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http://dx.doi.org/10.7735/ksmte.2012.21.1.033

A Study on the Tool Wear and Surface Roughness in Cutting Processes for a Neural-Network-Based Remote Monitoring system  

Kwon, Jung-Hee (창원대학교 대학원 기계설계공학과)
Jang, U-Il (창원대학교 대학원 기계설계공학과)
Jeong, Seong-Hyun (창원대학교 대학원 기계설계공학과)
Kim, Do-Un (창원대학교 대학원 기계설계공학과)
Hong, Dae-Sun (창원대학교 메카트로닉스공학부)
Publication Information
Journal of the Korean Society of Manufacturing Technology Engineers / v.21, no.1, 2012 , pp. 33-39 More about this Journal
Abstract
The tool wear and failure in automatic production system directly influences the quality and productivity of a product, thus it is essential to monitor the tool state in real time. For such purpose, an ART2-based remote monitoring system has been developed to predict the appropriate tool change time in accordance with the tool wear, and this study aims to experimently find the relationship between the tool wear and the monitoring signals in cutting processes. Also, the roughness of workpiece according to the wool wear is examined. Here, the tool wear is indirectly monitored by signals from a vibration senor attached to a machining center. and the wear dimension is measured by a microscope at the start, midways and the end of a cutting process. A series of experiments are carried out with various feedrates and spindle speeds, and the results show that the sensor signal properly represents the degree of wear of a tool being used, and the roughnesses measured has direct relation with the tool wear dimension. Thus, it is concluded that the monitoring signals from the vibration sensor can be used as a useful measure for the tool wear monitoring.
Keywords
Tool wear; Remote monitoring; Vibration sensor; ART2; Surface roughness;
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