EconPapers    
Economics at your fingertips  
 

The customer satisfaction-oriented planning method for redesign parameters of used machine tools

Xingyu Jiang, Boxue Song, Li Li, Mingming Dai and Haoyin Zhang

International Journal of Production Research, 2019, vol. 57, issue 4, 1146-1160

Abstract: Performance recovery is the main emphasis in most remanufactured machine tools, rather than the effective combination of customer requirements (CRs) and redesign processes. Because of this, remanufactured machine tools do not reach their potential competitiveness, highly restricting the implementations to recover used machine tools. To help remedy this, fuzzy nonlinear regression is applied to the fuzzy relationships between CRs and redesign parameters, and the fuzzy correlations among redesign parameters are analysed by fully considering the uncertainties between CRs and redesign parameters. Improved planning equations based on fuzzy nonlinear regression are proposed by injecting fuzziness into the original planning equations. The redesign process of a machine tool is taken as an example to implement the proposed method. The results show that the improved planning equations can obtain higher customer satisfaction compared to the unimproved planning equations. This can provide new thinking to effectively combine CRs and redesign processes.

Date: 2019
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2018.1502483 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1146-1160

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2018.1502483

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:57:y:2019:i:4:p:1146-1160