Tool wear in cutting operations: Experimental analysis and analytical models

Journal of Manufacturing Science and Engineering

Volumn 135, Issue 5, 2013, Pages

  Attanasio, A ^a   Ceretti, E ^a   Giardini, C ^b   Cappellini, C ^a  

^a UNIVERSITY OF BRESCIA   (Italy)

^b UNIVERSITY OF BERGAMO   (Italy)

Author keywords

Artificial neural networks; Cutting operations; Multidimensional regression; Tool wear

Indexed keywords

COSTS; FORECASTING; NEURAL NETWORKS; PREDICTIVE ANALYTICS; TURNING; WEAR OF MATERIALS;

CUTTING OPERATIONS; CUTTING PARAMETERS; EXPERIMENTAL ANALYSIS; EXPERIMENTAL VALUES; LONGITUDINAL TURNING; MULTIDIMENSIONAL REGRESSION; RESPONSE SURFACE METHODOLOGY; TOOL WEAR;

CUTTING TOOLS;

EID: 84888881165     PISSN: 10871357     EISSN: 15288935     Source Type: Journal    
DOI: 10.1115/1.4025010     Document Type: Article

References (24)

1. Childs, T. H. C., Maekawa, K., Obikawa, T., and Yamane, Y., 2000, Metal Machining: Theory and Applications, 1st ed., Butterworth-Heinemann, Washington, DC.
2. Grzesik, W., 2008, "Influence of Tool Wear on Surface Roughness in Hard Turning Using Differently Shaped Ceramic Tools," Wear, 265, pp. 327-335.
3. Tang, Z. T., Liu, Z. Q., Pan, Y. Z., Wan, Y. Z., and Ai, X., 2009, "The Influence of Tool Flank Wear on Residual Stresses Induced by Milling Aluminum Alloy," J. Mater. Process. Technol., 209, pp. 4502-4508.
4. Liu, M., Takagi, J., and Tsukuda, A., 2004, "Effect of Tool Nose Radius and Tool Wear on Residual Stress Distribution in Hard Turning of Bearing Steel," J. Mater. Process. Technol., 150, pp. 234-241.
5. Lin, Z. C., and Lee, B. Y., 1995, "An Investigation of the Residual Stress of a Machined Workpiece Considering Tool Flank Wear," J. Mater. Process. Technol., 51, pp. 1-24.
6. Chou, Y. K., 2002, "Surface Hardening of AISI 4340 Steel by Machining: A Preliminary Investigation," J. Mater. Process. Technol., 124, pp. 171-177.
7. Mukherjee, I., and Ray, P. K., 2006, "A Review of Optimization Techniques in Metal Cutting Processes," Comput. Ind. Eng., 50, pp. 15-34. (Pubitemid 43816785)
8. Montgomery, D. C., 1997, Design and Analysis of Experiments, 5th ed., John Wiley & Sons, New York.
9. Van Luttervelt, C. A., Childs, T. H. C., Jawahir, I. S., Klocke, F., Venuvinod, P. K., Altintas, Y., Armarego, E., Dornfeld, D., Grabec, I., Leopold, J., Lindstrom, B., Lucca, D., Obikawa, T., Shirakashi, and Sato, H., 1998, "Present Situation and Future Trends in Modelling of Machining Operations Progress Report of the CIRP Working Group Modelling of Machining Operations," CIRP Ann., 46(2), pp. 587-626.
10. Bhushan, R. K., 2013, "Multiresponse Optimization of Al Alloy-SiC Composite Machining Parameters for Minimum Tool Wear and Maximum Metal Removal Rate," ASME J. Manuf. Sci. Eng., 135(2), p. 021013.
11. Novak, A., and Wiklund, H., 1993, "Reliability Improvement of Tool-Wear Monitoring," CIRP Ann., 42(1), pp. 63-66. (Pubitemid 23679088)
12. Kadirgama, K., Abou-El-Hossein, K. A., Noor, M. M., Sharma, K. V., and Mohammad, B., 2011, "Tool Life and Wear Mechanism When Machining Hastelloy C-22HS," Wear, 270, pp. 258-268.
13. Poulachon, G., Dessoly, M., Le Calvez, C., Le Brun, J. L., Prunet, V., and Jawahir, I. S., 2001, "An Investigation of the Influence of Sulphide Inclusions on Tool-Wear in High Speed Milling of Tool Steels," Wear, 250, pp. 334-343. (Pubitemid 33050455)
14. Alauddin, M., El Baradic, M. A., and Hashmi, M. S. J., 1997, "Prediction of Tool Life in End Milling by Response Surface Methodology," J. Mater. Process. Technol., 71, pp. 456-465. (Pubitemid 127379859)
15. Colding, B. N., 2000, "Prediction, Optimization and Functional Requirements of Knowledge Based Systems," CIRP Ann., 49(1), pp. 351-354.
16. Noordin, M. Y., Venkatesh, V. C., Sharif, S., Elting, S., and Abdullah, A., 2004, "Application of Response Surface Methodology in Describing the Performance of Coated Carbide Tools When Turning AISI 1045 Steel," J. Mater. Process. Technol., 145, pp. 46-58.
17. Mashal, Y. A. H., El-Axir, M. H., and Kassem, M. A., 2001, "The Machinability and Tribological Characteristics of Aluminum Alloys With Improved Elevated Temperature Properties Using Rapidly Solidified Powder," Wear, 250, pp. 518-528. (Pubitemid 33050464)
18. Attanasio, A., Cappellini, C., Ceretti, E., and Giardini, C., 2010, "Tool Wear Evaluation by Means of Artificial Neural Networks in Turning," Proceedings of CIRP-ICME, Prof. Teti, ed., Capri, Italy, on CD.
19. Ezugwum, E. O., Arthur, S. J., and Hines, E. L., 1995, "Tool Wear Prediction Using Artificial Neural Networks," J. Mater. Process. Technol., 49, pp. 255-264.
20. Cetinel, H., Ozturk, H., Celik, E., and Karlik, B., 2006, "Artificial Neural Network-Based Prediction Technique for Wear Loss Quantities in Mo Coatings," Wear, 261, pp. 1064-1068. (Pubitemid 44755079)
21. Das, S., Roy, R., and Chattopadhyay, A. B., 1996, "Evaluation of Wear of Turning Carbide Insert Using Neural Networks," Int. J. Mach. Tools Manuf., 36(7), pp. 789-797. (Pubitemid 126370649)
22. Das, S., Bandyopadhyay, P. P., and Chattopadhyay, A. B., 1997, "Neural Networks Based Tool Wear Monitoring in Turning Medium Carbon Steel Using a Coated Carbide Tool," J. Mater. Process. Technol., 63, pp. 187-192. (Pubitemid 127384858)
23. Murray, W., 1972, Numerical Methods for Unconstrained Optimization, Academic, New York.
24. Bronshtein, I. N., Semendyayev, K. A., Musiol, G., and Muehlig, H., 2007, Handbook of Mathematics, 5th ed., Springer, New York.