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In situ process monitoring of multi-layer deposition in wire arc additive manufacturing (WAAM) process with acoustic data analysis and machine learning

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Abstract

Additive manufacturing (AM) of metal components is expanding as a developing technique for fabricating high-value and large-scale metal parts. Among various metal AM procedures, wire arc additive manufacturing (WAAM) received special attention in recent years due to its unique potential for fabricating complex geometries in industrial scale and applications. In this study, a step forward for developing a continuous, multi-layer in-situ monitoring technique based on acoustic signatures recorded by acoustic emission nondestructive method over the deposition process is presented. The major goal of this research is to investigate if previously proven single-layer monitoring procedures based on acoustic signatures can be expanded toward a robust multi-layer and continuous monitoring method. Two different types of materials have been used in a WAAM process equipped with acoustic emission sensors, and recorded signals were analyzed by traditional statistical assessment as well as a K-mean clustering machine learning algorithm. The findings affirm the effectiveness of acoustic signals in monitoring processes during the continuous deposition of material and indicate that acoustic signals can reliably identify distinct process states across all layers. This underscores the reliability of acoustic signals as a multi-layer process monitoring method.

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Data Availability

Data for this article in form of acoustic signals are available upon request to the corresponding author.

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Funding

Funding from the Faculty Research Seed Grant (FRSG-2023) from the College of Engineering and Computing at Georgia Southern University is acknowledged.

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Authors and Affiliations

  1. Department of Manufacturing Engineering, Georgia Southern University, Statesboro, GA, 30458, USA

    Md Arifur Rahman & Hossein Taheri

  2. Department of Information Technology, Georgia Southern University, Statesboro, GA, 30458, USA

    Suhaima Jamal & Meenalosini Vimal Cruz

  3. Department of Mechanical Engineering, Georgia Southern University, Statesboro, GA, 30458, USA

    Bishal Silwal

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  1. Md Arifur Rahman
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Correspondence to Hossein Taheri.

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Rahman, M.A., Jamal, S., Cruz, M.V. et al. In situ process monitoring of multi-layer deposition in wire arc additive manufacturing (WAAM) process with acoustic data analysis and machine learning. Int J Adv Manuf Technol (2024). https://doi.org/10.1007/s00170-024-13641-5

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