Optimization of Process Parameters Using Taguchi andSimulated Annealing Methods for Surface Roughnessin Turning of TI-6AL-4V Alloy

M. Venkata Ramana*, G. Krishna Mohan Rao**, D. Hanumantha Rao***
* Department of Automobile Engineering, VNR Vignana Jyothi Institute of Engineering & Technology, Hyderabad, India.
** Department of Mechanical Engineering, JNTUH College of Engineering, Hyderabad, India.
*** Principal, Mathrusri Engineering College, Hyderabad, India.
Periodicity:August - October'2014
DOI : https://doi.org/10.26634/jme.4.4.2843

Abstract

Titanium and its alloys are classified into difficult to cut materials. To machine such materials economically, the optimized process parameters plays significant role. Therefore the experiments have been planned and conducted using Design of Experiments. The experiments are conducted under different machining environments such as dry, flooded and Minimum Quantity Lubrication (MQL) machining with different tool materials such as uncoated, Chemical Vapour Deposition (CVD) and Physical Vapour Deposition (PVD) coated tools. In this study, Taguchi's L orthogonal array is 27 used to perform the experiments. The results obtained from these experiments are used to develop second order multiple regression model in terms of input process parameter. The same model is used as a fitness function for Simulated Annealing (SA) to optimize the process parameters for minimum surface roughness. The optimum results from SA is compared with Taguchi methodology and validated with Regression Analysis. The optimum parameters obtained both in Taguchi's methodology and Simulated Annealing are flooded machining, high cutting speed, low feed rate, low depth of cut and CVD coated tool.

Keywords

Taguchi Technique, Regression Analysis, Simulated Annealing (SA), Optimization, Titanium Alloy, Cutting Fluids.

How to Cite this Article?

Ramana, V., Rao, G. K. M., & Rao, D. H. (2014). Optimization of Process Parameters Using Taguchi and Simulated Annealing Methods for Surface Roughness in Turning of Ti-6Al-4V Alloy. i-manager's Journal on Mechanical Engineering, 4(4), 29-37. https://doi.org/10.26634/jme.4.4.2843

References

[1]. Ezugwu E.O., Wang Z.M., (1997), “Titanium alloys and their machinability- a review”, Journal of Materials Processing Technology, Vol.68, pp. 262-274.
[2]. Azlan Mohd Zain, Habibollah Haron, Safian Sharif, (2010), “Application of GA to optimize cutting conditions for minimizing surface roughness in end milling machining process”, Expert Systems with Applications, Vol. 37, pp. 4650–4659.
[3]. Hari Singh, Pradeep Kumar, (2004), “Tool wear optimization in turning operation by Taguchi method”, International Journal of Engineering & Material Sciences, Vol. 11, pp. 19-24.
[4]. Venkata Ramana M, Srinivasulu K., Krishna Mohan Rao G., Hanumantha Rao D., (2011), “Performance Evaluation and Selection of Optimal Cutting Conditions in Turning of Ti-6Al-4V Alloy under Different Cooling Conditions”, International Journal of Innovative Technology & Creative Engineering, Vol.1(5), pp. 10-21.
[5]. Shiba Narayan Sahu, Debasis Nayak, Hemanta Kumar Rana, (2013). “Optimization of ECM Process Parameter by Using Simulated Annealing Approach”, International Journal of Advanced Trends in Computer Science and Engineering, Vol.2(6), pp.18-21.
[6]. Farhad Kolahan, Reza Golmezerji, Masoud Azadi Moghaddam, (2012). “Multi Objective Optimization of Turning Process using Grey Relational Analysis and Simulated Annealing Algorithm”, Applied Mechanics and Materials, Vol. 110-116, pp. 2926-2932.
[7]. Azlan Mohd Zaina, Habibollah Haron, Safian Sharif, (2011). “Optimization of process parameters in the abrasive waterjet machining using integrated SA–GA”, Applied Soft Computing, Vol.11, pp. 5350–5359.
[8]. Hsien-Ching Chen, Jen-Chang Lin, Yung-Kuang Yang, Chih-Hung Tsai, (2010). “Optimization of wire electrical discharge machining for pure tungsten using a neural network integrated simulated annealing approach” Expert Systems with Applications, Vol. 37, pp.7147–7153.
[9]. Seung-Han Yang, J. Srinivas, Sekar Mohan, Dong-Mok Lee, Sree Balaji, (2009). “Optimization of electric discharge machining using simulated annealing”, Journal of Materials Processing Technology, Vol. 209, pp. 4471–4475.
[10]. Phillip J. Ross, (2005). “Taguchi Techniques for Quality Engineering”, Tata McGraw Hill, Second Edition.
[11]. Douglas C. Montgomery, (2008). “Design and Analysis of Experiments”, John Wiley & Sons.
[12]. Kirkpatrick S., Gelatt Jr. C. D., Vecchi, M. P., (1983). "Optimization by Simulated Annealing", Science 220 (4598)pp. 671–680,
[13]. Minitab Statistical Software Features – Minitab, (2011). "Software for Statistics, Process Improvement, Six Sigma, Quality – Minitab”. retrieved from http://en.wikipedia.org /wiki /Simulated_annealing.
[14]. Vydehi Arun Joshi, (2006). “Titanium Alloys: An Atlas of Structures and Fracture Features”, CRC Press. Retrieved from http://en.wikipedia.org/wiki/Titanium_alloy.
If you have access to this article please login to view the article or kindly login to purchase the article

Purchase Instant Access

Single Article

North Americas,UK,
Middle East,Europe
India Rest of world
USD EUR INR USD-ROW
Online 15 15

Options for accessing this content:
  • If you would like institutional access to this content, please recommend the title to your librarian.
    Library Recommendation Form
  • If you already have i-manager's user account: Login above and proceed to purchase the article.
  • New Users: Please register, then proceed to purchase the article.