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Project 4.4: Data analytics and process validation of collaborative robots and automated processes

PhD Researcher

Project based at

Lead Partner Organisation

Automated and collaborative robotic enabled processes naturally generate data. The validation, intentional use, and interrogation of this data can be leveraged to support quality assurance and process reliability, or to detect anomalies and ensure appropriate health and safety actions. Such data can also be used to refine the operation of a digital twin or be cross-checked against an operational twin in order to detect anomalies.

This Project will determine general and use-case specific methods for leveraging instrumented processes. General methods will promote rapid deployment to a wide range of applications and use-case specific methods will provide detailed solutions to industry traceability and reporting needs.

The role of digital twins in process validation and documentation will also be investigated.

  • The aim of the research is to apply concepts of Zero-Defect Manufacturing to solve real-world problems within the scope of Real-Time Quality Assurance, Quality Control of High-mix low-volume production and intuitive collaboration in safety settings.
  • Outcomes of this have been an ACRA publication on Haptic Devices with VR Interfaces, a submitted paper at MSEC 2023 on Non-Planar Additive Manufacturing and an ongoing research project with BTP on improving the safety of high-risk maintenance procedures.
  • The Project is exploring environments where these systems could have a great impact like Dubai, where we got to explore the Dubai Future Labs which is working on tackling the same problems.

Associated Researchers

Lee Clemon

Associate Investigator
University of Technology Sydney / University of Illinois Urbana-Champaign
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Michelle Dunn

Research Program Co-lead (Quality Assurance and Compliance)
Swinburne University of Technology
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Anushani Bibile

Alumni
Swinburne University of Technology
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Chris McCarthy

Chief Investigator
Swinburne University of Technology
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Danial Rizvi

PhD Researcher
University of Technology Sydney
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