A big data approach for worker’s performance evaluation in IoT-enabled manufacturing shopfloors

Abstract

Internet of things (IoT) and Radio Frequency Identification (RFID) technologies are gradually adopted in manufacturing recently. With the aid of them, numerous data is generated from daily manufacturing operations. Big data analytics is used in locating deficiencies and thus improving the productivity of a manufacturing shopfloor. Many studies have also examined the effect of “Blue Monday” and “post-lunch slump” on worker’s performance. This paper provides a big data approach on analyzing worker’s performance with the data collected from a manufacturing shopfloor. By evaluating the worker’s performance at different time periods, a better decision can be arranged for improving overall productivity.