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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

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

Abstract

Keywords

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References

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