Chih-Kuang Lin

This study focused on the efficacy of employing a pulsed fiber laser in the curved cutting of thin, non-oriented electrical steel sheets. Experiments were conducted in paraffinic oil by adjusting the input process parameters, including laser power, pulse frequency, cutting speed, and curvature radius. The multiple output quality metrics included kerf width, inner and outer heat-affected zones, and re-welded portions. Analyses of the Random Forest Method and Response Surface Method indicated that laser pulse frequency was the most important variable affecting the cut quality, followed by laser power, curvature radius, and cutting speed. To improve cut quality, an innovative artificial intelligence (AI) approach incorporating a deep neural network (DNN) model and a modified equilibrium optimizer (M-EO) was proposed. Initially, the DNN model established correlations between input parameters and cut quality aspects, followed by M-EO pinpointing optimal cut qualities. Such an approach successfully identified an optimal set of laser process parameters, even beyond the specified process window from the initial experiments on curved cuts, resulting in significant enhancements confirmed by validation experiments. A comparative analysis showcased the developed models’ superior performance over prior studies. Notably, while the models were initially developed based on the results from curved cuts, they proved adaptable and capable of yielding comparable outcomes for straight cuts as well.

A novel PID-type fuzzy logic controller (FLC) with an online fuzzy tuner was created to maintain stable in situ control of the cutting front temperature, aiming to enhance the laser process for thin non-oriented electrical steel sheets. In the developed controller, the output scaling factors and the universe of discourse were initially optimized using a hybrid of the particle swarm optimization and grey wolf optimization methods. The optimal parameters obtained were utilized in experiments involving the laser cutting of thin non-oriented electrical steel sheets, compared to an open-loop control system maintaining a constant cutting speed. The PID-type FLC with an online fuzzy tuner demonstrated a superior cutting quality, generating a smaller roundness and a reduced heat-affected zone (HAZ) through the in situ tuning of control parameters. Particularly, the HAZ width was significantly smaller than that reported in a previous study which used fuzzy gain scheduling for temperature control. Moreover, the cutting time was diminished by optimally adjusting the cutting speed using PID-type FLC with an online fuzzy tuner. Therefore, the accumulated heat in the steel sheet, particularly under high laser pulse frequencies, was effectively reduced, making it suitable for industrial applications.

This study investigates the effect of laser volume energy density (VED) on the properties of AISI 420 stainless steel and TiN/AISI 420 composite manufactured by selective laser melting (SLM). The composite contained 1 wt.% TiN and the average diameters of AISI 420 and TiN powders were 45 µm and 1 µm, respectively. The powder for SLMing the TiN/AISI 420 composite was prepared using a novel two-stage mixing scheme. The morphology, mechanical, and corrosion properties of the specimens were analyzed, and their correlations with microstructures were investigated. The results showed that the surface roughness of both SLM samples decreases with increasing VED, while relative densities greater than 99% were achieved at VEDs higher than 160 J/mm³. The SLM AISI 420 specimen fabricated at a VED of 205 J/mm³ exhibited the highest density of 7.7 g/cm³, tensile strength (UTS) of 1270 MPa, and elongation of 3.86%. The SLM TiN/AISI 420 specimen at a VED of 285 J/mm³ had a density of 7.67 g/cm³, UTS of 1482 MPa, and elongation of 2.72%. The microstructure of the SLM TiN/AISI 420 composite displayed a ring-like micro-grain structure consisting of retained austenite on the grain boundary and martensite in the grain. The TiN particles strengthened the mechanical properties of the composite by accumulating along the grain boundary. The mean hardnesses of the SLM AISI 420 and TiN/AISI 420 specimens were 635 and 735 HV, respectively, which exceeded previously reported results. The SLM TiN/AISI 420 composite exhibited excellent corrosion resistance in both 3.5 wt.% NaCl and 6 wt.% FeCl₃ solutions, with a resulting corrosion rate as low as 11 µm/year.