Novel and cost-effective CNC tool condition monitoring through image processing techniques
Abstract CNC machining is an important part of the manufacturing industry. This paper introduces a novel and efficient approach for tool condition monitoring in CNC machine operations through the application of image processing techniques. By utilizing a consumer-grade camera capable of recording vi...
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| Format: | Article |
| Language: | English |
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Springer
2025-01-01
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| Series: | Discover Applied Sciences |
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| Online Access: | https://doi.org/10.1007/s42452-024-06200-w |
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| _version_ | 1841544386014347264 |
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| author | Alireza Falah Mátyás Andó |
| author_facet | Alireza Falah Mátyás Andó |
| author_sort | Alireza Falah |
| collection | DOAJ |
| description | Abstract CNC machining is an important part of the manufacturing industry. This paper introduces a novel and efficient approach for tool condition monitoring in CNC machine operations through the application of image processing techniques. By utilizing a consumer-grade camera capable of recording videos at 60 frames per second, the study demonstrates a cost-effective method to detect tool breakage and identify edge fractures. Basic image processing techniques, including frame extraction, background subtraction, thresholding, and morphological operations, are applied to analyze captured images and videos. This research not only offers a practical solution to enhance the efficiency and accuracy of CNC machine operations but also aligns with advancements in smart manufacturing and Industry 4.0. The findings will showcase the proposed system’s effectiveness in actual CNC machine environments, underscoring its potential to enhance maintenance strategies and operational productivity for small and medium-sized manufacturers without incurring high costs. Furthermore, it sets the stage for future investigations in this domain, indicating the possibility for enhancements through machine learning and an expanded application of these monitoring techniques. |
| format | Article |
| id | doaj-art-c4d7d7b6dee940448823bee80da50733 |
| institution | Kabale University |
| issn | 3004-9261 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Springer |
| record_format | Article |
| series | Discover Applied Sciences |
| spelling | doaj-art-c4d7d7b6dee940448823bee80da507332025-01-12T12:35:03ZengSpringerDiscover Applied Sciences3004-92612025-01-017111310.1007/s42452-024-06200-wNovel and cost-effective CNC tool condition monitoring through image processing techniquesAlireza Falah0Mátyás Andó1Faculty of Informatics, ELTE Eötvös Loránd UniversityFaculty of Informatics, ELTE Eötvös Loránd UniversityAbstract CNC machining is an important part of the manufacturing industry. This paper introduces a novel and efficient approach for tool condition monitoring in CNC machine operations through the application of image processing techniques. By utilizing a consumer-grade camera capable of recording videos at 60 frames per second, the study demonstrates a cost-effective method to detect tool breakage and identify edge fractures. Basic image processing techniques, including frame extraction, background subtraction, thresholding, and morphological operations, are applied to analyze captured images and videos. This research not only offers a practical solution to enhance the efficiency and accuracy of CNC machine operations but also aligns with advancements in smart manufacturing and Industry 4.0. The findings will showcase the proposed system’s effectiveness in actual CNC machine environments, underscoring its potential to enhance maintenance strategies and operational productivity for small and medium-sized manufacturers without incurring high costs. Furthermore, it sets the stage for future investigations in this domain, indicating the possibility for enhancements through machine learning and an expanded application of these monitoring techniques.https://doi.org/10.1007/s42452-024-06200-wCNC tool monitoringImage processingMachine visionSmart manufacturingPredictive maintenance |
| spellingShingle | Alireza Falah Mátyás Andó Novel and cost-effective CNC tool condition monitoring through image processing techniques Discover Applied Sciences CNC tool monitoring Image processing Machine vision Smart manufacturing Predictive maintenance |
| title | Novel and cost-effective CNC tool condition monitoring through image processing techniques |
| title_full | Novel and cost-effective CNC tool condition monitoring through image processing techniques |
| title_fullStr | Novel and cost-effective CNC tool condition monitoring through image processing techniques |
| title_full_unstemmed | Novel and cost-effective CNC tool condition monitoring through image processing techniques |
| title_short | Novel and cost-effective CNC tool condition monitoring through image processing techniques |
| title_sort | novel and cost effective cnc tool condition monitoring through image processing techniques |
| topic | CNC tool monitoring Image processing Machine vision Smart manufacturing Predictive maintenance |
| url | https://doi.org/10.1007/s42452-024-06200-w |
| work_keys_str_mv | AT alirezafalah novelandcosteffectivecnctoolconditionmonitoringthroughimageprocessingtechniques AT matyasando novelandcosteffectivecnctoolconditionmonitoringthroughimageprocessingtechniques |