PERFORMANCE OPTIMIZATION OF BS970 MILD STEEL TURNING PARAMETERS UNDER SiC-MoS2 HYBRID NANOFLUID USING HYBRID DEEP BELIEF NETWORK BASED COOT OPTIMIZATION
Thangavel Palaniappan and
Prakasam Subramaniam
Additional contact information
Thangavel Palaniappan: Department of Mechanical Engineering, Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode 638455, Tamil Nadu, India
Prakasam Subramaniam: Department of Mechanical Engineering, Shree Venkateshwara Hi-Tech Engineering College, Gobichettipalayam, Erode 638455, Tamil Nadu, India
Surface Review and Letters (SRL), 2024, vol. 31, issue 12, 1-20
Abstract:
In the modern world of competitive manufacturing, turning is a basic and important process that needs to be optimized for the fast-evolving industrial nature. It has its application in various fields involving numerous materials. This research study deals with modeling with optimization on the turning process parameters of turning E2-BS970 mild steel with cryogenically treated tungsten carbide tool under NFMQL having SiC+MoS2 nanofluid. The parameters considered as the input factors are spindle speed and depth of cut along with feed rate and lubrication condition. The design of the experiment is done based on Box–Behnken design for 27 trials in the response surface method. The Deep Neural Network (DBN) and the Coot optimization algorithm are employed using MATLAB software for the prediction modeling. The prediction model developed by the DBN sigmoid function gave minimal error with prediction regression values of 0.99988 for MRR, 0.99516 for Cutting temperature, and 0.99545 for Tool life. The optimized result by CO shows a value of 188.89 rpm for spindle speed, 0.2318mm/rev for feed rate, Doc of 1.45mm, and 0.5015vol.% nanofluid MQL condition. The optimized values of MRR are 3.35mm3/min, 24.145∘C cutting temperature, and 1543.12s of tool life. The DBN model combined with the Coot algorithm shows minimal deviation compared to the experimental results validation and confirmatory analysis and is deemed suitable for efficient prediction.
Keywords: E2-BS970; turning process; cryogenically treated tungsten carbide tool; SiC+MoS2 nanofluid; nanofluid minimum quantity lubrication (search for similar items in EconPapers)
Date: 2024
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0218625X24500975
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:srlxxx:v:31:y:2024:i:12:n:s0218625x24500975
Ordering information: This journal article can be ordered from
DOI: 10.1142/S0218625X24500975
Access Statistics for this article
Surface Review and Letters (SRL) is currently edited by S Y Tong
More articles in Surface Review and Letters (SRL) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().