System Informatics: From Methodology to Applications

• Published in: IEEE intelligent systems 2015-11, Vol.30 (6), p.12-29
• Main Authors: Zhao, Kang, Xie, Yao, Tsui, Kwok-Leung, Wei, Qingming, Huang, Wenpo, Jiang, Wei, Li, Yanting, Cho, Sugon, Kim, Seoung Bum, Liu, Kaibo, Shi, Jianjun, Jeong, Young-Seon, Kim, Byunghoon, Tong, Seung Hoon, Chang, In-Kap, Jeong, Myong K., Charruaud, Florent, Li, Lishuai
• Format: Article
• Language: English
• Subjects: after-sales service and support; Algorithms; Chips; Complex systems; Control charts; data analytics; Decision making; Dynamic random access memory; Informatics; Integrated circuits; intelligent systems; Internet of Things; Lithium; Methodology; Monitoring; Monitoring systems; Process control; projection; real-time monitoring; Real-time systems; Risk levels; Semiconductors; service decision making; system informatics
• ISSN: 1541-1672; 1941-1294
• DOI: 10.1109/MIS.2015.111

This installment of Trends & Controversies provides an array of perspectives on the latest research in system informatics. Kang Zhao, Yao Xie, and Kwok-Leung Tsui introduce the work in "System Informatics: From Methodology to Applications." On the methodology side, in "Projection-Based Process Monitoring and Empirical Divergence," Wenpo Huang, Wei Jiang, Qingming Wei, and Yanting Li propose a framework of projection-based methods, and in "One-Class Classification Methods for Process Monitoring and Diagnosis," Sugon Cho and Seoung Bum Kim discuss how a data analytics algorithm can be used as a control chart. On the application side, "IoT-Enabled System Informatics for Service Decision Making," by Kaibo Liu and Jianjun Shi, reviews current trends and future opportunities for IoT, with a special focus on issues related to the big data collected by multiple sensors. "Quantifying the Risk Level of Functional Chips in DRAM Wafers," by Young-Seon Jeong, Byunghoon Kimb, Seung Hoon Tong, In-Kap Chang, and Myong K. Jeong, not only identifies research challenges and opportunities for decision making with massive data in the process of semiconductor manufacturing but also quantifies the risk level of functional chips in DRAM wafers. Finally, "Flight Operations Monitoring through Cluster Analysis: A Case Study," by Florent Charruaud and Lishuai Li, describes a new method called cluster-based anomaly detection to help airline safety experts monitor daily flights and detect anomalies.