 35
National Category
Production Engineering, Human Work Science and Ergonomics
Research subject
Production and Automation Engineering
Identifiers
urn:nbn:se:his:diva-19303 (URN)978-91-984918-9-0 (ISBN)
Public defence
2021-01-15, ASSAR Innovation Arena, Kavelbrovägen 2B, Skövde, 13:00 (English)
Opponent
Supervisors
Note

ADDITIONAL PUBLICATIONS:

8. System Design and Improvement of an Emergency Department using Simulation-Based Multi-Objective Optimization. Goienetxea Uriarte, Ainhoa; Ruiz Zúñiga, Enrique; Urenda Moris, Matías; Ng, Amos H. C. Journal of Physics, Conference Series, 2015, Vol. 616, no 1, article id 012015

9. A Simulation-Based Multi-Objective Optimization Approach for Production and Logistics Considering the Production Layout. Ruiz Zúñiga, Enrique; Urenda Moris, Matias; Syberfeldt, Anna. Proceedings of the 7th Swedish Production Symposium, 2016

10. The Internet of Things, Factory of Things and Industry 4.0 in Manufacturing: Current and Future Implementations. Ruiz Zúñiga, Enrique; Syberfeldt, Anna; Urenda Moris, Matías. Advances in Manufacturing Technology XXXI: Proceedings of the 15th International Conference on Manufacturing Research, 2017, p. 221-226

11. How can Decision Makers be Supported in the Improvement of an Emergency Department? A Simulation, Optimization and Data Mining Approach. Goienetxea Uriarte, Ainhoa; Ruiz Zúñiga, Enrique; Urenda Moris, Matías; Ng, Amos H. C. Operations Research for Health Care, 2017, 15, p. 102-122

12. A Genetic Algorithm for Bi-Objective Assembly Line Balancing Problem. Nourmohammadi, Amir; Fathi, Masood; Ruiz Zúñiga, Enrique; Ng, Amos H. C. Advances in Manufacturing Technology XXXIII: Proceedings of the 17th International Conference on Manufacturing Research, incorporating the 34th National Conference on Manufacturing Research, 2019, Vol. 9, p. 519-524

Available from: 2020-12-11 Created: 2020-12-07 Last updated: 2023-11-02Bibliographically approved

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Ruiz Zúñiga, EnriqueUrenda Moris, MatíasSyberfeldt, Anna

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