Design and Realisation of a Monitoring System for Wire-Arc Additive Manufacturing

  • Fangda Xu

Student thesis: Doctoral ThesisPhD


Additive manufacturing (AM) has been growing at a significant rate over the last ten years. During this period, the process has moved from the prototyping of plastic and metal components to the generation of the industrial parts used in actual products. The major focus of AM has predominantly been related to powder-bed complex components, but the use of direct energy deposition (DED) processes is now becoming widely prevalent. This thesis focuses on research related to a DED process namely wire arc additive manufacturing (WAAM) and specifically the monitoring of the WAAM process for large scale components.

The aim of this research is to define and realize a monitoring framework for the WAAM processes which can be generically applied to different WAAM machines. Based on this aim a framework and monitoring system has been generated consisting of 3 sub-systems namely, Environment Monitoring Sub-system, Heat Monitoring Sub-system and Bead Geometry Monitoring Sub-system. These three sub-systems contain a suite of sensors that provide the ability to monitor oxygen level, argon gas flow rate, arc voltage, arc current, temperature of the part and geometric profile of the top and the side of the WAAM parts produced.

A set of three experiment has been devised to test the performance of the WAAM monitoring system. These evaluate the effectiveness of the system with validation of the voltage and current collected from the sensors, monitoring the process data and monitoring of the geometric shape of the WAAM part produced. This showed that the monitoring was able to precisely represent the WAAM process and provide a geometric accuracy of 0.01mm.

The WAAM monitoring system developed in this thesis has been shown to have the ability to monitor, record and analyse the major output of the WAAM processes. The system has been shown to provide rapid feedback at 5Hz that makes it possible to monitor the WAAM process in real time with the generation of repeatable high quality parts.
Date of Award13 May 2020
Original languageEnglish
Awarding Institution
  • University of Bath
SupervisorVimal Dhokia (Supervisor) & Stephen Newman (Supervisor)


  • Additive manufacturing
  • Welding
  • Process Control
  • Process Monitoring

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