Automated Production Data Integration and Processing via Simulation Based Digital Twin

Recent developments in the production sector are slowly beginning to test Small and Medium Enterprises (SME) and their ability to compete with the remainder of the market, especially the enterprises specializing in large-scale mass production. The ever-increasing demand gradually creates a large gap between the various competitors and often forces the SME to take risks when making important decisions regarding production control. One of the solutions to this problem can be the use of a simulation based Digital Twin (DT) as a decisionmaking tool for production control. Naturally, the established on-site hardware and software differs for each job-shop, thus making the creation of generally applicable solutions almost impossible. The biggest issue that needs to be solved is the discrepancy in data between the on-site software and the newly created DT of the production line. Manual data transformation and transfer is one of the options for the integration process, but it requires an experienced operator with a specific skillset to perform the actions necessary for seamless execution of this process. Automating the process of data integration between two systems helps alleviate the entry requirements for the DT technology implementation into a job-shop environment. The presented case study explores the possibility of using automated algorithms for production order data evaluation and processing which can be applied to other data types with minor adjustments to the methods proposed.