https://www.mdu.se/

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. 

Manufacturing companies are introducing process innovations, namely new production processes or technologies, to achieve increased competitiveness. Production systems design can ensure the fulfillment of process innovations. However, literature shows that the staff responsible for the design of production systems face unfamiliar circumstances, lack of consensus or understanding (equivocality), and absence of information (uncertainty). Hence, manufacturing companies find it difficult to support decision-making in the design of production systems leading to increased competitiveness. One way to support decision-making during production systems design is through discrete-event simulation (DES). However, there is limited understanding of the application of DES in decision-making support, in this context.

Therefore, the purpose of this thesis is to support decision-making through DES in the design of production systems involving process innovations. To this end, the thesis reviews the current understanding of production system design, including decision-making and DES. This thesis adopts a qualitative case study method to extract empirical data from three production systems design projects of a manufacturing company in the heavy vehicle industry.

The thesis offers several contributions. Firstly, the findings identify the conditions of use, challenges, requirements, and activities essential for the utilization of DES during production system design related to process innovations. These important findings are critical for supporting decision-making when manufacturing companies renew their production processes. Secondly, this thesis reveals that determining the conditions of use of DES for supporting decision-making rests on the structuredness of a decision (e.g. its degree of equivocality or analyzability), and the quantitative or qualitative nature or DES models. Thirdly, the results describe four novel findings about the challenges undermining the use of DES including equivocality, uncertainty, and the lack of a structured approach and the absence of resources for DES use. Fourthly, the results reveal three requirements necessary for the use of DES including analyzing information consensus, specifying the activities of conceptual models, and coordinating DES models with the information needs. Fifthly, this thesis provides three valuable findings describing additional activities in the design of production systems related to defining the objectives of DES models, and facilitating a structured approach and the management of resources for the use of DES.

This thesis present a framework that contributes to the use of DES for decision-making support at manufacturing companies. Based on this framework, managers of those companies can supervise formal activities involving the use of DES in production systems design.