STATISTICAL MODEL BASED OPTIMAL PREDICTION ON DRILLING PARAMETERS
DOI:
https://doi.org/10.24297/jac.v12i17.1073Keywords:
Drilling, cutting speed, feed rate, material removal rate, Eccentricity factor, Artificial Fish Swarm Optimization (AFSO).Abstract
The drilling is an imperative machining practice in the mechanical field for fitting or cutting the materials devoid of any disturbance. Various elements are basically employed within the automobile applications on account of the light weight, exceptional firmness and the moderate cheapness. The effectiveness of the drilled opening for the material shields is expanded by minimizing the eccentricity factor. The eccentricity is a degree of the nature of a drilled hole, and the process is based on input parameters. The significant intention of the suggested procedure is to built a mathematical modeling  with the support  of the optimization techniques. The mathematical modeling is done by minimizing the time consumed in the case of extension of the real time experiment. It is utilized to predict the diameter of the drill whole entry and exit, material removal rate and the eccentricity factor for the drilling process. Different optimization algorithms are utilized to find the optimal weights α and β of the mathematical modeling. All the optimum results demonstrate that the attained error values between the output of the experimental values and the predicted values are near equal to zero in the designed model. From the results, the minimum error 97.2% is determined by the mathematical modeling attained in the Artificial Fish Swarm Optimization (AFSO) process.
Downloads
Download data is not yet available.
References
1. Antonio Marquesa, Luis Duraob, Antonio Magalhaesb, Joao Francisco Silvab and Joao Manuel Tavaresa, 2009. Delamination Analysis of Carbon Fibre Reinforced Laminates: Evaluation of A Special Step Drill, Journal of Composites Science and Technology, Vol.69, No.14, pp. 2376–2382..
2. Jayapal,and Natarajan, 2010. Influence of Cutting parameters on thrust force and torque in drilling of E-glass / polyester composites, Journal of Engineering & Materials Science, Vol.17, pp.463-470.
3. Murugesh and Sadashivappa, “Influence of Filler Material on Glass Fiber/ Epoxy Composite Laminates during Drillingâ€, Journal of Advances in Engineering & Technology, Vol.3, No.1, pp.233-239, 2012.
4. Mahmoudi, Hossain, Truman, Smith,and Pavier,2009. A New Procedure to Measure Near Yield Residual Stresses Using the Deep Hole Drilling Techniqu, Journal of Experimental Mechanics, Vol.49, pp.595–604.
5. Klaus Weinert, Claus Weihs, Oliver Webber and Nils Raabe, 2007. Varying bending eigen frequencies in BTA deep hole drilling: mechanical modeling using statistical parameter estimation, Journal of Production Engineering,Vol.1,pp.127-134.
6. Hae-Sung Yoon, Jong-Seol Moon, Minh-Quan Pham, Gyu-Bong Lee and Sung-Hoon Ahn,2013. Control of machining parameters for energy and cost savings in micro-scale drilling of PCBs, Journal of Cleaner Production, Vol.54, pp.41-48.
7. Tsao and Hocheng,2008. Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network, Elsevier Journal of materials processing technology, Vol.203, pp.342–348.
8. Vimal Sam Singh, Latha, and Senthilkumar,2009. Modeling and Analysis of Thrust Force and Torque in Drilling GFRP Composites by Multi-Facet Drill Using Fuzzy Logic, International Journal of Recent Trends in Engineering, Vol.1, No.5, pp 66-70.
9. Andres Bustillo, and Maritza Correa, 2012. Using artificial intelligence to predict surface roughness in deep drilling of steel components, Journal of Intelligent Manufacturing, Vol.23, No.5, pp.1-10.
10. Sunday Albert Lawal, Imtiaz Ahmed Choudhury,and Yusoff Nukman, 2013. A critical assessment of lubrication techniques in machining processes: a case for minimum quantity lubrication using vegetable oil-based lubricant , Journal of Cleaner Production,Vol.41,pp. 210-221.
11. Vijayan Krishnaraj, 2008. Effects of Drill Points on Glass Fiber Reinforced Plastic Composite While Drilling at High Spindle Speed, In Proceedings of the World Congress on Engineering, Vol.2.
12. Faramarz Ashenai Ghasemi, Abbas Hyvadi, Gholamhassan Payganeh, and Nasrollah Bani Mostafa Arab, 2011. Effects of Drilling Parameters on Delamination of Glass-Epoxy Composites, Australian Journal of Basic and Applied Sciences, Vol.5, No.12, pp.1433-1440.
13. Murthy B.R.N, Lewlyn L.R. Rodrigues and Anjaiah Devineni, 2012. Process Parameters Optimization in GFRP Drilling through Integration of Taguchi and Response Surface Methodology , Journal of Recent Sciences, Vol.1, No.6, pp.7-15.
14. Jaroslaw Zubrzycki, Antoni swic and Victor Taranenko, 2013. Mathematical model of the hole drilling process and typical automated process for designing hole drilling operations, Journal of Applied Mechanics and Materials, Vol.282, pp.221-229.
15. Kishore, Tiwari and Singh, 2009. Investication of Drilling in [(0/90)/0] S Glass Fiber Reinforced Plastics using Taguchi Method, Advance in Production Engineering and Management, Vol.4, pp.37-46.
16. Kerri Hicken bottom, Nathan Hancock, Nathan Hutchings, Eric Appleton, Edward Beaudry, Pei Xu and Tzahi Cath,2013. Forward osmosis treatment of drilling mud and fracturing wastewater from oil and gas operations, Journal of Desalination, Vol.312, pp.60-66.
17. Rajesh Kumar Verma, Kumar Abhishek, Saurav Datta, and Siba Sankar Mahapatra, 2011. Fuzzy rule based optimization in machining of FRP composites, Turkish Journal of Fuzzy Systems, Vol.2, No.2, pp.99-121.
18. Saravanan, Ramalingam, Manikandan,Rinu and Kaarthikeyan, 2012. Multi objective optimization of drilling parameters using genetic algorithm, In Proceedings of the Procedia Engineering, Vol.38,pp.197-207.
19. S.Jayapal , U.Natarajan, 2010. Regression and Nero Fuzzy models for prediction of thrust force and torque in drilling of glass fiber reinforced composites, Journal of Scientific & International Research, Vol.69, pp.741-745.
20. Girolami, Marzaro, Vivan, Mazzon, Giorio, Marton and Tapparo, 2012. Aerial powdering of bees inside mobile cages and the extent of neonicotinoid cloud surrounding corn drillers, Journal of Applied Entomology, pp.1-10.
21. Amini, Paktinat, Barani and Fadaei Tehran, 2013. Vibration Drilling of Al2024-T6",Journal of Materials and Manufacturing Processes, Vol.28, pp.476-480.
22. Rajesh Kumar, Harsha Vardhan, Govindaraj and Vijay, 2013. Regression analysis and ANN models to predict rock properties from sound levels produced during drilling, Journal of Rock Mechanics & Mining Sciences, Vol.58, pp.61–72.
23. Lee, Park and Rhee, 2013. Revegetation of Decomposed Granite Road cuts in Korea: Developing Digger, Evaluating Cost Effectiveness, and Determining Dimensions Of Drilling Holes, Revegetation Species, And Mulching Treatment, Journal of land degradation and development, Vol.24, pp.591-604.
24. Navid Zarif Karimi, Hossein Heidary, Giangiacomo Minak and Mehdi Ahmadi, 2013. Effect of the drilling process on the compression behavior of glass/epoxy laminates, Journal of Composite Structures, Vol.98, pp.59-68.
25. Vaibhav Phadnis, Farrukh Makhdum, Anish Roy and Vadim Silberschmidt, 2013. Drilling in carbon / epoxy composites: Experimental investigations and finite element implementation, Journal of Composites: Part A, Vol.47, pp.41-51.
2. Jayapal,and Natarajan, 2010. Influence of Cutting parameters on thrust force and torque in drilling of E-glass / polyester composites, Journal of Engineering & Materials Science, Vol.17, pp.463-470.
3. Murugesh and Sadashivappa, “Influence of Filler Material on Glass Fiber/ Epoxy Composite Laminates during Drillingâ€, Journal of Advances in Engineering & Technology, Vol.3, No.1, pp.233-239, 2012.
4. Mahmoudi, Hossain, Truman, Smith,and Pavier,2009. A New Procedure to Measure Near Yield Residual Stresses Using the Deep Hole Drilling Techniqu, Journal of Experimental Mechanics, Vol.49, pp.595–604.
5. Klaus Weinert, Claus Weihs, Oliver Webber and Nils Raabe, 2007. Varying bending eigen frequencies in BTA deep hole drilling: mechanical modeling using statistical parameter estimation, Journal of Production Engineering,Vol.1,pp.127-134.
6. Hae-Sung Yoon, Jong-Seol Moon, Minh-Quan Pham, Gyu-Bong Lee and Sung-Hoon Ahn,2013. Control of machining parameters for energy and cost savings in micro-scale drilling of PCBs, Journal of Cleaner Production, Vol.54, pp.41-48.
7. Tsao and Hocheng,2008. Evaluation of thrust force and surface roughness in drilling composite material using Taguchi analysis and neural network, Elsevier Journal of materials processing technology, Vol.203, pp.342–348.
8. Vimal Sam Singh, Latha, and Senthilkumar,2009. Modeling and Analysis of Thrust Force and Torque in Drilling GFRP Composites by Multi-Facet Drill Using Fuzzy Logic, International Journal of Recent Trends in Engineering, Vol.1, No.5, pp 66-70.
9. Andres Bustillo, and Maritza Correa, 2012. Using artificial intelligence to predict surface roughness in deep drilling of steel components, Journal of Intelligent Manufacturing, Vol.23, No.5, pp.1-10.
10. Sunday Albert Lawal, Imtiaz Ahmed Choudhury,and Yusoff Nukman, 2013. A critical assessment of lubrication techniques in machining processes: a case for minimum quantity lubrication using vegetable oil-based lubricant , Journal of Cleaner Production,Vol.41,pp. 210-221.
11. Vijayan Krishnaraj, 2008. Effects of Drill Points on Glass Fiber Reinforced Plastic Composite While Drilling at High Spindle Speed, In Proceedings of the World Congress on Engineering, Vol.2.
12. Faramarz Ashenai Ghasemi, Abbas Hyvadi, Gholamhassan Payganeh, and Nasrollah Bani Mostafa Arab, 2011. Effects of Drilling Parameters on Delamination of Glass-Epoxy Composites, Australian Journal of Basic and Applied Sciences, Vol.5, No.12, pp.1433-1440.
13. Murthy B.R.N, Lewlyn L.R. Rodrigues and Anjaiah Devineni, 2012. Process Parameters Optimization in GFRP Drilling through Integration of Taguchi and Response Surface Methodology , Journal of Recent Sciences, Vol.1, No.6, pp.7-15.
14. Jaroslaw Zubrzycki, Antoni swic and Victor Taranenko, 2013. Mathematical model of the hole drilling process and typical automated process for designing hole drilling operations, Journal of Applied Mechanics and Materials, Vol.282, pp.221-229.
15. Kishore, Tiwari and Singh, 2009. Investication of Drilling in [(0/90)/0] S Glass Fiber Reinforced Plastics using Taguchi Method, Advance in Production Engineering and Management, Vol.4, pp.37-46.
16. Kerri Hicken bottom, Nathan Hancock, Nathan Hutchings, Eric Appleton, Edward Beaudry, Pei Xu and Tzahi Cath,2013. Forward osmosis treatment of drilling mud and fracturing wastewater from oil and gas operations, Journal of Desalination, Vol.312, pp.60-66.
17. Rajesh Kumar Verma, Kumar Abhishek, Saurav Datta, and Siba Sankar Mahapatra, 2011. Fuzzy rule based optimization in machining of FRP composites, Turkish Journal of Fuzzy Systems, Vol.2, No.2, pp.99-121.
18. Saravanan, Ramalingam, Manikandan,Rinu and Kaarthikeyan, 2012. Multi objective optimization of drilling parameters using genetic algorithm, In Proceedings of the Procedia Engineering, Vol.38,pp.197-207.
19. S.Jayapal , U.Natarajan, 2010. Regression and Nero Fuzzy models for prediction of thrust force and torque in drilling of glass fiber reinforced composites, Journal of Scientific & International Research, Vol.69, pp.741-745.
20. Girolami, Marzaro, Vivan, Mazzon, Giorio, Marton and Tapparo, 2012. Aerial powdering of bees inside mobile cages and the extent of neonicotinoid cloud surrounding corn drillers, Journal of Applied Entomology, pp.1-10.
21. Amini, Paktinat, Barani and Fadaei Tehran, 2013. Vibration Drilling of Al2024-T6",Journal of Materials and Manufacturing Processes, Vol.28, pp.476-480.
22. Rajesh Kumar, Harsha Vardhan, Govindaraj and Vijay, 2013. Regression analysis and ANN models to predict rock properties from sound levels produced during drilling, Journal of Rock Mechanics & Mining Sciences, Vol.58, pp.61–72.
23. Lee, Park and Rhee, 2013. Revegetation of Decomposed Granite Road cuts in Korea: Developing Digger, Evaluating Cost Effectiveness, and Determining Dimensions Of Drilling Holes, Revegetation Species, And Mulching Treatment, Journal of land degradation and development, Vol.24, pp.591-604.
24. Navid Zarif Karimi, Hossein Heidary, Giangiacomo Minak and Mehdi Ahmadi, 2013. Effect of the drilling process on the compression behavior of glass/epoxy laminates, Journal of Composite Structures, Vol.98, pp.59-68.
25. Vaibhav Phadnis, Farrukh Makhdum, Anish Roy and Vadim Silberschmidt, 2013. Drilling in carbon / epoxy composites: Experimental investigations and finite element implementation, Journal of Composites: Part A, Vol.47, pp.41-51.
Downloads
Published
2016-09-01
How to Cite
Saravanan, M., & Kathirvel, C. (2016). STATISTICAL MODEL BASED OPTIMAL PREDICTION ON DRILLING PARAMETERS. JOURNAL OF ADVANCES IN CHEMISTRY, 12(17), 4981–4991. https://doi.org/10.24297/jac.v12i17.1073
Issue
Section
Articles
License
All articles published in Journal of Advances in Linguistics are licensed under a Creative Commons Attribution 4.0 International License.
