Development of the Adaptive System for Tool Management
Technological developments in the manufacturing industry have accelerated recently. Although many traditional manufacturing factories had adopted automated production, owing to the inability to control the status of individual tools, it is challenging for manufacturers to accurately track the real t...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
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Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek
2023-01-01
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| Series: | Tehnički Vjesnik |
| Subjects: | |
| Online Access: | https://hrcak.srce.hr/file/426088 |
| _version_ | 1827281948404350976 |
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| author | Jenn-Yih Chen Yi-Ling Lin Bean-Yin Lee |
| author_facet | Jenn-Yih Chen Yi-Ling Lin Bean-Yin Lee |
| author_sort | Jenn-Yih Chen |
| collection | DOAJ |
| description | Technological developments in the manufacturing industry have accelerated recently. Although many traditional manufacturing factories had adopted automated production, owing to the inability to control the status of individual tools, it is challenging for manufacturers to accurately track the real time status of production line tools. To bring smart production into existence, a robust database system needs to be ensured. New models of computer numerical control machines are equipped with a built-in tool management system (TMS), but most versions of this system are only able to set a machining time limit or a total number of workpieces limit for each tool to determine tool replacement intervals. Such system could likely cause early tool replacement, resulting in waste and increased tool costs. In order to implement green manufacturing, the prediction of tool wear is essential to reduce wastage of materials. In this study, we developed a TMS that is based on a not only SQL (NoSQL) database, which not only stores several different types of data, but also can store prediction models to make it suitable for the demands of varying enterprise scales. It will be more helpful to ensure processing safety and effectively reduce manufacturing costs. |
| first_indexed | 2024-04-24T09:08:41Z |
| format | Article |
| id | doaj.art-d4e80eea0d9d428198c2b0693f2ef9b8 |
| institution | Directory Open Access Journal |
| issn | 1330-3651 1848-6339 |
| language | English |
| last_indexed | 2024-04-24T09:08:41Z |
| publishDate | 2023-01-01 |
| publisher | Faculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in Osijek |
| record_format | Article |
| series | Tehnički Vjesnik |
| spelling | doaj.art-d4e80eea0d9d428198c2b0693f2ef9b82024-04-15T18:18:51ZengFaculty of Mechanical Engineering in Slavonski Brod, Faculty of Electrical Engineering in Osijek, Faculty of Civil Engineering in OsijekTehnički Vjesnik1330-36511848-63392023-01-0130264865410.17559/TV-20220702054333Development of the Adaptive System for Tool ManagementJenn-Yih Chen0Yi-Ling Lin1Bean-Yin Lee2Department of Mechanical and Computer-Aided Engineering, National Formosa University, Yunlin 632, TaiwanDepartment of Power Mechanical Engineering, National Formosa University, Yunlin 632, TaiwanDepartment of Mechanical and Computer-Aided Engineering, Smart Machinery and Intelligent Manufacturing Research Ceneter, National Formosa University, Yunlin 632, TaiwanTechnological developments in the manufacturing industry have accelerated recently. Although many traditional manufacturing factories had adopted automated production, owing to the inability to control the status of individual tools, it is challenging for manufacturers to accurately track the real time status of production line tools. To bring smart production into existence, a robust database system needs to be ensured. New models of computer numerical control machines are equipped with a built-in tool management system (TMS), but most versions of this system are only able to set a machining time limit or a total number of workpieces limit for each tool to determine tool replacement intervals. Such system could likely cause early tool replacement, resulting in waste and increased tool costs. In order to implement green manufacturing, the prediction of tool wear is essential to reduce wastage of materials. In this study, we developed a TMS that is based on a not only SQL (NoSQL) database, which not only stores several different types of data, but also can store prediction models to make it suitable for the demands of varying enterprise scales. It will be more helpful to ensure processing safety and effectively reduce manufacturing costs.https://hrcak.srce.hr/file/426088group method of data handlingNoSQL databasepolynomial networktool management system |
| spellingShingle | Jenn-Yih Chen Yi-Ling Lin Bean-Yin Lee Development of the Adaptive System for Tool Management Tehnički Vjesnik group method of data handling NoSQL database polynomial network tool management system |
| title | Development of the Adaptive System for Tool Management |
| title_full | Development of the Adaptive System for Tool Management |
| title_fullStr | Development of the Adaptive System for Tool Management |
| title_full_unstemmed | Development of the Adaptive System for Tool Management |
| title_short | Development of the Adaptive System for Tool Management |
| title_sort | development of the adaptive system for tool management |
| topic | group method of data handling NoSQL database polynomial network tool management system |
| url | https://hrcak.srce.hr/file/426088 |
| work_keys_str_mv | AT jennyihchen developmentoftheadaptivesystemfortoolmanagement AT yilinglin developmentoftheadaptivesystemfortoolmanagement AT beanyinlee developmentoftheadaptivesystemfortoolmanagement |