This thesis describes the planning, execution and results of an embedded case study of discreteevent manufacturing simulation at Asea Brown Boveri's (ABB) operations in Sweden from 1968 through 1993. The main aim of the study has been to explore and learn more about the values created from manufacturing simulations. This is done by describing and analyzing the context of manufacturing simulation within one company group for a long period of time. The work has focused on four issues: the manufacturing systems, the simulation software tools, the application projects and the developments over the 26 years time horizon. The study is based on personal interviews, questionnaires and documents, such as project reports, meeting minutes etc.

Two in-house manufacturing simulators are described and compared with the two most frequently used standard software tools. The most important differences between the tools were found in the ease of learning and use, the modeling flexibility and the model visibility. 61 projects in which this software has been applied are described and analyzed. The majority of the projects involve capacity planning and/or evaluation of control rules.

Three recent projects within one division are described and analyzed in detail. The values created are more diverse than expected. Generally the literature brings us the notion of simulation as a tool for evaluating alternatives in a decision process. However, the study shows that this is just one of twelve possible motives for using simulation. A model is suggested that distinguishes these possible motives along three dimensions: process, phase and actors.

Different hypotheses as to why the use of simulation has changed over the 26 year period are discussed. Two reasons are found to be the level of investment and the software capabilities. However, management's interest in manufacturing in general and organizational learning through simulation in particular, seem to be of greater importance. Trends in the manufacturing industry and their impact on the demand for simulation are also discussed in the text, as well as a comparison between discrete-event simulation and some alternatives for capacity planning.