Aug 2026· Journal of Mechanical Science and Technology· Vol 40, pp. 6141 - 6152· 0 citations· 37 references
TL;DR
Results demonstrate that the proposed ANN–GA framework enables systematic adjustment of cutting parameters according to operational priorities, supporting both finishing and roughing applications, and provides a practical and scalable decision-support tool for intelligent manufacturing environments.
Dry turning has emerged as a sustainable and environmentally conscious machining strategy due to the complete elimination of cutting fluids from the manufacturing process. However, the simultaneous optimization of machining responses such as crater wear, face wear, and surface roughness remains challenging because of t...
Tejinder Kaur, Caston Fernandes, Anitha Rani Palakayala et al.· 2026 International Conferenc...· 0 citations
A primary machining operation in today's manufacturing is CNC turning; the optimization of process parameters affects the quality of products manufactured, productivity, and ultimately the cost of manufacturing for all manufactured parts. A systematic review that examines the development and effectiveness of various pa...
Mangesh Patil, Munna Verma, Pundalik Patil et al.· international journal of eng...· 0 citations
Background: When a small design-of-experiments dataset is used to optimize a machining process with particle swarm optimization (PSO), the regression model chosen as the fitness function is rarely validated against more than one candidate response, checked against alternative model families, or checked for the optimiza...
P. Marimuthu, J. Petrů, Thenarasu Mohanavelu· Journal of Manufacturing and...· 0 citations
This study presents a data-driven, real-time drilling optimization framework and a direct comparison between single-objective PSO and multi-objective PSO (MOPSO) for optimizing WOB, RPM, and flow rate (Q). A stacked ensemble surrogate model was trained to predict ROP and HMSE, achieving high generalization accuracy (RO...
Tool wear significantly affects cutting performance and workpiece quality, while also leading to increased machining process complexity and diminishing tool longevity. Consequently, identifying the appropriate process parameters to guarantee high efficiency and quality in material processing has emerged as a signific...
Dong-Wei Li, Jia-Hao Huang, Lin Huang et al.· Proceedings of the Instituti...· 0 citations
Sheet metal blanking optimization is traditionally performed using design-of-experiments (DOE) techniques that evaluate only discrete parameter combinations, limiting the identification of optimal operating conditions within the continuous design space. This study proposes a surrogate-assisted Artificial Neural Network...
S. Bhoir, Munna Verma· Discover Mechanical Engineer...· 0 citations
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