Optimization of Process Parameters Using Response Surface Methodology for SAE8620

Chinmay Anil Tornekar; Mayur Laxmanrao Jadhav; Sachin Chandrakant Borse

doi:doi:10.11648/j.ajmie.20220704.11

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Optimization of Process Parameters Using Response Surface Methodology for SAE8620

Chinmay Anil Tornekar, Mayur Laxmanrao Jadhav, Sachin Chandrakant Borse

Published in American Journal of Mechanical and Industrial Engineering (Volume 7, Issue 4)

Received: 3 August 2022 Accepted: 23 August 2022 Published: 17 October 2022

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Abstract

The present study is carried for the optimization of the process parameters in order to reduce the monthly In-House Rejection Rate, improving quality and enhancement of production thereby minimizing the consumer complaints. The component selected for study is Shift fork. A pareto Analysis Study clearly explains that I.D not ok contributes around 30% defects. This I.D Not OK included I.D Oversize, I.D Shift, I.D patch Mark & I.D Burn. Design of Experiments has been used to study the effect of Process parameters like speed, feed and no of passes on VMC and Honing Machine to determine the Surface Roughness, I. D oversize and I. D shift of SAE 8620 Fork. A mathematical Model has been generated in terms of the above process parameters the effect of these parameters on Surface roughness, I. D oversize and I. D shift has been Investigated using Response Surface Methodology (RSM). Surface Plot and Contour plots were constructed to determine the optimum conditions for the desired Output. The Developed Prediction shows that Cutting speed is the influential factor for all three Output Results, and No. of Pass is main factor is important for I. D shift. These results thus provided the optimal solution, thereby reducing the Customer Complaint and minimizing the Rejection Rate in the Company.

Published in	American Journal of Mechanical and Industrial Engineering (Volume 7, Issue 4)
DOI	10.11648/j.ajmie.20220704.11
Page(s)	53-62
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2022. Published by Science Publishing Group

Keywords

SAE8620, DOE, RSM, Optimization, In-House Rejection, VMC, Honing

References

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[2]	M. Pradeep Kumar, K. Vikram Kumar, V. Kumar, “Response Surface Methodology- A Review”, IJSRD - International Journal for Scientific Research & Development\| Vol. 8, Issue 7, 2020 \| ISSN (online): 2321-0613.
[3]	K. Devaki Devi, K. Satish Babu, K. Hemachandra Reddy, “Mathematical Modelling and Optimization of Turning Process Parameters Using Response Surface Methodology”, International Journal of Applied Science and Engineering 2015.13, 1: 55-68.
[4]	Ranganath M S, Vipin, Harshith, “Optimization of Process Parameters in Turning Operation Using Response Surface Methodology: A Review”, International Journal of Emerging Technology and Advanced Engineering, Volume 4 Issue 10, October 2014.
[5]	Chelladurai, Samson Jerold Samuel, Ramesh Arthanari, Arunprasad Narippalayam Thangaraj, and Harishankar Sekar, Dry sliding wear characterization of squeeze cast LM13/FeCu composite using response surface methodology, China Foundry 14, no. 6 (2017): 525-533.
[6]	Srinivasan, A., R. M. Arunachalam, S. Ramesh and J. S. Senthilkumaar, Machining Performance Study on Metal Matrix Composites-A Response Surface Methodology Approach, American Journal of Applied Sciences vol. 9 issue 4, 2012, pp. 478-483.
[7]	Subramanian M. et ell Using RSM and GA to Predict Surface Roughness Based on Process Parameters in CNC Turning of AL7075-T6. International Journal of Innovative Research in Science, Engineering and Technology Volume 3, Special Issue 3, 2014.
[8]	Wasif M. G., Safiulla. M, Evaluation Of Optimal Machining Parameters Of Nicrofer C263 Alloy Using Response Surface Methodology While Turning On Cnc Lathe Machine, International Journal of Mechanical and Industrial Engineering (IJMIE), Vol 2, Iss-4, 2012.
[9]	Ghazi Abu Taher α & Md. Jahangir Alam σ, “Improving Quality and Productivity in Manufacturing Process by using Quality Control Chart and Statistical Process Control Including Sampling and Six Sigma”, Global Journal of Researches in Engineering: G Industrial Engineering Volume 14 Issue 3 Version 1.0 Year 2014.
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[12]	S. Karthikheyen et al. (2014) “Optimization of Machining Parameters for Face Milling Operation in a vertical CNC Milling Machine” International Journal of Advance Research in Education, Technology & Management, Vol. 3, No. 3, ISSN: 2349-0012.
[13]	Bharat chandra routara, Saumya darsan mohanty, saurav datta, Asish bandyopadhyay and siba sankar mahapatra, Sadhana, (2010) “Optimization in CNC end milling of UNS C34000 medium leaded brass with multiple surface roughness characteristics”, Indian Academy of Sciences, vol. 35, Part 5, pp. 619–629.
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APA Style

Chinmay Anil Tornekar, Mayur Laxmanrao Jadhav, Sachin Chandrakant Borse. (2022). Optimization of Process Parameters Using Response Surface Methodology for SAE8620. American Journal of Mechanical and Industrial Engineering, 7(4), 53-62. https://doi.org/10.11648/j.ajmie.20220704.11

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ACS Style

Chinmay Anil Tornekar; Mayur Laxmanrao Jadhav; Sachin Chandrakant Borse. Optimization of Process Parameters Using Response Surface Methodology for SAE8620. Am. J. Mech. Ind. Eng. 2022, 7(4), 53-62. doi: 10.11648/j.ajmie.20220704.11

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AMA Style

Chinmay Anil Tornekar, Mayur Laxmanrao Jadhav, Sachin Chandrakant Borse. Optimization of Process Parameters Using Response Surface Methodology for SAE8620. Am J Mech Ind Eng. 2022;7(4):53-62. doi: 10.11648/j.ajmie.20220704.11

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@article{10.11648/j.ajmie.20220704.11,
  author = {Chinmay Anil Tornekar and Mayur Laxmanrao Jadhav and Sachin Chandrakant Borse},
  title = {Optimization of Process Parameters Using Response Surface Methodology for SAE8620},
  journal = {American Journal of Mechanical and Industrial Engineering},
  volume = {7},
  number = {4},
  pages = {53-62},
  doi = {10.11648/j.ajmie.20220704.11},
  url = {https://doi.org/10.11648/j.ajmie.20220704.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmie.20220704.11},
  abstract = {The present study is carried for the optimization of the process parameters in order to reduce the monthly In-House Rejection Rate, improving quality and enhancement of production thereby minimizing the consumer complaints. The component selected for study is Shift fork. A pareto Analysis Study clearly explains that I.D not ok contributes around 30% defects. This I.D Not OK included I.D Oversize, I.D Shift, I.D patch Mark & I.D Burn. Design of Experiments has been used to study the effect of Process parameters like speed, feed and no of passes on VMC and Honing Machine to determine the Surface Roughness, I. D oversize and I. D shift of SAE 8620 Fork. A mathematical Model has been generated in terms of the above process parameters the effect of these parameters on Surface roughness, I. D oversize and I. D shift has been Investigated using Response Surface Methodology (RSM). Surface Plot and Contour plots were constructed to determine the optimum conditions for the desired Output. The Developed Prediction shows that Cutting speed is the influential factor for all three Output Results, and No. of Pass is main factor is important for I. D shift. These results thus provided the optimal solution, thereby reducing the Customer Complaint and minimizing the Rejection Rate in the Company.},
 year = {2022}
}

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TY - JOUR
T1 - Optimization of Process Parameters Using Response Surface Methodology for SAE8620
AU - Chinmay Anil Tornekar
AU - Mayur Laxmanrao Jadhav
AU - Sachin Chandrakant Borse
Y1 - 2022/10/17
PY - 2022
N1 - https://doi.org/10.11648/j.ajmie.20220704.11
DO - 10.11648/j.ajmie.20220704.11
T2 - American Journal of Mechanical and Industrial Engineering
JF - American Journal of Mechanical and Industrial Engineering
JO - American Journal of Mechanical and Industrial Engineering
SP - 53
EP - 62
PB - Science Publishing Group
SN - 2575-6060
UR - https://doi.org/10.11648/j.ajmie.20220704.11
AB - The present study is carried for the optimization of the process parameters in order to reduce the monthly In-House Rejection Rate, improving quality and enhancement of production thereby minimizing the consumer complaints. The component selected for study is Shift fork. A pareto Analysis Study clearly explains that I.D not ok contributes around 30% defects. This I.D Not OK included I.D Oversize, I.D Shift, I.D patch Mark & I.D Burn. Design of Experiments has been used to study the effect of Process parameters like speed, feed and no of passes on VMC and Honing Machine to determine the Surface Roughness, I. D oversize and I. D shift of SAE 8620 Fork. A mathematical Model has been generated in terms of the above process parameters the effect of these parameters on Surface roughness, I. D oversize and I. D shift has been Investigated using Response Surface Methodology (RSM). Surface Plot and Contour plots were constructed to determine the optimum conditions for the desired Output. The Developed Prediction shows that Cutting speed is the influential factor for all three Output Results, and No. of Pass is main factor is important for I. D shift. These results thus provided the optimal solution, thereby reducing the Customer Complaint and minimizing the Rejection Rate in the Company.
VL - 7
IS - 4
ER -

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Author Information

Chinmay Anil Tornekar

Department of Mechanical Engineering, Deogiri College of Engineering and Management Studies, Aurangabad, India
Mayur Laxmanrao Jadhav

Department of Mechanical Engineering, Deogiri College of Engineering and Management Studies, Aurangabad, India
Sachin Chandrakant Borse

Department of Mechanical Engineering, Deogiri College of Engineering and Management Studies, Aurangabad, India

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Plain Text BibTeX RIS

APA Style

Chinmay Anil Tornekar, Mayur Laxmanrao Jadhav, Sachin Chandrakant Borse. (2022). Optimization of Process Parameters Using Response Surface Methodology for SAE8620. American Journal of Mechanical and Industrial Engineering, 7(4), 53-62. https://doi.org/10.11648/j.ajmie.20220704.11

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ACS Style

Chinmay Anil Tornekar; Mayur Laxmanrao Jadhav; Sachin Chandrakant Borse. Optimization of Process Parameters Using Response Surface Methodology for SAE8620. Am. J. Mech. Ind. Eng. 2022, 7(4), 53-62. doi: 10.11648/j.ajmie.20220704.11

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AMA Style

Chinmay Anil Tornekar, Mayur Laxmanrao Jadhav, Sachin Chandrakant Borse. Optimization of Process Parameters Using Response Surface Methodology for SAE8620. Am J Mech Ind Eng. 2022;7(4):53-62. doi: 10.11648/j.ajmie.20220704.11

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@article{10.11648/j.ajmie.20220704.11,
  author = {Chinmay Anil Tornekar and Mayur Laxmanrao Jadhav and Sachin Chandrakant Borse},
  title = {Optimization of Process Parameters Using Response Surface Methodology for SAE8620},
  journal = {American Journal of Mechanical and Industrial Engineering},
  volume = {7},
  number = {4},
  pages = {53-62},
  doi = {10.11648/j.ajmie.20220704.11},
  url = {https://doi.org/10.11648/j.ajmie.20220704.11},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.ajmie.20220704.11},
  abstract = {The present study is carried for the optimization of the process parameters in order to reduce the monthly In-House Rejection Rate, improving quality and enhancement of production thereby minimizing the consumer complaints. The component selected for study is Shift fork. A pareto Analysis Study clearly explains that I.D not ok contributes around 30% defects. This I.D Not OK included I.D Oversize, I.D Shift, I.D patch Mark & I.D Burn. Design of Experiments has been used to study the effect of Process parameters like speed, feed and no of passes on VMC and Honing Machine to determine the Surface Roughness, I. D oversize and I. D shift of SAE 8620 Fork. A mathematical Model has been generated in terms of the above process parameters the effect of these parameters on Surface roughness, I. D oversize and I. D shift has been Investigated using Response Surface Methodology (RSM). Surface Plot and Contour plots were constructed to determine the optimum conditions for the desired Output. The Developed Prediction shows that Cutting speed is the influential factor for all three Output Results, and No. of Pass is main factor is important for I. D shift. These results thus provided the optimal solution, thereby reducing the Customer Complaint and minimizing the Rejection Rate in the Company.},
 year = {2022}
}

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