A PHM Approach to Additive Manufacturing Equipment Health Monitoring, Fault Diagnosis, and Quality Control

Jae Yoon, David He, and Brandon Van Hecke
Submission Type: 
Full Paper
AttachmentSizeTimestamp
phmc_14_074.pdf1.14 MBSeptember 22, 2014 - 8:51am

Fabrication of three-dimensional (3D) objects through direct deposition of functional materials using 3D printing equipment is called additive manufacturing (AM). Benefits of AM include producing goods quickly and on-demand, with greater customization and complexity and less material waste. While the use of AM has been growing, a number of challenges continue to impede its more widespread adoption, particularly in the areas of non-destructive evaluation/non-destructive testing (NDE/NDT) techniques for AM equipment health monitoring and measurement. In this paper, a PHM approach to AM equipment health monitoring, fault diagnosis and quality control is presented and illustrated with a case study. The presented PHM approach is developed using two types of NDE/NDT sensors: acoustic emission (AE) sensor and piezoelectric strain sensor. A seeded driving belt fault is used on a fused filament fabrication desktop 3D printer in the case study. The case study results have shown the effectiveness of the presented method for AM equipment fault diagnosis and quality control.

Publication Year: 
2014
Publication Volume: 
5
Publication Control Number: 
074
Page Count: 
9
Submission Keywords: 
fault detection
Additive manufacturing equipment
acoustic emission sensors
3D printer
PE strain sensor
Submission Topic Areas: 
Data-driven methods for fault detection, diagnosis, and prognosis
Submitted by: 
  
 
 
 

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