An investigation of burr formation and cutting parameter optimization in micro-drilling of brass C-360 using image processing

Shashank Pansari, Ansu Mathew, Aniket Nargundkar

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A lot of research has been done in area of conventional micro-drilling but the measurement techniques for measuring burr size and holes circularity were either very expensive or inaccurate. This paper attempts to investigate role of input parameters like the spindle speed and the feed rate on burr height and burr thickness at hole exit for Brass C-360, which is a widely used material in micro-fabrication. The measurements were taken from scanning electron microscope (SEM) images of micro-drilled holes using image processing which makes the measurement simple, fast, and accurate. All the experiments were conducted using response surface methodology to develop second-order polynomial models for burr thickness and height of burr. Optimization by using multi-objective genetic algorithm and cohort intelligence algorithm using MATLAB is done to generate optimum output results. All the micro-hole SEM images were analyzed to detect the types of burrs formed during different experiments.

Original languageEnglish
Title of host publicationProceedings of the 2nd International Conference on Data Engineering and Communication Technology - ICDECT 2017
EditorsAli Husseinzadeh Kashan, Tai Kang, Anand J. Kulkarni, Suresh Chandra Satapathy
PublisherSpringer Verlag
Pages289-302
Number of pages14
ISBN (Print)9789811316098
DOIs
Publication statusPublished - 01-01-2019
Externally publishedYes
Event2nd International Conference on Data Engineering and Communication Technology, ICDECT 2017 - Pune, India
Duration: 15-12-201716-12-2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume828
ISSN (Print)2194-5357

Conference

Conference2nd International Conference on Data Engineering and Communication Technology, ICDECT 2017
CountryIndia
CityPune
Period15-12-1716-12-17

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All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Pansari, S., Mathew, A., & Nargundkar, A. (2019). An investigation of burr formation and cutting parameter optimization in micro-drilling of brass C-360 using image processing. In A. H. Kashan, T. Kang, A. J. Kulkarni, & S. C. Satapathy (Eds.), Proceedings of the 2nd International Conference on Data Engineering and Communication Technology - ICDECT 2017 (pp. 289-302). (Advances in Intelligent Systems and Computing; Vol. 828). Springer Verlag. https://doi.org/10.1007/978-981-13-1610-4_30