{"title":"基于LabVIEW的数控车床刀具状态监测与控制","authors":"Sanket Bhagat, S. Nalbalwar","doi":"10.1109/RTEICT.2016.7808058","DOIUrl":null,"url":null,"abstract":"Tool Condition Monitoring is very fundamental part of the Manufacturing industry similar to the automation and hence has a great importance in research based on manufacturing engineering. Many of the people those concern with the manufacturing industries are interestedly study the TCM as successful unmanned automation in production is only possible if there is presence of good tool wear monitor and tool breakage detection system. So that reliability of the production system can be increased significantly. The tool wear can also affect the quality of surface finish of work piece and dimension of the manufactured parts which further decides the quality of final product. This need has raised quite a large interest among researchers and frequent users and learners. Tool Condition is done by employing various methods but all are not able to give successful result due to complexity in parameter variation in the machining process. Only few of them are globally accepted, studied and used worldwide. This paper concerns about some useful and efficient methods of TCM (Tool Condition Monitoring). An integrated approach of tool condition monitoring and control together with the data acquisition of different parameters is proposed. And to inspect tool wear condition different sensors are used for signal measurement.","PeriodicalId":6527,"journal":{"name":"2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","volume":"41 1","pages":"1386-1388"},"PeriodicalIF":0.0000,"publicationDate":"2016-05-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"LabVIEW based tool condition monitoring and control for CNC lathe based on parameter analysis\",\"authors\":\"Sanket Bhagat, S. Nalbalwar\",\"doi\":\"10.1109/RTEICT.2016.7808058\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Tool Condition Monitoring is very fundamental part of the Manufacturing industry similar to the automation and hence has a great importance in research based on manufacturing engineering. Many of the people those concern with the manufacturing industries are interestedly study the TCM as successful unmanned automation in production is only possible if there is presence of good tool wear monitor and tool breakage detection system. So that reliability of the production system can be increased significantly. The tool wear can also affect the quality of surface finish of work piece and dimension of the manufactured parts which further decides the quality of final product. This need has raised quite a large interest among researchers and frequent users and learners. Tool Condition is done by employing various methods but all are not able to give successful result due to complexity in parameter variation in the machining process. Only few of them are globally accepted, studied and used worldwide. This paper concerns about some useful and efficient methods of TCM (Tool Condition Monitoring). An integrated approach of tool condition monitoring and control together with the data acquisition of different parameters is proposed. And to inspect tool wear condition different sensors are used for signal measurement.\",\"PeriodicalId\":6527,\"journal\":{\"name\":\"2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"volume\":\"41 1\",\"pages\":\"1386-1388\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-05-20\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/RTEICT.2016.7808058\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 IEEE International Conference on Recent Trends in Electronics, Information & Communication Technology (RTEICT)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/RTEICT.2016.7808058","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
LabVIEW based tool condition monitoring and control for CNC lathe based on parameter analysis
Tool Condition Monitoring is very fundamental part of the Manufacturing industry similar to the automation and hence has a great importance in research based on manufacturing engineering. Many of the people those concern with the manufacturing industries are interestedly study the TCM as successful unmanned automation in production is only possible if there is presence of good tool wear monitor and tool breakage detection system. So that reliability of the production system can be increased significantly. The tool wear can also affect the quality of surface finish of work piece and dimension of the manufactured parts which further decides the quality of final product. This need has raised quite a large interest among researchers and frequent users and learners. Tool Condition is done by employing various methods but all are not able to give successful result due to complexity in parameter variation in the machining process. Only few of them are globally accepted, studied and used worldwide. This paper concerns about some useful and efficient methods of TCM (Tool Condition Monitoring). An integrated approach of tool condition monitoring and control together with the data acquisition of different parameters is proposed. And to inspect tool wear condition different sensors are used for signal measurement.