IoT-based production logistics and supply chain system – part 2 IoT-based cyber-physical system: a framework and evaluation

Tu, M., Lim, M.K. and Yang, M.-F. (2018) IoT-based production logistics and supply chain system – part 2 IoT-based cyber-physical system: a framework and evaluation. Industrial Management and Data Systems, 118(1), pp. 96-125. (doi: 10.1108/IMDS-11-2016-0504)

Abstract

Purpose: The purpose of this paper is threefold: to present internet of things (IoT)-based cyber-physical system (CPS) architecture framework to facilitate the integration of IoT and CPS; to implement an IoT-based CPS prototype based on the architecture framework for a PL application scenario of in a case study; and to devise evaluation methods and conduct experimental evaluations on an IoT-based CPS prototype. Design/methodology/approach: The design research method, case study, emulation experiment method, and cost-benefit analysis are applied in this research. An IoT-based CPS architecture framework is proposed, and followed by the development of prototype system and testbed platform. Then, the emulation and experimental evaluation of IoT-based CPS are conducted on the testbed, and the experimental results are analyzed. Findings: The emulation experiment results show that the proposed IoT-based CPS outperforms current barcode-based system regarding labor cost, efficiency, and operational adaptiveness. The evaluation of the IoT-based CPS prototype indicates significant improvements in PL tasks and reduced part inventory under a dynamic changing shop-floor environment. Practical implications: The case study shows that the proposed architecture framework and prototype system can be applied to many discrete manufacturing industries, such as automobile, airplane, bicycle, home appliance, and electronics. Originality/value: The proposed IoT-based CPS is among the first to address the need to integrate IoT and CPS for PL applications, and to conduct experimental evaluations and cost-benefit analysis of adopting IoT-based CPS for PL. This paper also contributes to the IoT research by using diverse research methods to offer broader insights into understanding IoT and CPS.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Lim, Professor Ming
• Authors: Tu, M., Lim, M.K., and Yang, M.-F.
• College/School: College of Social Sciences > Adam Smith Business School > Management
• Journal Name: Industrial Management and Data Systems
• Publisher: Emerald
• ISSN: 0263-5577