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International Journal of Business Studies and Innovation
Frequency: Quarterly Published by lIKll

Open Access Research Paper
 IJBSI 2023/06
Vol.3, Iss.2 : 1-14

Green Smart Factory Information Transparency—Self-Healing Network Decision Analysis System

Xin-Xiu Yin1, Wei-Jie Guo1, Hung-Wei Chang1 and Chun-Pin Chang1*

1Department of Information Management, Chia Nan University of Pharmacy and Science, Tainan City 71710, Taiwan

Received:April 28, 2023; Revised:May 15, 2023; Accepted:June 10, 2023; Published:June 30, 2023
We proposed a management system with the concepts of decision analysis and on-site management for the transformation of the traditional manufacturing industry into smart factories (such as opaque and non-real-time information). The system was developed to achieve information transparency through a low-power customized communication protocol and make supply chain management clearer. In conjunction with the on-site management concept, it provided real-time on-site status information which integrated decision-making analysis methods to comprehensively evaluate the current situation of the factory. In the system, message queuing telemetry transport (MQTT) protocol was used to push emergency messages and quickly respond to emergencies. In this study, the system developed effectively improved the factory’s information transparency, production quality and efficiency, and process optimization which were in line with ESG goals and achieved sustainable development goals.

Keywords:  Scene management, Information transparency, Smart factory, ESG

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*Corresponding author; e-mail:

Citation:Yin, X.X., & Guo, W.J., & Chang, H.W., & Chang, C.P.(2023). Green Smart Factory Information Transparency—Self-Healing Network Decision Analysis System. International Journal of Business Studies and Innovation, 3(2), 1-14.

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Copyright: © 2023  The Author(s). Published with license by IIKII, Singapore. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.