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In their strive for success in competitive markets companies often turn to Lean philosophy. However, for many companies Lean benefits are hard to substantialize especially when their ventures have met success through traditional manufacturing approaches. Traditional Lean tools analyze current situations or help Lean implementation. Therefore productions facilities require tools that enhance the evaluation of Lean proposals in such a way that decisions are supported by quantitative data and not only on a gut feeling.

This thesis proposes how Discrete Event Simulation may be used as an evaluation tool in production process improvement to decide which proposal best suits Lean requirements. Theoretical and empirical studies were carried out. Literature review helped define the problem. A case study was performed at Alfa Laval to investigate through a holistic approach how and why did this tool provide a solution to the research questions. Case study analysis was substantiated with Discrete Event Simulation models for the evaluation of current and future state Lean proposals.

Results of this study show that Discrete Event Simulation was not designed and does not function as a Lean specific tool. The use of Discrete Event Simulation in Lean assessment applications requires the organization to understand the principles of Lean and its desired effects. However, the use of traditional static Lean tools such as Value Stream Mapping and dynamic Discrete Event Simulation complement each other in a variety of ways. Discrete Event Simulation provides a unique condition to account for process variability and randomness. Both measurement of and reduction in variability through simulation provide insight to Lean implementation strategies.