Projects

Industrial IoT System for Automated AI-Defect ​Detection of Concrete Sleepers


15 Jan 2025 - 14 Jan 2026
Swinburne University of Technology
$357,373
Engineered Solutions

Challenge and proposed solution

Quality control ensures concrete sleepers adhere to Australian and international standards. But current quality control processes rely on manual inspection methods that are time-consuming and susceptible to human error. These methods can result in product inconsistencies, leading to costly returns and reworks.

In this project, Swinburne University and Sunset Sleepers have partnered to create a solution. They will develop an industrial internet-of-things system which will use AI to detect and report defects in concrete sleepers. This automated process will replace manual inspection to free up workers to focus on other critical tasks while making quality control more precise, efficient and consistent. Over time, the system will generate valuable data and help identify defect-causing issues during production.

The insights gained in this project will also be applicable beyond sleepers to comparable precast concrete products facing similar quality control challenges, leading to industry-wide improvements to manufacturing standards and practices.

 


PROJECT PARTNERS

  • Sunset Sleepers
  • Swinburne University of Technology