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Statistical monitoring and decision-making of tool wear processes
National University of Singapore, Singapore.
National University of Singapore, Singapore.
Standard Chartered Bank, Singapore.
2000 (English)In: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 7, no 4, 331-340 p.Article in journal (Refereed) Published
Abstract [en]

Statistical control charts have been successfully used in industry for monitoring stable processes. However, processes with uncontrollable but acceptable trend are common in practice. One typical example is the wear process of cutting tools. Conventional control charts may not serve the purpose of process monitoring. In this paper, a forecast-based technique using Double Exponential Smoothing is proposed. It eliminates the trend component, and control charts are applied to the residuals. Furthermore, a procedure based on double control lines is suggested and adopted in tool wear process monitoring to integrate statistical and engineering properties for better decision making on tool wear-out. Other than the monitoring of tool wear process, the method can be used for better monitoring of other processes with trend. An actual tool wear data set is used as illustration.

Place, publisher, year, edition, pages
2000. Vol. 7, no 4, 331-340 p.
Keyword [en]
Tool wear, Quality Technology and Management, TQM, Quality control
Keyword [sv]
Kvalitetsteknik, Kvalitet
National Category
Other Mechanical Engineering
Identifiers
URN: urn:nbn:se:miun:diva-2968Scopus ID: 2-s2.0-33749625608Local ID: 2712OAI: oai:DiVA.org:miun-2968DiVA: diva2:28000
Available from: 2008-09-30 Created: 2008-09-30 Last updated: 2016-09-29Bibliographically approved

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Wiklund, Håkan
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Citation style
  • apa
  • harvard1
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