主催: 一般社団法人 日本機械学会
会議名: 2017年度 年次大会
開催日: 2017/09/03 - 2017/09/06
Monitoring, analytical, and guidance and control technologies are required in intelligent machine tools. To meet the required machining accuracy of a product, the cutting process is monitored, and information such as tool wear is detected and analyzed using the three technologies previously introduced. Based on the analysis result, changes can then be made to the cutting conditions, the tool diameter correction amount, and the tool itself. In this study, an attempt was made to detect the tool wear state by monitoring the cutting state with an on-measurement system using the acoustic emission (AE) method. During the experiment, cutting resistance, surface roughness, and wear of the cutting edge of the tool were measured. In addition, the relationship between these measurements and the AE signal was investigated. As a result, findings on the relationship between AE signal and tool wear can be reported.