Internet of things (IoT) technology has been widely used in manufacturing where great myriad of data have been generated. This paper introduces a big data analytics for Internet of Things (IoT)-enabled manufacturing shop floor which uses radio frequency identification (RFID) technology for capturing the real-time production data. This involves two machine learning techniques: k-means clustering and gradient descent optimization for the data from the manufacturing sites. In particular, this research deals with the real RFID data related to various processes for individual batches and processing time. This could produce valid predictions about expected overall manufacturing time for a given number of manufacturing batch inputs.
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Kho et al. (2018) studied this question.
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