Online Dimensional Controlling System for Drilling

Subject Areas : journal of Artificial Intelligence in Electrical Engineering

Reza Farshbaf Zinati ¹ , Ahmad Habibi Zad navin ² , Mohammad Reza Razfar ³

1 - Department of Mechanical Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
2 - Department of Computer Engineering, Tabriz Branch, Islamic Azad University, Tabriz, Iran
3 - Department of Mechanical Engineering, AmirKabir University of Technology, Tehran, Iran.

Received: 2016-11-03 Accepted : 2016-11-03 Published : 2016-06-01

Keywords:

References:

[1] Ahn, D.K.; Choi, J.H.; Kweon, J.H. (2014).
Relationship between the drilling condition and
the damage (delamination) zone of glass-fiberreinforced
plastic composites. Advanced
Composite Materials, DOI:
10.1080/09243046.2014.926655.
[2] Aramesh, M.; Shaban, Y.; Balazinski, M.; Attia,
H.; Kishawy, H.; Yacout, S. (2014). Survival Life
Analysis of the Cutting Tools During Turning
Titanium Metal Matrix Composites (Ti-MMCs).
Procedia CIRP, 14, 605-609.
[3] Aziz, M.H.; Ayub, M.A.; Jaafar R. (2012). Realtime
Algorithm for Detection of Breakthrough
Bone Drilling. Procedia Engineering, 41, 352-359.
[4] Debnath, K.; Singh, I.; Dvivedi, A. (2014).
Drilling Characteristics of Sisal Fiber-Reinforced
Epoxy and Polypropylene Composites. Materials
and Manufacturing Processes, 29(11-12), 1401-
1409.
[5] Farshbaf Zinati, R.; Razfar M.R. (2012).
Constrained optimum surface roughness
prediction in turning of X20Cr13 by coupling
novel modified harmony search-based neural
network and modified harmony search algorithm.
International Journal of Advanced Manufacturing
Technology, 58, 93–107.
[6] Farshbaf Zinati, R.; Razfar, M.R.; Nazockdast, H.
(2015). Surface Integrity Investigation for Milling
PA6-MWCNT. Materials and Manufacturing
Processes, DOI: 10.1080/10426914.2014.961473.
[7] Farshbaf Zinati, R.; Razfar, M.R. (2013). An
investigation of the machinability of PA 6/nano-
CaCO3 composite. International journal of
advanced manufacturing technology, 68, 2489–
2497.
[8] Figueroa, M.; García, E.; Muhl, S.; Rodil, S.
(2014). Preliminary Tribological Study and Tool
Life of Four Commercial Drills. Tribology
Transactions, 57(4), 581-588.
[9] Gokulachandran, J.; Mohandas, K. (2012).
Predicting remaining useful life of cutting tools
with regression and ANN analysis. International
Journal of Productivity and Quality Management,
9, 502-518.
[10] Guhring Inc. (2014). Full-line drill catalogue,
press: Guhring, USA.
[11] MacAvelia, T.; Ghasempoora, A.; Janabi-
Sharifia, F. (2014). Force and torque modelling of
drilling simulation for orthopaedic surgery.
Computer Methods in Biomechanics and
Biomedical Engineering, 17(12), 1285-1294.
[12] Palanikumar, K.; Srinivasan, T.; Rajagopal, K.;
Latha, B. (2014). Thrust Force Analysis in
Drilling Glass Fiber Reinforced/Polypropylene
(GFR/PP) Composites. Materials and
Manufacturing Processes ,DOI:
10.1080/10426914.2014.961478.
[13] Samuel Raj, D.; Karunamoorthy, L. (2015).
Study of the Effect of Tool Wear on Hole Quality
in Drilling Cfrp to Select a Suitable Drill for
Multi-Criteria Hole Quality. Materials and
Manufacturing Processes, DOI:
10.1080/10426914.2015.1004713.
[14] Si, X.S.; Wang, W.; Hu, C.H.; Zhou, D.H.
(2011). Remaining useful life estimation–A
review on the statistical data driven approaches.
European journal of operational research, 213, 1-
14.
[15] Steinzig, M.; Upshaw, D.; Rasty, J. (2014).
Influence of Drilling Parameters on the Accuracy
of Hole-drilling Residual Stress Measurements.
Experimental Mechanics, 54 (9), 1537-1543.
[16] Wang, M.; Wang, J. (2012). CHMM for tool
condition monitoring and remaining useful life
prediction. The International Journal of Advanced
Manufacturing Technology, 59, 463-471.
[17] Wang, Y.; Bao, Y.; Zhang, H.; Qiu, Q.; Yan, Z.;
Guo, C. (2014). Evaluating equipment reliability
function and mean residual life based on
proportional hazard model and semi-Markov
process. Power System Technology
(POWERCON), 2014 International Conference
on, 1293-1299.