研究目的
Investigating the effect of various process parameters on weld strength and weld seam width in laser transmission welding of thermoplastic materials using beam wobbling technique and optimizing the process parameters using Particle Swarm Optimization.
研究成果
The study concludes that beam wobbling significantly improves weld strength by enlarging the joint area, with wobble width being the most dominant parameter affecting weld width. Optimal process parameters for achieving the best weld strength and width are identified using PSO. The findings suggest that laser power, welding frequency, scanning speed, wobble width, and wobble frequency have strong interaction effects on both weld strength and width.
研究不足
The study is limited to the use of specific thermoplastic materials (transparent polycarbonate and black carbon filled PMMA) and a low power laser. The effect of wobble frequency on weld width is found to be minimal, indicating potential areas for further optimization.
1:Experimental Design and Method Selection:
The study uses Response Surface Methodology (RSM) to model the responses in terms of process parameters with a quadratic second order polynomial equation. Central composite unblocked design with five continuous factors is used for the design of experiment.
2:Sample Selection and Data Sources:
Transparent polycarbonate and black carbon filled PMMA, each of 2.8 mm thickness, are used as workpiece materials.
3:8 mm thickness, are used as workpiece materials.
List of Experimental Equipment and Materials:
3. List of Experimental Equipment and Materials: Electrox EMS 100 Raptor laser system with Nd:YVO4 diode laser, Comsol marker software, Instron universal tester, Mitutoyo Tool maker’s microscope.
4:Experimental Procedures and Operational Workflow:
The experimental work involves joining the materials using low power laser with beam wobbling technique, applying constant pressure between two workpiece materials, and conducting lap shear pull tests to assess weld strength.
5:Data Analysis Methods:
ANOVA is applied to evaluate the influence of individual process parameters on weld strength and width. Particle Swarm Optimization (PSO) is used for multi-objective optimization.
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