Client: Dot Incorporation, Seoul, South Korea
Digital Innovation
Siemens Predictive Analytics
SiePA is a predictive analytics system that helps customers to turn collected plant data into valuable insights. Based on the in-depth analysis of historical data via integrated AI, it helps predict potential failures of equipment and processes, identify root causes, search for valuable maintenance experience and suggest preventive measures before the real failures happen. The system integrates plant data monitoring, condition prediction and smart diagnosis, as well as a series of visual analysis tools, in order to simplify the professional data analysis procedure in the form of intuitive and user-friendly tasks.
Credits
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Client:Siemens, Shanghai, China
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Design:Siemens AG / Siemens Ltd. Digital Enterprise Lab (DE-L), Process Automation, Digital Industry, Shanghai, China
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Project Team:Dr. Wu Wenchao (Product Owner) Que Yilin (UX Designer) Li Tian (Developer) Wang Yin (Developer) Tang Qi (Technical Support) Tian Pengwei (Technical Support) Monica Florentina Hildinger (Business Owner) Yue Sheng (Business Owner) Dr. Yao Jun (Supervising Management) Steffen Wagner (Supervising Management)