Intelligent Tapping Machine: Tap Geometry Inspection
Currently, the majority of industrial metal processing involves the use of taps for cutting. However, existing tap machines require relocation to specialized inspection stations and only assess the condition of the cutting edges for defects. They do not evaluate the quality of the cutting angles and...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
MDPI AG
2023-09-01
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| Series: | Sensors |
| Subjects: | |
| Online Access: | https://www.mdpi.com/1424-8220/23/18/8005 |
| _version_ | 1827723466855415808 |
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| author | En-Yu Lin Ju-Chin Chen Jenn-Jier James Lien |
| author_facet | En-Yu Lin Ju-Chin Chen Jenn-Jier James Lien |
| author_sort | En-Yu Lin |
| collection | DOAJ |
| description | Currently, the majority of industrial metal processing involves the use of taps for cutting. However, existing tap machines require relocation to specialized inspection stations and only assess the condition of the cutting edges for defects. They do not evaluate the quality of the cutting angles and the amount of removed material. Machine vision, a key component of smart manufacturing, is commonly used for visual inspection. Taps are employed for processing various materials. Traditional tap replacement relies on the technician’s accumulated empirical experience to determine the service life of the tap. Therefore, we propose the use of visual inspection of the tap’s external features to determine whether replacement or regrinding is needed. We examined the bearing surface of the tap and utilized single images to identify the cutting angle, clearance angle, and cone angles. By inspecting the side of the tap, we calculated the wear of each cusp. This inspection process can facilitate the development of a tap life system, allowing for the estimation of the durability and wear of taps and nuts made of different materials. Statistical analysis can be employed to predict the lifespan of taps in production lines. Experimental error is 16 μm. Wear from tapping 60 times is equivalent to 8 s of electric grinding. We have introduced a parameter, thread removal quantity, which has not been proposed by anyone else. |
| first_indexed | 2024-03-10T22:01:09Z |
| format | Article |
| id | doaj.art-281d7aca43f248de8024172676236a4e |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-10T22:01:09Z |
| publishDate | 2023-09-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-281d7aca43f248de8024172676236a4e2023-11-19T12:57:20ZengMDPI AGSensors1424-82202023-09-012318800510.3390/s23188005Intelligent Tapping Machine: Tap Geometry InspectionEn-Yu Lin0Ju-Chin Chen1Jenn-Jier James Lien2Department of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, TaiwanDepartment of Computer Science and Information Engineering, National Kaohsiung University of Science and Technology, Kaohsiung 807, TaiwanDepartment of Computer Science and Information Engineering, National Cheng Kung University, Tainan 701, TaiwanCurrently, the majority of industrial metal processing involves the use of taps for cutting. However, existing tap machines require relocation to specialized inspection stations and only assess the condition of the cutting edges for defects. They do not evaluate the quality of the cutting angles and the amount of removed material. Machine vision, a key component of smart manufacturing, is commonly used for visual inspection. Taps are employed for processing various materials. Traditional tap replacement relies on the technician’s accumulated empirical experience to determine the service life of the tap. Therefore, we propose the use of visual inspection of the tap’s external features to determine whether replacement or regrinding is needed. We examined the bearing surface of the tap and utilized single images to identify the cutting angle, clearance angle, and cone angles. By inspecting the side of the tap, we calculated the wear of each cusp. This inspection process can facilitate the development of a tap life system, allowing for the estimation of the durability and wear of taps and nuts made of different materials. Statistical analysis can be employed to predict the lifespan of taps in production lines. Experimental error is 16 μm. Wear from tapping 60 times is equivalent to 8 s of electric grinding. We have introduced a parameter, thread removal quantity, which has not been proposed by anyone else.https://www.mdpi.com/1424-8220/23/18/8005taptappingcutting angleclearance anglecone angleslength of the tool |
| spellingShingle | En-Yu Lin Ju-Chin Chen Jenn-Jier James Lien Intelligent Tapping Machine: Tap Geometry Inspection Sensors tap tapping cutting angle clearance angle cone angles length of the tool |
| title | Intelligent Tapping Machine: Tap Geometry Inspection |
| title_full | Intelligent Tapping Machine: Tap Geometry Inspection |
| title_fullStr | Intelligent Tapping Machine: Tap Geometry Inspection |
| title_full_unstemmed | Intelligent Tapping Machine: Tap Geometry Inspection |
| title_short | Intelligent Tapping Machine: Tap Geometry Inspection |
| title_sort | intelligent tapping machine tap geometry inspection |
| topic | tap tapping cutting angle clearance angle cone angles length of the tool |
| url | https://www.mdpi.com/1424-8220/23/18/8005 |
| work_keys_str_mv | AT enyulin intelligenttappingmachinetapgeometryinspection AT juchinchen intelligenttappingmachinetapgeometryinspection AT jennjierjameslien intelligenttappingmachinetapgeometryinspection |