Refine your search
Collections
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Naresh, N.
- Optimisation of Machining Parameters for Turning En16 Steel:Desirability Function Analysis and Anova
Abstract Views :146 |
PDF Views:0
Authors
Affiliations
1 Dept. of Mechanical Engineering, N.B.K.R. Institute of Science and Technology, Vidyanagar - 524413, Nellore, A.P., IN
1 Dept. of Mechanical Engineering, N.B.K.R. Institute of Science and Technology, Vidyanagar - 524413, Nellore, A.P., IN
Source
Research Journal of Engineering and Technology, Vol 5, No 1 (2014), Pagination: 25-32Abstract
This paper presents optimisation of machining parameters for turning EN16 steel using desirability function analysis (DFA). The experiments were conducted using Taguchi's L27 orthogonal array on CNC turning with tungsten carbide tool. The machining parameters such as, cutting speed, feed rate and depth of cut are optimised by multi-response considerations namely surface roughness and material removal rate. The optimal machining parameters have been determined by the composite desirability value obtained from the desirability function analysis, and significant contribution of parameters can then be determined by analysis of variance (ANOVA). The analysis of the result shows that the optimal combination for good surface roughness and high material removal rate are medium cutting speed, medium feed rate and high depth of cut. Confirmation test is also conducted to validate the test result. Experimental results have shown that machining performance can be improved effectively through this approach.Keywords
ANOVA, CNC Turning, Desirability Function Analysis, EN16 Steel, MRR, Surface Roughness.
- Application of Desirability Based Hybrid Anfis Model for Optimization of Electro Discharge Machining of Hastealloy C-276
Abstract Views :190 |
PDF Views:0
Authors
Affiliations
1 Department of Mechanical Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, IN
1 Department of Mechanical Engineering, Sree Vidyanikethan Engineering College, Tirupati, Andhra Pradesh, IN
Source
Manufacturing Technology Today, Vol 17, No 7 (2018), Pagination: 32-43Abstract
Hastealloy C-276 is a difficult to machine superalloy and comprehensively employed in various engineering fields such as nuclear applications, aerospace and gas turbines. Hastealloy C-276 having better strength and poor thermal conductivity makes them difficult to machine materials which results in reduced life of the cutting tool and poor machinability by conventional methods of material removal. Advanced metal removal methods have evolved to accomplish those kind of needs and appealed to be an opposite alternative approach to traditional machining. Electro Discharge Machining (EDM) is considered as one of the nontraditional metal removal process which is especially adopted for machining of hard to machine materials. In this present investigation Spark Erosion Machining has been employed for machining of Haste Alloy C-276 with copper electrode by using Taguchi’s experimental design approach. Applied current (A), pulse on time (TON) and pulse off time (TOFF) were considered as the input process variables and the performance of spark erosion machining has been assessed by considering the performance measures such as material removal rate, surface roughness, overcut, form and orientation tolerance errors. The significance of process variables were analyzed by Analysis of Variance (ANOVA). Multi objective optimization has been performed by desirability function analysis to obtain better machining performance. In addition DFA based Adaptive Neuro Fuzzy Inference System (ANFIS) have been evolved to optimize the desired performance characteristics.Keywords
EDM, Haste Alloy, Taguchi’s Design, Desirability Function Analysis, ANFIS.References
- Ahilan, C; Kumanan, S; Sivakumaran, N: Multi-objective optimisation of CNC turning process using grey based fuzzy logic. 'Int. J. Mach. Mach. Mater.', vol.5, 2009, 434–451.
- Baraskar SS; Banwait, SS and Laroiya, SC: Multi-objective optimisation of electrical discharge machining process using Derringer’s desirability function approach, 'Int. J. Mater. Eng. Innova'., vol. 2, no. 3/4, 2011, 203-221.
- Bharti, PS; Maheshwari, S; Sharma, C: Experimental investigation of Inconel 718 during die- sinking electric discharge machining, 'Int. J. Eng. Sci. Technol'., vol. 2, 2010, 6464–6473.
- Derringer, G; Suich, R: Simultaneous Optimization of Several Response Variables, 'J. Quality Technol'., vol. 12, no. 4, 1980, 214-219.
- Dhanabalan, C; Sivakumar, K; Sathiya Narayanan, C: Optimization of machining parameters of EDM while machining Inconel 718 for form tolerance and orientation Tolerance, 'Indian J. Eng. Mater. Sci'., vol. 20, 2013, 391–397.
- Ho, KH; Newman, ST: State of the art electrical discharge machining (EDM), 'Int. J. Mach. tools and manuf'., vol. 43, 2003, 1287 – 1300.
- Jang, JSR; Sun, CT; Mizutani, E: Neuro-fuzzy and Soft Computing: A Comput. App. Learn. Mach. Intelligence, Prentice Hall, Upper Saddle River, NJ, 1997.
- Kuppan, P; Narayanan, S; Rajadurai, A; Adithan, M: Effect of EDM parameters on hole quality characteristics in deep hole drilling of Inconel 718 superalloy, 'Int. J. Manuf. Res'., vol. 10, no. 1, 2015, 45-63.
- Kuppan, P; Rajadurai, A; Narayanan, S: Influence of EDM process parameters in deep hole drilling of Inconel 718, 'Int. J. Adv. Manuf. Technol'., 38, 2008, 74–84.
- Lin, JL; Wang, KS; Yan, BH; Tarng, YS: Optimization of the electrical discharge machining process based on the Taguchi method with fuzzy logics, 'J. Mater. Process. Technol'., vol. 102, 2000, 48-55.
- Luis, CJ; Puertas, I; Villa, G: Material removal rate and electrode wear study on the EDM of silicon carbide, 'J. Mater. Process. Technol'., 165, 2005, 889–896.
- Pradhan, MK & Biswas, CK: Neuro-fuzzy and neural network-based prediction of various responses in electrical discharge machining of AISID2 steel “NF and NN based prediction of responses in EDM of D2 steel, 'Int. J. Adv. Manuf. Technol'., vol. 50(5-8), 2010, 591–610.
- Qu, NS; Hu, Y; Zhu, D; Xu, ZY: Electrochemical machining of blisk channels with progressive pressure electrolyte flow. Mater. Manuf. Process'. vol. 29, 2014, 572-578.
- Rupesh Kumar Pandey, SS Panda: Optimization of bone drilling parameters using grey-based fuzzy algorithm, Meas., vol. 47, 2014, 386–392.
- Pervaiz, Salman; Rashid, Amir; Deiab, Ibrahim; Nicolescu, Mihai: Influence of tool materials on machinability of titanium- and nickel-based alloys: A Review, 'Mater. Manuf. Process'., vol. 29, 2014, 219-252.
- Sengottuvel, P; Satishkumar, S; Dinakaran, D: Optimization of multiple characteristics of EDM parameters based on desirability approach and fuzzy modeling., 'Procedia Eng'., 64, 2013, 1069-1078.
- Suresh, P; Marimuthu, K; Ranganathan, S; Rajmohan, T: Optimization of machining parameters in turning of Al−SiC−Gr hybrid metal matrix composites using grey-fuzzy algorithm, 'Trans. Nonferrous Met. Soc. China', vol. 24, 2014, 2805−2814.
- Teimouri, R; Baseri, H; Moharami, R: Multiresponses optimization of ultrasonic machining process, 'J. Intel. Manuf'., vol. 26, 2015, 745-753.
- Caydas, Ulas; Hascalık, Ahmet; Ekici, Sami: An adaptive neuro-fuzzy inference system (ANFIS) model for wire-EDM, 'Expert Syst. Appl'., vol. 36, 2009, 6135–6139.
- Wu, Q: Serrated chip formation and tool-edge wear in high-speed machining of advanced aerospace materials, Utah State University, Logan, Utah, 2007.
- Xiaojiang Cai; Sheng Qin; Junli Li; Qinglong An; Ming Chen: Experimental investigation on surface integrity of end milling nickel based alloy - Inconel 718, 'Mach. Sci. Technol. Int. J'., vol. 18, 31-46