عنوان انگلیسی مقاله:
Data analytics-enable production visibility for Cyber-Physical Production Systems
ترجمه فارسی عنوان مقاله:
تولید تجزیه و تحلیل داده فعال برای تولید برای سایبر فیزیکی سیستم های
Sciencedirect - Elsevier - Journal of Manufacturing Systems, 57 (2020) 242-253: doi:10:1016/j:jmsy:2020:09:002
With the wide integration of the Cyber-Physical System (CPS) and Internet of things (IoT), the manufacturing industry has entered into an era of big data. Thus, manufacturing companies are facing challenges when con- ducting Big Data Analytics, including the high velocity of data generation, the enormous volume, the multi- farious formats and types as well as the quality or fidelity. In this paper, a Cyber-Physical Production System (CPPS) using data analytics is proposed to enable production visibility. Firstly, this study uses data stream processing approaches to clean redundant data efficiently. Secondly, a Bayesian inference engine, which is trained by ming the historical data offline, is employed to identify the accuracy of an RFID-captured event online. Then, complex event processing is applied to fuse multi-source heterogeneous data. Finally, production progress visibility is achieved by the Business Process Management. The proposed system demonstrates that it is signif- icant to implement real-time data collection, processing and visibility, as well as to improve production effi- ciency. A demonstrative case from the machinery industry is presented to validate the CPPS.
Keywords: Production visibility | CPPS | Data analytics | Event stream processing | Complex event processing