Multi-objective optimization of laser spot welding parameters for enhancing mechanical properties of hard disk components using response surface methodology
This study investigates the optimization of laser welding parameters for stainless-steel components using response surface methodology. The aim is to achieve robust joints and sufficient contact between components by employing a laser spot preheating technique followed by subsequent laser spot appli...
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| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2025-03-01
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| Series: | Results in Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2590123025005274 |
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| Summary: | This study investigates the optimization of laser welding parameters for stainless-steel components using response surface methodology. The aim is to achieve robust joints and sufficient contact between components by employing a laser spot preheating technique followed by subsequent laser spot application for joining. The parameters considered include outer diameter (OD), inner diameter (ID), penetration, and tip height. Through a central composite design matrix experiment and quadratic modeling, empirical mathematical models were established to predict the response variables. The study reveals significant relationships between power flash ramps, time flash ramps, and N2 flow rate, particularly influencing tip height and ID. Multi-objective optimization using a desirability function was employed to determine the optimal process parameters. The optimal process parameters were determined to be power flash ramp 1 at 2.15 kW, time flash ramp 1 at 0.5 ms, power flash ramp 2 at 2.83 kW, time flash ramp 2 at 1.2 ms and N2 flow rate at 18 l/min Finally, empirical model validation was performed, resulting in slight differences between the predicted and actual values of OD, ID, penetration and tip height which were 6.614.00%, 4.60%, 8.398% and 15.42% respectively. The validation test results indicated that the proposed models showed good agreement between the actual values and the predicted values from the optimization. |
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| ISSN: | 2590-1230 |