Difference between revisions of "Projects:2019s2-20001 Using Machine Learning to Determine Deposit Height and Defects for Wire + Arc Additive Manufacture (3D printing)"

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== Background ==
 
== Background ==
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=== Wire Arc Additive Manufacturing ===
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Wire and Arc Additive Manufacturing (WAAM) is a type of additive manufacturing that uses electric arc as the heat source and material wire to feed the manufacture process <ref name="WAAM"> S. W. Williams, F. Martina, A. C. Addison, J. Ding, G. Pardal & P. Colegrove (2016) Wire + Arc Additive Manufacturing, Materials Science and Technology, 32:7, 641-647, DOI: 10.1179/1743284715Y.0000000073 </ref>. WAAM has been investigated since the 1990s <ref name="WAAM" />, but only recently that it received more attention from the manufacture world.
  
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=== Gas metal arc welding (GMAW) ===
  
=== Topic 1 ===
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==== Pulse Arc Welding ====
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==== Cold Metal Transfer ====
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=== Machine Learning ===
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==== Support Vector Machine ====
  
 
== Method ==
 
== Method ==
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== References ==
 
== References ==
[1] a, b, c, "Simple page", In Proceedings of the Conference of Simpleness, 2010.
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<references />
 
 
[2] ...
 

Revision as of 17:39, 5 October 2019

Abstract here

Introduction

3D printing is an emerging technology that has the potential to significantly reduce material usage through the production of near net-shape parts. Many of the systems for 3D printing are based on lasers and powders; however the deposition rate with such systems is very low making the production of large-scale parts difficult. AML Technologies specialises in the use of Wire + Arc Additive Manufacture (WAAM) where deposition is based on arc welding processes and the deposition rates are an order of magnitude greater. When building 3D printed parts, even a relatively small layer height error of only 0.1 mm can produce large build height errors when multiplied across the many layers of a typical build. This can make path planning difficult, so in-process layer height measurement is an essential building block of any production 3D printing system. A variety of techniques can be used for monitoring the layer height including laser scanners, and arc monitoring. It is the latter technique that will be explored in this project due to its robustness, and low cost of implementation – it only requires the measurement of arc current and voltage. Furthermore, it can potentially be used to detect defects by identifying waveform irregularities.

Project team

Project students

  • Anh Tran
  • Nhat Nguyen

Supervisors

  • Dr. Brian Ng
  • Dr. Paul Colegrove (AML3D)

Aml3d logo.jpg

Objectives

The objective of this project is to increase the efficiency of the manufacture process at AML3D. In order to do so, the team will investigate into the possibility of automating and optimising the quality control processes. The two quality control processes that are currently being implemented at AML3D are measuring layer height using laser sensors, and human supervision for detecting defects. These processes add overhead into production time and usage of human resource, which is not desired. To achieve the goal, it is expected that machine learning methods will be used extensively to analyse the electrical signatures of the weld process.

Background

Wire Arc Additive Manufacturing

Wire and Arc Additive Manufacturing (WAAM) is a type of additive manufacturing that uses electric arc as the heat source and material wire to feed the manufacture process [1]. WAAM has been investigated since the 1990s [1], but only recently that it received more attention from the manufacture world.

Gas metal arc welding (GMAW)

Pulse Arc Welding

Cold Metal Transfer

Machine Learning

Support Vector Machine

Method

Results

Conclusion

References

  1. 1.0 1.1 S. W. Williams, F. Martina, A. C. Addison, J. Ding, G. Pardal & P. Colegrove (2016) Wire + Arc Additive Manufacturing, Materials Science and Technology, 32:7, 641-647, DOI: 10.1179/1743284715Y.0000000073