In Situ Process Monitoring for Additive Manufacturing Through Acoustic Techniques

被引:60
|
作者
Hossain, Md Shahjahan [1 ]
Taheri, Hossein [1 ]
机构
[1] Georgia Southern Univ, Dept Mfg Engn, Statesboro, GA 30460 USA
关键词
acoustic emission (AE); additive manufacturing (AM); non-destructive testing (NDT); process monitoring; QUALITY-CONTROL; EMISSION; LASER; MICROSTRUCTURE; ULTRASOUND;
D O I
10.1007/s11665-020-05125-w
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Additive manufacturing (AM) is an emerging field where a complex geometrical model can be made with no requirement of individual parts and assembly production. This advantage provides the capability for fabricating components in a single integrated process. On the contrary, lack of non-destructive testing adoption due to complex geometries of final products, makes this technology less convenient for the production of critical parts with high accuracy. Non-destructive testing through acoustic techniques is one of the most popular methodologies for AM inspection because of its provision to detect defects on the internal structure of the components. The technique has also been used in other types of fabrication processes (machining and welding) for defect monitoring. There are several studies where acoustic data acquisition and analysis have been done to detect cracks and other anomalies. In this paper, the progress of using acoustic techniques for AM process and part quality monitoring has been reviewed, and critical discussion has been made for the potential application of acoustic techniques toward quality inspection and monitoring in AM technology.
引用
收藏
页码:6249 / 6262
页数:14
相关论文
共 50 条
  • [1] In Situ Process Monitoring for Additive Manufacturing Through Acoustic Techniques
    Md Shahjahan Hossain
    Hossein Taheri
    Journal of Materials Engineering and Performance, 2020, 29 : 6249 - 6262
  • [2] MACHINE LEARNING TECHNIQUES FOR ACOUSTIC DATA PROCESSING IN ADDITIVE MANUFACTURING IN SITU PROCESS MONITORING A REVIEW
    Taheri, Hossein
    Zafar, Suhaib
    MATERIALS EVALUATION, 2023, 81 (07) : 50 - 60
  • [3] In-situ process monitoring for metal additive manufacturing through acoustic techniques using wavelet and convolutional neural network (CNN)
    Md Shahjahan Hossain
    Hossein Taheri
    The International Journal of Advanced Manufacturing Technology, 2021, 116 : 3473 - 3488
  • [4] In-situ process monitoring for metal additive manufacturing through acoustic techniques using wavelet and convolutional neural network (CNN)
    Hossain, Md Shahjahan
    Taheri, Hossein
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2021, 116 (11-12): : 3473 - 3488
  • [5] In-situ Acoustic Signature Monitoring in Additive Manufacturing Processes
    Koester, Lucas W.
    Taheri, Hossein
    Bigelow, Timothy A.
    Bond, Leonard J.
    Faierson, Eric J.
    44TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 37, 2018, 1949
  • [6] Acoustic laser triangulation and tagging for additive manufacturing process monitoring
    Jan Petrich
    Robert W. Smith
    Edward (Ted) W. Reutzel
    The International Journal of Advanced Manufacturing Technology, 2023, 129 : 3233 - 3245
  • [7] Acoustic Monitoring of Additive Manufacturing for Damage and Process Condition Determination
    Koester, Lucas W.
    Taheri, Hossein
    Bond, Leonard J.
    Faierson, Eric J.
    45TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 38, 2019, 2102
  • [8] Acoustic laser triangulation and tagging for additive manufacturing process monitoring
    Petrich, Jan
    Smith, Robert W.
    Reutzel, Edward W.
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2023, 129 (7-8): : 3233 - 3245
  • [9] Infrared-assisted Acoustic Emission Process Monitoring for Additive Manufacturing
    Plotnikov, Yuri
    Henkel, Dan
    Burdick, Jeffrey
    French, Arthur
    Sions, John
    Bourne, Keith
    45TH ANNUAL REVIEW OF PROGRESS IN QUANTITATIVE NONDESTRUCTIVE EVALUATION, VOL 38, 2019, 2102
  • [10] In-situ monitoring additive manufacturing process with AI edge computing
    Zhu, Wenkang
    Li, Hui
    Shen, Shengnan
    Wang, Yingjie
    Hou, Yuqing
    Zhang, Yikai
    Chen, Liwei
    OPTICS AND LASER TECHNOLOGY, 2024, 171