Automated input data management in manufacturing process simulation
Input Data Management (IDM) is a time consuming and costly process for Discrete Event Simulation (DES) projects. Input Data Management is considered as the basis of real-time process simulation (Bergmann, Stelzer and Strassburger, 2011). According to Bengtsson et al. (2009), data input phase constitutes on the average about 31% of the time of an entire simulation project. Moreover, the lack of interoperability between manufacturing applications and simulation software leads to a high cost to users in developing custom-built interfaces (NIST, 2011). Therefore, a standard structure is needed to facilitate data exchange within different manufacturing data from various sources and simulation packages (Harari, 2012). \ud \ud This work aims to develop an IDM system in order to enhance automatic data exchange within manufacturing process simulation projects. The approach is to use a Business Intelligence (BI) package to extract and collect simulation data from various sources, and then import to a DES application. Thus, a simulation model can be automatically updated in DES application by real-time system data. The prototype system is currently implemented in pilot-scale, and results are based on sample data files retrieved from the Simulation Engineering Department at Ford Motor Company. In addition to automatic data management, the system also generates an interoperable data file, which is compatible with most DES packages for simulation experiments. \ud \ud For the first time, a Business Intelligence system is applied to simulation data management projects, and is introduced as a novel solution for this context. The results of pilot-implementation indicated the possibility of direct connection between raw data sources and model database. The direct connection allows DES applications to integrate with different business systems without the need of plug-in translators for interpreting the exchanged data file. The system developed also reduces the number of human-driven processes through model update procedures. Also, it is found that the BI package can be integrated with existing middleware used in a company, to maintain an “as-is” simulation procedure, and minimise the possibility of process change in systematic model update.
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