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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.