Alborz Shokrani , Hakan Dogan , David Burian , Tobechukwu D. Nwabueze , Petr Kolar , Zhirong Liao , Ahmad Sadek , Roberto Teti , Peng Wang , Radu Pavel , Tony Schmitz
{"title":"用于加工过程和机上监控的传感器","authors":"Alborz Shokrani , Hakan Dogan , David Burian , Tobechukwu D. Nwabueze , Petr Kolar , Zhirong Liao , Ahmad Sadek , Roberto Teti , Peng Wang , Radu Pavel , Tony Schmitz","doi":"10.1016/j.cirpj.2024.05.001","DOIUrl":null,"url":null,"abstract":"<div><p>Machining is extensively used for producing functional parts in various industries such as aerospace, automotive, energy, etc. There is a growing demand for improved part quality and performance at lower costs from increasingly difficult-to-machine materials. Whilst modern machine tools are equipped with sensors for closed loop control of their axes’ movements and position, they provide minimal information regarding the cutting performance and tool condition. The integration of additional sensors into cutting tools, machine tools and/or their components can provide an insight into the machining performance. It also provides an opportunity to improve the machining process and reduce the need for post-process inspection and rework. This paper presents a comprehensive analysis of various sensors utilised for in-process and on-machine measurement and monitoring of machining performance parameters such as cutting forces, vibrations, tool wear, surface integrity, etc. Data transfer and communication methods, as well as power supply options for sensor-integrated systems are also investigated. Sensor integrated machining systems can potentially improve machining performance and part quality by early detection of errors and damages, maximising tool usage and preventing machining and tool wear induced damages. A combination of sensor data collection and intelligent sensor signal processing can further increase the capabilities of sensor integrated systems from process monitoring to active process control.</p></div>","PeriodicalId":56011,"journal":{"name":"CIRP Journal of Manufacturing Science and Technology","volume":"51 ","pages":"Pages 263-292"},"PeriodicalIF":4.6000,"publicationDate":"2024-05-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.sciencedirect.com/science/article/pii/S1755581724000592/pdfft?md5=8f24ed247563f32646015faf8d5d5189&pid=1-s2.0-S1755581724000592-main.pdf","citationCount":"0","resultStr":"{\"title\":\"Sensors for in-process and on-machine monitoring of machining operations\",\"authors\":\"Alborz Shokrani , Hakan Dogan , David Burian , Tobechukwu D. Nwabueze , Petr Kolar , Zhirong Liao , Ahmad Sadek , Roberto Teti , Peng Wang , Radu Pavel , Tony Schmitz\",\"doi\":\"10.1016/j.cirpj.2024.05.001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Machining is extensively used for producing functional parts in various industries such as aerospace, automotive, energy, etc. There is a growing demand for improved part quality and performance at lower costs from increasingly difficult-to-machine materials. Whilst modern machine tools are equipped with sensors for closed loop control of their axes’ movements and position, they provide minimal information regarding the cutting performance and tool condition. The integration of additional sensors into cutting tools, machine tools and/or their components can provide an insight into the machining performance. It also provides an opportunity to improve the machining process and reduce the need for post-process inspection and rework. This paper presents a comprehensive analysis of various sensors utilised for in-process and on-machine measurement and monitoring of machining performance parameters such as cutting forces, vibrations, tool wear, surface integrity, etc. Data transfer and communication methods, as well as power supply options for sensor-integrated systems are also investigated. Sensor integrated machining systems can potentially improve machining performance and part quality by early detection of errors and damages, maximising tool usage and preventing machining and tool wear induced damages. A combination of sensor data collection and intelligent sensor signal processing can further increase the capabilities of sensor integrated systems from process monitoring to active process control.</p></div>\",\"PeriodicalId\":56011,\"journal\":{\"name\":\"CIRP Journal of Manufacturing Science and Technology\",\"volume\":\"51 \",\"pages\":\"Pages 263-292\"},\"PeriodicalIF\":4.6000,\"publicationDate\":\"2024-05-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.sciencedirect.com/science/article/pii/S1755581724000592/pdfft?md5=8f24ed247563f32646015faf8d5d5189&pid=1-s2.0-S1755581724000592-main.pdf\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"CIRP Journal of Manufacturing Science and Technology\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1755581724000592\",\"RegionNum\":2,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, MANUFACTURING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"CIRP Journal of Manufacturing Science and Technology","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1755581724000592","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
Sensors for in-process and on-machine monitoring of machining operations
Machining is extensively used for producing functional parts in various industries such as aerospace, automotive, energy, etc. There is a growing demand for improved part quality and performance at lower costs from increasingly difficult-to-machine materials. Whilst modern machine tools are equipped with sensors for closed loop control of their axes’ movements and position, they provide minimal information regarding the cutting performance and tool condition. The integration of additional sensors into cutting tools, machine tools and/or their components can provide an insight into the machining performance. It also provides an opportunity to improve the machining process and reduce the need for post-process inspection and rework. This paper presents a comprehensive analysis of various sensors utilised for in-process and on-machine measurement and monitoring of machining performance parameters such as cutting forces, vibrations, tool wear, surface integrity, etc. Data transfer and communication methods, as well as power supply options for sensor-integrated systems are also investigated. Sensor integrated machining systems can potentially improve machining performance and part quality by early detection of errors and damages, maximising tool usage and preventing machining and tool wear induced damages. A combination of sensor data collection and intelligent sensor signal processing can further increase the capabilities of sensor integrated systems from process monitoring to active process control.
期刊介绍:
The CIRP Journal of Manufacturing Science and Technology (CIRP-JMST) publishes fundamental papers on manufacturing processes, production equipment and automation, product design, manufacturing systems and production organisations up to the level of the production networks, including all the related technical, human and economic factors. Preference is given to contributions describing research results whose feasibility has been demonstrated either in a laboratory or in the industrial praxis. Case studies and review papers on specific issues in manufacturing science and technology are equally encouraged.