Title :
Cluster analysis of maintenance management problems
Author_Institution :
Fac. of Automotive & Mech. Eng., Changsha Univ. of Sci. & Technol., Changsha, China
Abstract :
Some problems in maintenance management and decision need to classify a set of items into several classes based on some criteria. This paper presents a simple, straightforward and intuitive cluster method to solve such problems. The proposed method is different from but somewhat similar to the K-means approach. The main advantage is that it does not need iteration. Three real-world examples are included to illustrate its appropriateness and usefulness.
Keywords :
maintenance engineering; pattern clustering; K-means approach; cluster analysis; intuitive cluster method; maintenance management problems; straightforward cluster method; Automotive engineering; Clustering methods; Decision making; Engineering management; Inventory management; Iterative methods; Maintenance; Mechanical engineering; Spreadsheet programs; Technology management; Cluster analysis; Maintenance management Partial average; Similarity curve; Statistical classification;
Conference_Titel :
Industrial Engineering and Engineering Management, 2009. IEEM 2009. IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-4869-2
Electronic_ISBN :
978-1-4244-4870-8
DOI :
10.1109/IEEM.2009.5372972
