A combined approach of artificial neural network, multi-objective genetic algorithm, and response surface methodology for enhanced PMMA micro-channeling in low power fiber laser beam machining

Sen, A.; Pramanik, D.; Roy, N.

doi:10.1016/j.ijleo.2024.171624

Cited by 1 publication

(1 citation statement)

References 22 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The results demonstrated that the ANN method has superior prediction accuracy, which is consistent with empirical findings in forecasting micro-channel dimensions. The proposed strategy minimised the amount of material that was wasted, decreased expenses, and enhanced productivity within the biomedical industry [75]. Further, in another study, researchers introduced a streamlined process utilising a simplified model to forecast distortion in laser peen production.…”

Section: Gamentioning

confidence: 99%

Systematic review of optimization techniques for laser beam machining

Kharche,

Patil

2024

Eng. Res. Express

View full text Add to dashboard Cite

Laser Beam Machining (LBM) has several applications in the aerospace, medical, and automobile domains. Optimization techniques are essential for LBM to increase resource-efficiency and sustainability of the system. The present paper aims to provide a systematic review of the research in the domain of optimization techniques for LBM. A total of 228 research papers published during the last 20 years, from 2003 to 2023, are reviewed. The literature review is classified into three major sections- (i) optimization techniques, (ii) applications of optimization techniques, and (iii) challenges and future directions. The novelty of the present systematic review paper is to provide a direction for future research in the domain of optimization techniques of LBM. As a result of the suggested research, an efficient and sustainable LBM with the required performance will be developed in the shortest possible time.

show abstract

Section: Gamentioning

confidence: 99%