Statistics Pattern Analysis: A Statistical Process Monitoring Tool for Smart Manufacturing
作者： Q. Peter He , Jin Wang
DOI: 10.1016/B978-0-444-64241-7.50340-2
关键词: Smart manufacturing 、 Component (UML) 、 Statistical process monitoring 、 Statistics 、 Pattern analysis 、 Big data 、 Process (engineering) 、 Computer science
摘要: Abstract Statistical process monitoring (SPM) is an important component in the long-term reliable operation of any system and its importance can only become greater era smart manufacturing (SM). Previously we proposed statistics pattern analysis (SPA) based on idea using various to quantify characteristics, these instead variables themselves perform monitoring. In this work examine SPA’s capability handling characteristics including dynamics, nonlinearity data non-Gaussianity, compare performance representative state-of-the-art SPM methods. addition, discuss how SPA help address new challenges presented by big data.
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