Laser transmission welding of ABS polymers: a systematic study of parameter-quality correlations and interfacial morphology
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Ghulam Anwer
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Bappa Acherjee
Abstract
A comprehensive analysis of laser transmission welding (LTW) of acrylonitrile butadiene styrene (ABS), a widely used engineering plastic for structural applications, is presented in this research paper. The efficiency and reliability of LTW for ABS are examined by analyzing the complex interactions between process parameters and weld characteristics, as well as through the study of fracture surface characteristics and weld morphology. Systematic experimentation combined with response surface methodology is employed to develop precise mathematical models correlating process parameters with weld quality. Optimization strategies are explored to identify parameter configurations yielding desired weld quality. It is observed that higher laser power enhances weld strength by improving energy transfer, while careful balancing of scanning speeds prevents overheating, and increased stand-off distances improve both weld strength and width. Fracture surface analysis reveals significant fibril elongation and interlayer deformation, demonstrating the effectiveness of LTW in enhancing weld quality through improved interfacial bonding and material integration. The research provides key insights into LTW for ABS, emphasizing parameter interactions, weld quality, fracture characteristics, morphology, and optimal processing conditions for advanced engineering applications.
Acknowledgments
The authors gratefully acknowledge the Central Instrumentation Facility (CIF) of BIT Mesra, Ranchi, India, for the testing carried out in this work.
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Research ethics: Not applicable.
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Informed consent: Not applicable.
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Author contributions: All authors have accepted responsibility for the entire content of this manuscript and approved its submission. G.A: investigation, methodology, formal analysis, writing – original draft. B.A.: conceptualization, visualization, supervision, writing – review & editing.
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Use of Large Language Models, AI and Machine Learning Tools: None declared.
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Conflict of interest: The authors state no conflict of interest.
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Research funding: B.A. would like to acknowledge partial financial support from ANRF/SERB, DST (India) sponsored projects (CRG/2021/001066, Dt. 03-03-2022), (CRG/2022/004102, Dt. 14-02-2023) and (CRG/2023/0003537, Dt. 23-02-2024).
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Data availability: The datasets generated and/or analyzed during the current study are available from the corresponding author on reasonable request.
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Supplementary Material
This article contains supplementary material (https://doi.org/10.1515/polyeng-2025-0016).
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