Deep learning-driven optimization and predictive modeling of LASER beam machining for XG3 steel
Adithya Hegde, Raviraj Shetty, Gururaj Bolar, V Balaji
TL;DR
This paper uses deep learning and optimization techniques to improve laser beam machining of XG3 steel, focusing on parameters that affect surface quality and machining efficiency.
Contribution
The novel use of BPANN for predictive modeling and MOGA for multi-objective optimization in laser machining of XG3 steel.
Findings
Cutting speed was the most dominant factor affecting surface roughness, machining time, surface hardness, and burr thickness.
BPANN outperformed RSM with high accuracy (R > 0.999) and low MAPE for predicting surface roughness and hardness.
Multi-objective optimization using MOGA provided balanced trade-off solutions for circular hole profiles.
Abstract
LASER Beam Machining (LBM) has emerged as a highly precise and non-contact thermal machining process, widely adopted for cutting complex geometries in advanced engineering materials. Its ability to machine difficult-to-cut alloys with minimal mechanical stress makes it particularly suitable for aerospace and defense components. This paper presents an experimental investigation and multi-objective optimization of LASER Beam Machining (LBM) for XG3 steel, a high-performance alloy used in aerospace and defense applications. The study evaluates the impact of four process parameters i.e. cutting speed (8, 10, 12 m/min), gas pressure (0.5, 0.7, 0.9 Bar), focus point (2, 4, 6 mm), and depth of cut (3, 6, 9 mm) on four output responses: surface roughness, machining time, surface hardness, and burr thickness. Experiments were conducted using a Taguchi L27 orthogonal array on three distinct hole…
Genes, proteins, chemicals, diseases, species, mutations and cell lines named across the full text — each resolved to its canonical identifier and authoritative record.
Click any figure to enlarge with its caption.
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 1
Figure 20
Figure 21
Figure 22
Figure 23
Figure 24
Figure 25
Figure 26
Figure 27
Figure 28
Figure 29
Figure 2
Figure 30
Figure 31
Figure 32
Figure 33
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsAdvanced machining processes and optimization · Laser Material Processing Techniques · Welding Techniques and Residual Stresses