A dynamic processing methodology of manufacturing data for the automated throughput analysis in cyber

Various studies have been conducted on cyber-physical production systems (CPPS), a core technology for the implementation of smart manufacturing. However, existing studies are mostly conceptual or at an early stage, such as the proposal of a reference architecture. To achieve the practical implementation of CPPS, a systematic methodology for the collection, processing, and application of the data for CPPS is required. This is because CPPS can be successfully implemented only when processing criteria and application methods for the diverse data that change in real time because of the nature of a manufacturing shop floor are presented. Various technologies and systems have been developed for collecting raw data from a shop floor, but they are mainly focused on the automation of manufacturing. Thus, more detailed and systematic research is required for more efficient application of such technologies using a cyber model, which is the core of CPPS. For this purpose, in this article, a logic-based systematic methodology that can generate a throughput analysis model from the real-time data of a shop floor in a CPPS environment was proposed. Furthermore, logics that perform the Mapping, Scaling, and Calibration of the data of the shop floor into the machine, process, and factory levels were developed and their application to throughput analysis was described through a case study. The results of this study are expected to facilitate the practical implementation of CPPS and contribute to the successful implementation of smart manufacturing and the resultant revival of the manufacturing industry