TY - GEN
T1 - An investigation of burr formation and cutting parameter optimization in micro-drilling of brass C-360 using image processing
AU - Pansari, Shashank
AU - Mathew, Ansu
AU - Nargundkar, Aniket
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
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U2 - 10.1007/978-981-13-1610-4_30
DO - 10.1007/978-981-13-1610-4_30
M3 - Conference contribution
AN - SCOPUS:85054819379
SN - 9789811316098
T3 - Advances in Intelligent Systems and Computing
SP - 289
EP - 302
BT - Proceedings of the 2nd International Conference on Data Engineering and Communication Technology - ICDECT 2017
A2 - Kashan, Ali Husseinzadeh
A2 - Kang, Tai
A2 - Kulkarni, Anand J.
A2 - Satapathy, Suresh Chandra
PB - Springer Verlag
T2 - 2nd International Conference on Data Engineering and Communication Technology, ICDECT 2017
Y2 - 15 December 2017 through 16 December 2017
ER -