Abstract
This approach combines in a semi-automatic way known simulation-based bottleneck detection methods. It considers the integration of these methods into the simulation, significantly influencing execution speed and acceptance of the industrial environment. Even if the majority of detection tasks are automatically driven some user interaction is needed to find the bottlenecks. The paper describes common bottleneck definitions; already published bottleneck detection methods; and deployment of the new approach. The approach consists of a two-step procedure, first analyzing the system, and then generating scenarios testing the system's sensitivity against changes. Based on the scenarios, the bottleneck is derived. The applicability of the approach is discussed on a real-world paint shop system and items limiting system performance are identified.
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