Developing performance measurement system for Internet of Things and smart factory environment

Gyusun Hwang, Jeongcheol Lee, Jinwoo Park and Tai-Woo Chang

International Journal of Production Research, 2017, vol. 55, issue 9, 2590-2602

Abstract: To cope with large fluctuations in the demand of a commodity, it is necessary for the manufacturing system to have rapid reactive ability. This requirement may be secured by performance measurement. Although manufacturing companies have used information systems to manage performance, there has been the difficulty of capturing real-time data to depict real situations. The recent development and application of the Internet of Things (IoT) has enabled the resolution of this problem. In demonstration of the functionality of IoT, we developed an IoT-based performance model consistent with the ISA-95 and ISO-22400 standards, which define manufacturing processes and performance indicator formulas. The development comprised three steps: (1) Selection of the Key Performance Indicators of the Overall Equipment Effectiveness (OEE), and the development of an IoT-based production performance model, (2) Implementation of the IoT-based architecture and performance measurement process using Business Process Modelling and (3) Validation of the proposed model through virtual factory simulation. We investigated the effect of the IoT-workability on the OEE, based on the final results of the simulation, both for the planned and actual productions. The simulation results showed that the proposed model represented the timestamp data acquired by IoT and captured the entire production process, thus enabling the determination of real-time performance indicators.

Date: 2017
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Citations: View citations in EconPapers (15)

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DOI: 10.1080/00207543.2016.1245883

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