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Towards a Reduction of Uncertainty in Production System Design Decisions
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation. IPR (Innovation and Product Realisation).ORCID iD: 0000-0003-0798-0753
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0002-5963-2470
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0001-7935-8811
Mälardalen University, School of Innovation, Design and Engineering, Innovation and Product Realisation.ORCID iD: 0000-0003-4308-2678
2016 (English)In: Swedish Production Symposium 2016 SPS 2016, 2016Conference paper, (Refereed)
Abstract [en]

A tenet of production system design is to increase a manufacturing company’s competitiveness by introducing novel processes, technologies, and products. However, uncertainties exist regarding the actual benefits that can be attained when novelty and change are introduced into a production system. Addressing this issue, this paper explores how manufacturing companies can reduce uncertainties that challenge production system design decisions when significant changes are introduced into the production system. A real-time case study at a Swedish manufacturing company that decided to change its existing product specific assembly system to a multi-product assembly one was performed. Empirical results identify uncertainties challenging production system design configuration, and the activities targeting reduction of uncertainty. To extend current theory, empirical case study data is synthesized with current findings in production system design decisions, and uncertainty reduction in product design decisions. The paper concludes that information acquisition, uncertainty prioritization, project member background, and complexity of change influence uncertainty reduction in production system design decisions. Managerial implications highlight the importance of information acquisition and a structured approach when reducing uncertainties necessary to achieve an efficient and effective production system design. Thus, academic approaches to uncertainty reduction could benefit manufacturing practice.

Place, publisher, year, edition, pages
2016.
Keyword [en]
production system design, design decisions, uncertainty
National Category
Production Engineering, Human Work Science and Ergonomics
Identifiers
URN: urn:nbn:se:mdh:diva-34090OAI: oai:DiVA.org:mdh-34090DiVA: diva2:1056578
Conference
Swedish Production Symposium 2016 SPS 2016, 25 Oct 2016, Lund, Sweden
Available from: 2016-12-15 Created: 2016-12-13 Last updated: 2017-02-06Bibliographically approved
In thesis
1. Supporting Production System Design Decisions through Discrete Event Simulation
Open this publication in new window or tab >>Supporting Production System Design Decisions through Discrete Event Simulation
2017 (English)Licentiate thesis, comprehensive summary (Other academic)
Abstract [en]

Manufacturing companies are increasingly required to deal with and introduce significant changes in their production systems to gain a competitive advantage. The production system design process is widely considered a means of introducing such changes, and decisions made during design are viewed as critical to its characterization and performance. However, this presents a problem because committing to decisions that involve significant changes implies not only dealing with requirements, products, challenges, or expectations that are different from what currently exists, but also addressing uncertainties regarding both the information necessary for committing to a production system design decision and the actual benefits that can be achieved as a result of these changes. One way to support the production system design decisions in this context is through the use of Discrete Event Simulation (DES). However, understanding of DES use when supporting production system design decisions in this domain remains limited.    

Therefore, the objective of this thesis is to explore the use of DES in support of production system design decisions when significant changes are introduced. Data are collected through a multiple case study method and DES from three real-time production system design projects at one manufacturing company. All production system design projects studied involved the introduction of significant production system changes for which limited experience existed. The cases and results are presented in three appended publications.

The findings establish the purpose of DES use when supporting production system design decisions in this context. To this end three groups of DES model objectives are identified: communicating decisions and visualizing results, evaluating a production system design concept focused on operational performance, and experimenting with what-if scenarios while predicting production system outputs. The points of DES use when supporting production system design decisions are specified in relation to current theoretical understanding of a production system design process. Then, challenges and contributions of DES use supporting production system design decisions are identified.

A framework is presented to facilitate the use of DES supporting production system design decisions when significant changes are introduced. The framework is based on the identification of high-level strategic objectives and relates these to production system design decisions. It defines DES use in support of these decisions and establishes milestones for DES use during production system design. Based on an analysis of the challenges and contributions of DES use, the framework helps formulate the purpose of DES use to achieve production system design decision support. 

Place, publisher, year, edition, pages
Eskilstuna: Mälardalen University, 2017
Series
Mälardalen University Press Licentiate Theses, ISSN 1651-9256 ; 252
National Category
Engineering and Technology Production Engineering, Human Work Science and Ergonomics
Research subject
Innovation and Design
Identifiers
urn:nbn:se:mdh:diva-34800 (URN)978-91-7485-310-0 (ISBN)
Presentation
2017-03-17, Filen, Mälardalens högskola, Eskilstuna, 10:15 (English)
Opponent
Supervisors
Available from: 2017-02-06 Created: 2017-02-06 Last updated: 2017-03-08Bibliographically approved

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