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Optimization of Environmental Friendly Turning Process using Taguchi Integrated Grey Relational Analysis during Machining of 17-4 PH Stainless Steel

P. Sivaiah*, P. Mallikarjuna**, B.K.Sridhara***, K. Venkata Chalapathi****

* Senior Assistant Professor, Department of Mechanical Engineering, Madanapalle Institute of Technology & Science, Andhra Pradesh, India.

** Assistant Professor, Department of Mechanical Engineering, Annamacharya Institute of Technology and Sciences, Andhra Pradesh, India.

*** Postgraudate, Department of Mechanical Engineering, Jawaharlal Nehru Technological University Ananthapur, Andhra Pradesh, India.

**** Assistant Professor, Department of Mechanical Engineering, Chaitanya Bharathi Institute of Technology, Andhra Pradesh, India.

Periodicity:August - October'2018
DOI : https://doi.org/10.26634/jme.8.4.14190

Abstract

Chemically contaminated conventional coolants and conventional cooling techniques negatively affect the manual operator's health and environmental pollution. To overcome these problems, in the present study, biodegradable coolant and environmentally friendly cooling techniques were used for experimental investigation. Determination of optimum conditions significantly affect the productivity hence selection of optimum cutting conditions is crucial in turning process. The current work is concentrated on optimization of multiple responses using Taguchi integrated Grey Relational Analysis (TGRA) in turning of 17-4 precipitated hardenable stainless steel (PH SS) under minimum quantity lubrication (MQL) environment. The respective multiple responses considered are surface roughness (R_a), tool flank wear (V_b) and material removal rate (MRR), whereas, the respective process parameters considered are cutting velocity (v), feed rate (f) and depth of cut (d). The optimum process parameters determined from the TGRA are at v = 84.62 m/min, f = 0.048 mm/rev and d = 0.7 mm respectively. From the results, it was observed that the respective reductions in R_a and V_b are 30 % and 17.64 %, whereas, MRR increased by 24.68 % at the optimum parameter settings. Also, analysis of variance (ANOVA) was carried out to find out the influence of each input factor on turning performance characteristics. MQL cooling technique is an efficient alternative solution for metal cutting industries from the stringent environmental regulation point of view. On the other hand, TGRA helps to improve the productivity during machining of 17-4 PH SS.

Keywords

Grey Relational Analysis, Optimization, MQL, Sustainable Manufacturing, Tool Wear, Surface Roughness

How to Cite this Article?

Sivaiah, P., Mallikarjuna, P., Uma, B., and Chalapath, K. V. (2018). Optimization Of Environmental Friendly Turning Process Using Taguchi Integrated Grey Relational Analysis During Machining of 17-4 PH Stainless Steel. i-manager’s Journal on Mechanical Engineering, 8(4), 8-17. https://doi.org/10.26634/jme.8.4.14190

References

[1]. Abhang, L. B., & Hameedullah, M. (2012). Determination of optimum parameters for multi-performance characteristics in turning by using Grey Relational Analysis. The International Journal of Advanced Manufacturing Technology, 63(1-4), 13-24.

[2]. Amini, S., Khakbaz, H., & Barani, A. (2014). Improvement of Near-Dry Machining and its effect on tool wear in turning of AISI 4142. Materials and Manufacturing Processes, 30(2), 241-247. http://doi.org/10.1080/ 10426914.2014.952029

[3]. Chinchanikar, S., & Choudhury, S. K. (2014). Hard turning using HiPIMS-coated carbide tools: Wear behavior under dry and Minimum Quantity Lubrication (MQL). Measurement: Journal of the International Measurement Confederation, 55, 536-548. http://doi.org/10.1016/ j.measurement.2014.06.002

[4]. Deng, J. L. (1982). Control problems of grey systems. Sys. & Contr. Lett., 1(5), 288-294.

[5]. Feng, S., & Hattori, M. (2000). Cost and Process Information Modeling for Dry Machining. In Proc. of the International Workshop for Environment Conscious Manufacturing-ICEM-2000, (pp.1-8). Retrieved from http://www.mel.nist.gov/div826/library/doc/cost_process.p df

[6]. Gupta, M. K., Sood, P. K., & Sharma, V. S. (2016a). Machining parameters optimization of titanium alloy using Response Surface Methodology and Particle Swarm Optimization under Minimum-Quantity Lubrication environment. Materials and Manufacturing Processes, 31(13), 1671-1682.

[7]. Gupta, M. K., Sood, P. K., & Sharma, V. S. (2016b). Optimization of machining parameters and cutting fluids during nano-fluid based minimum quantity lubrication turning of titanium alloy by using evolutionary techniques. Journal of Cleaner Production, 135, 1276-1288.

[8]. Hong, S. Y., & Broomer, M. (2000). Economical and ecological cryogenic machining of AISI 304 austenitic stainless steel. Clean Products and Processes, 2(3), 0157–0166. http://doi.org/10.1007/s100980000073

[9]. Kaynak, Y., Lu, T., & Jawahir, I. S. (2014). Cryogenic Machining-Induced Surface Integrity: A review and comparison with Dry, MQL, and Flood-Cooled Machining. Machining Science and Technology, 18(2), 149-198. http://doi.org/10.1080/10910344.2014.897836

[10]. Kibria, G., Doloi, B., & Bhattacharyya, B. (2013). Optics & Laser Technology experimental investigation and multi-objective optimization of Nd: YAG laser micro-turning process of alumina ceramic using orthogonal array and Grey Relational Analysis. Optics and Laser Technology, 48, 16–27. http://doi.org/10.1016/j.optlastec.2012.09.036

[11]. Kochmaski, P., & Nowacki, J. (2006). Activated gas nitriding of 17-4 PH stainless steel. Surface and Coatings Technology, 200(22-23), 6558-6562. http://doi.org/ 10.1016/j.surfcoat.2005.11.034

[12]. Kouam, J., Songmene, V., Balazinski, M., & Hendrick, P. (2015). Effects of Minimum Quantity Lubricating (MQL) conditions on machining of 7075-T6 aluminum alloy. The International Journal of Advanced Manufacturing Technology, 79(5-8), 1325-1334.

[13]. Kumar, S, V., & Kumar, M, P., (2014). Optimization of cryogenic cooled EDM process parameters using Grey Relational Analysis. Journal of Mechanical Science and Technology, 28, 3777-3784.

[14]. Kuram, E., & Ozcelik, B. (2013). Measurement Multi-objective optimization using Taguchi based grey relational analysis for micro-milling of Al 7075 material with ball nose end mill. Measurement, 46(6), 1849-1864. http://doi.org/ 10.1016/j.measurement.2013.02.002

[15]. Kuzu, A. T., Bijanzad, A., & Bakkal, M. (2015). Experimental investigations of machinability in the turning of compacted Graphite Iron using Minimum Quantity Lubrication. Machining Science and Technology, 19(4), 559–576. http://doi.org/10.1080/10910344.2015.1085313

[16]. Lin, C. L. (2004). Use of the Taguchi method and Grey Relational Analysis to optimize turning operations with multiple performance characteristics. Materials and Manufacturing Processes, 19(2), 209-220.

[17]. Prasanna, J., Karunamoorthy, L., Raman, M. V., Prashanth, S., & Chordia, D. R. (2014). Optimization of process parameters of small hole dry drilling in Ti – 6Al – 4V using Taguchi and Grey Relational Analysis. Measurement, 48, 346-354. http://doi.org/10.1016/j.measurement. 2013.11.020

[18]. Ranganathan, S., & Senthilvelan, T. (2011). Multiresponse optimization of machining parameters in hot turning using grey analysis. The International Journal of Advanced Manufacturing Technology, 56(5-8), 455-462.

[19]. Sarıkaya, M., Yılmaz, V., & Güllü, A. (2016). Analysis of cutting parameters and cooling/lubrication methods for sustainable machining in turning of Haynes 25 superalloy. Journal of Cleaner Production, 133, 172-181. http://doi.org/10.1016/j.jclepro.2016.05.122

[20]. Shaw, M. C., Pigott, J. D., & Richardson, L. P. (1951). Effect of cutting fluid upon chip–tool interface temperature. Trans. ASME, 71(2), 45-56.

[21]. Siva, R. S., Lal, D. M., & Jaswin, M. A. (2015). Optimization of Deep Cryogenic Treatment Process for 100Cr6 bearing steel using the Grey- Taguchi Method. Tribology Transactions, 55(6), 854-862. http://doi.org/ 10.1080/10402004.2012.720002

[22]. Sohrabpoor, H., Khanghah, S. P., & Teimouri, R. (2014). Investigation of lubricant condition and machining parameters while turning of AISI 4340. The International Journal of Advanced Manufacturing Technology, 76(9-12), 2099-2116. http://doi.org/10.1007/s00170-014-6395-1

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