In the bustling world of manufacturing, there are a lot of moving parts to keep track of and often it is up to operators to keep track of all the moving parts. The training of operators is an obvious first step to improve safety, but operators cannot be solely relied on.
With the implementation of IoT devices, there is great potential to improve safety and reduce reliance on manual processes. This project is about developing a smart anti-collision system using the steel mill of New Zealand Steel as an application scenario.
New Zealand Steel is the biggest single-site manufacturing employer in New Zealand at its site in Glenbrook. It produces 670,000 tonnes of steel per year in a range of products used for construction, infrastructure, rural and transport applications.
Due to the safety risk of not having any anti-collision systems in place in the steel mill, New Zealand Steel are looking to implement a system that can assist crane and vehicle operators in avoiding collisions.
Research questions:
· How could we account for various modes of operations undertaken by the? There are 6 routine tasks and an estimated 20 non-routine low-frequency tasks that would be important to consider for the robustness of the system in all modes of operation.
· How can we align our anti-collision system with the industry standards? This will explore what safety measures are critical for operation and will involve research into the Industry
4.0 standards such as OPC UA.
· How can we use the real-time location readings to further improve safety? This could explore using machine learning for predictive maintenance and to alert when failure will occur based on historic readings.
· How accurate can UWB and NFC communication be? If a scaled-down prototype system can be functional does this mean a true scale system should be equally simple? What are the limitations?
· How can we apply all this research to the site-specific environment at New Zealand Steel? Considering factors such as dust levels, temperatures, and increased traffic due to the Electric Arc Furnace project. It would be good to individually key people involved with the day-to-day operations to understand user needs and to have a better understanding of the system that is needed.
Undergraduate
This project will see the team developing a control system that will use IoT devices to control alarming process and potentially using the readings to control actuating within the system.
· Recommending technologies to New Zealand Steel to optimise safety and efficiency according to user needs.
· Research and design of a robust actuating system to work under multiple modes of operation.
· Carry out a confined test on-site.
None
Manufacturing Systems (405.870, Lab)