Monitoring of tool wear and surface roughness in end-milling for intelligent machining
Recently, cutting tool and product quality management in intelligent machining has been implemented by automated tool and quality monitoring and control systems. These systems utilize born features recognized in indirect signals, which reflect, on-line, the tool and quality conditions. In this resea...
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| Format: | Article |
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Academic Journals
2011
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| _version_ | 1796946848638828544 |
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| author | Sarhan, A.A.D. El-Zahry, R.M. |
| author_facet | Sarhan, A.A.D. El-Zahry, R.M. |
| author_sort | Sarhan, A.A.D. |
| collection | UM |
| description | Recently, cutting tool and product quality management in intelligent machining has been implemented by automated tool and quality monitoring and control systems. These systems utilize born features recognized in indirect signals, which reflect, on-line, the tool and quality conditions. In this research work, study was carried out to analyze the dynamic cutting signals of the end-milling process, in order to establish a force based model extracted from these signals, to monitor the end milling tool flank wear and workpiece surface roughness for intelligent machining. Experimental tests in end milling operations are carried out as a case study to verify the results of the proposed force model. The results showed that the proposed force model is an applicable method to predict the tool wear and surface roughness in end milling. |
| first_indexed | 2024-03-06T05:38:02Z |
| format | Article |
| id | um.eprints-15078 |
| institution | Universiti Malaya |
| last_indexed | 2024-03-06T05:38:02Z |
| publishDate | 2011 |
| publisher | Academic Journals |
| record_format | dspace |
| spelling | um.eprints-150782015-12-16T01:07:07Z http://eprints.um.edu.my/15078/ Monitoring of tool wear and surface roughness in end-milling for intelligent machining Sarhan, A.A.D. El-Zahry, R.M. TJ Mechanical engineering and machinery Recently, cutting tool and product quality management in intelligent machining has been implemented by automated tool and quality monitoring and control systems. These systems utilize born features recognized in indirect signals, which reflect, on-line, the tool and quality conditions. In this research work, study was carried out to analyze the dynamic cutting signals of the end-milling process, in order to establish a force based model extracted from these signals, to monitor the end milling tool flank wear and workpiece surface roughness for intelligent machining. Experimental tests in end milling operations are carried out as a case study to verify the results of the proposed force model. The results showed that the proposed force model is an applicable method to predict the tool wear and surface roughness in end milling. Academic Journals 2011-05 Article PeerReviewed Sarhan, A.A.D. and El-Zahry, R.M. (2011) Monitoring of tool wear and surface roughness in end-milling for intelligent machining. International Journal of the Physical Sciences, 6 (10). pp. 2380-2392. ISSN 1992-1950, DOI https://doi.org/10.5897/IJPS10.577 <https://doi.org/10.5897/IJPS10.577>. http://www.academicjournals.org/journal/IJPS/article-abstract/0C95BCC23849 DOI: 10.5897/IJPS10.577 |
| spellingShingle | TJ Mechanical engineering and machinery Sarhan, A.A.D. El-Zahry, R.M. Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title | Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title_full | Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title_fullStr | Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title_full_unstemmed | Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title_short | Monitoring of tool wear and surface roughness in end-milling for intelligent machining |
| title_sort | monitoring of tool wear and surface roughness in end milling for intelligent machining |
| topic | TJ Mechanical engineering and machinery |
| work_keys_str_mv | AT sarhanaad monitoringoftoolwearandsurfaceroughnessinendmillingforintelligentmachining AT elzahryrm monitoringoftoolwearandsurfaceroughnessinendmillingforintelligentmachining |