Abstract. The purpose of this paper is to demonstrate the approach of a scalable, flexible and adaptive simulation model used in factory planning on the basis of existing ERP and MES data. The dynamic simulation model was developed to validate and verify the changes of the production yield during factory planning and restructuring in the shop floor. This includes machinery relocation and ramp-up, new product phase-in, product portfolio changes and new product qualification processes. The objective is to enable an industrial engineer without simulation knowledge and experience to perform the simulations. Moreover, the model facilitates an analysis of the results for different scenarios, using the actual data from the ERP and MES systems.

This paper addresses methods for the preparation of simulation studies in the manufacturing domain. The approach builds on an existing Semantic Web Platform for Modeling and Simulation that supports planning and simulation projects especially during information preparation and results evaluation. A new platform module was developed in order to support simulation project members in the early phase, especially in the provision of information as well as in the rapid capacity analysis. The module integrates the constraints that have to be considered during the definition and calculation of different solution scenarios. These constraints are built as semantic rules utilizing the predicate logic and the Semantic Web technologies. INTRODUCTIONThe Procedure Model for Simulation ( Figure 1) comprises two phases that are very important not just for the simulation study itself, but also can be very beneficial for a rapid capacity analysis of the system to be simulated (for a detailed discussion of the Procedure Model see Rabe et al. 2008b). The first one is the phase of System Analysis that includes the objective to determine which elements of the real system in which granularity and with which mechanism have to be modeled and simulated. The second phase is the development of the Formal Model that contains a system-independent description of the future simulation model. In the phase of turning the model description into the executable model and before the start of the implementation phase, it is very beneficial to provide the simulation expert with rough but substantial information about the performance of the system to be simulated, especially about the required capacities. The best method is to assess the planned manufacturing system in the early phase and to obtain measurable benchmarks and performance indicators of the future system like capacity demand for each resource in hours per year, suitable shift system, required number of workstations, and necessary production space for the designated production portfolio and product mix. Additionally, there is a necessity to provide different views on the real system, its structure and components, the relations between the parts' functions and the resources. These multi faceted views should support the process of communication, answering, clarification and conclusion within the project phases. According to the Procedure Model in Figure 1, data (Raw Data and Prepared Data) are administrated separately from the knowledge (Conceptual Model and Formal Model) during simulation studies. Therefore, a significant effort has to be made in order to provide an information base for capacity estimation in the early phase of the simulation project. This paper suggests a solution for efficient and rapid preparation and support of simulation studies in the manufacturing domain. The solution is based on Semantic Web technologies as a system of ontologies and offers an explicit description of the system to be simulated beginning after the System Analysis phase integrating the data and therewith...

Abstract. Cyber Physical Systems (CPS) receiving more and more industrial reality. In this paper a concept for the application of CPS for Aircraft maintenance repair and overhaul, sketched with airline partners, will be given. Based on industrial needs and requirements as well as the current state of the art the concept is describing a direct assignment of MRO-tasks to mechanic, tools and spare parts in order improve aircraft availability. The planning will be supported through simulation based generation of contextual MRO-tasks.

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