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Equipment Quality Data Integration and Cleaning Based on Multiterminal Collaboration
Author(s) -
Cuibin Ji,
Guijiang Duan,
Junyan Zhou,
Wei-Jie Xuan
Publication year - 2021
Publication title -
complexity
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.447
H-Index - 61
eISSN - 1099-0526
pISSN - 1076-2787
DOI - 10.1155/2021/5943184
Subject(s) - computer science , quality (philosophy) , data quality , variety (cybernetics) , data integration , xml , data management , architecture , database , systems engineering , data mining , world wide web , engineering , artificial intelligence , operations management , art , metric (unit) , philosophy , epistemology , visual arts
With the advancement of digital manufacturing technology, data-driven quality management is getting more and more attention, and it is developing rapidly under the impetus of technology and management. Quality data are growing exponentially with the help of increasingly interconnected devices and IoT (Internet of Things technologies). Aiming at the problems of insufficient quality data acquisition and poor data quality of complex equipment, the research on quality data integration and cleaning based on digital total quality management is carried out. The data integration architecture of complex equipment quality based on multiterminal collaboration is constructed. The architecture integrates a variety of integration methods and standards, such as XML, OPC-UA, and QIF protocol. Then, to unify the data view, a cleaning method of complex equipment quality data based on the combination of edit distance and longest common subsequence similarity calculation is proposed, and its effectiveness is verified. It provides the basis for the design of the digital total quality management system of complex equipment.

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