A Comparative Study of I-kaz Based Signal Analysis Techniques: Application to Detect Tool Wear during Turning Process

Authors

  • Muhammad Rizal Department of Mechanical Engineering, Faculty of Engineering, Syiah Kuala University, 23111 Darussalam, Banda Aceh, Indonesia
  • Jaharah A. Ghani Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • Mohd Zaki Nuawi Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • Mohamad Amir Shafiq r Mohd Tahir Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia
  • Che Hassan Che Haron Department of Mechanical and Materials Engineering, Faculty of Engineering and Built Environment, Universiti Kebangsaan Malaysia, 43600 Bangi, Selangor, Malaysia

DOI:

https://doi.org/10.11113/jt.v66.2704

Keywords:

Tool wear detection, I-kaz method, cutting force, turning process

Abstract

Detection of tool wear during in-progress machining process is a significant requirement to assure the quality of machined parts that helps to improve the productivity. The cutting force is one of the signals in machining process that has been widely used for tool wear monitoring. In the present paper three derived I-kazTM based methods explained and compared for monitoring tool wear changes during turning process. The aim of this work is to study the performance of I-kazTM, I-kaz 2D and I-kaz Multilevel techniques to detect flank wear width using the cutting force signal. The experiments were carried out by turning hardened carbon steel, and cutting force signals were measured by two channels of strain gauges that were mounted on the surface of tool holder. The analysis of results using I-kaz 2D, I-kazTM and also I-kaz Multilevel methods, revealed that all methods can applied to determine tool wear progression during turning process and feed force signal change is very significant due to flank wear.

References

Dimla, D. E., & P. M. Lister. 2000.Int. J. Mach. Tools & Manufact. 40: 739.

Teti, R., K. Jemielniak, G. O’Donnell, & D. Dornfeld. 2010. CIRP Ann.–Manuf. Technol. 59: 717.

Jemielniak, K., L, Kwiatkowski, & P. Wrzosek. 1998. J. Intell. Manuf. 9: 447.

Das, S., A. B. Chattopadhyay, & A. S. R. Murthy. 1996. Neural Nets. 9: 1639.

Chungchoo, C. & D. Saini. 2002. Int. J. Mach. Tools & Manufact, 42: 29.

Abdullah, S., N. Ismail, M. Z. Nuawi, Z. M. Nopiah, & M. N. Baharin. 2009. Int. Conf. Signal Proc. Sys., IEEE. 989.

Mansor, N. I. I., M. J. Ghazali, M. Z. Nuawi, & S. E. M. Kamal. 2009. Int. J. Mech. Mater. Eng. 4: 152.

Nuawi, M. Z., F. Lamin, M. J. M. Nor, N. Jamaluddin, S. Abdullah, & C. K. E. Nizwan. 2007. Int. J. Mech. 4: 44.

Karim, Z., H. A. R. Izatul, S.A.S. Azuan, S. Mastura, A. Y. M. Said, A. R. Bahari, J. A. Ghani, & M. Z. Nuawi. 2013. Aust. J. BasicAppl. Sci. 7(4): 94.

Ghani, J. A., M. Rizal, M. Z. Nuawi, C. H. C. Haron, M. J. Ghazali, & M. N. A. Rahman. 2010. Adv. Mater. Res. 126–128: 738.

Ghani, J. A., M. Rizal, M. Z. Nuawi, M. J. Ghazali, & C. H. C. Haron. 2011. Wear. 271: 2619.

Ghani, J. A., M. Rizal, M. Z. Nuawi, & C. H. C. Haron. 2012. Adv. Sci. Lett. 13: 702.

Rizal, M., J. A. Ghani, M. Z. Nuawi, & C. H. C. Haron. 2013. Appl. Soft Comput. 13: 1960.

Nuawi, M. Z., F. Lamin, M. J. M. Nor, N. Jamaluddin, S. Abdullah, & C. K. E. Nizwan. 2008. J. Appl. Sci. 8: 1541.

Ghani, J. A., P. S. Jye, C. H. C. Haron, M. Rizal, & M. Z. Nuawi. 2012. J. Teknol. (Sci. & Eng.). 59(2): 91.

Rizal, M. 2011. Development of an Online Cutting Tool Wear Monitoring System using Strain Gauge in Turning Process. MSc-Thesis. Bangi: Malaysia.

Bhattacharyya, P., D. Sengupta, & S. Mukhopadhyay. 2007. Mech. Sys. Signal Proc. 21: 2665.

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Published

2013-02-15

Issue

Vol. 66 No. 3: Special Issue on Recent Research in Tribology

Section

Science and Engineering

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Copyright of articles that appear in Jurnal Teknologi belongs exclusively to Penerbit Universiti Teknologi Malaysia (Penerbit UTM Press). This copyright covers the rights to reproduce the article, including reprints, electronic reproductions, or any other reproductions of similar nature.

How to Cite

A Comparative Study of I-kaz Based Signal Analysis Techniques: Application to Detect Tool Wear during Turning Process. (2013). Jurnal Teknologi (Sciences & Engineering), 66(3). https://doi.org/10.11113/jt.v66.2704