In the steel manufacturing industry, torpedo vehicles transport ladles containing molten metal (temperature of 1400-1500 Deg C) along a rail track. Each Torpedo vehicle is equipped with a pair of leaf spring stacks to support the ladles during transit. A leaf spring stack comprises 24 leaf springs and bears a load of approximately 200 tons.
The leaf spring stacks are crucial for the safe transportation of molten metal. However, the industry has experienced recurring failures in the leaf spring stacks. These failures pose a significant safety risk as they can lead to the spillage of molten metal and result in unplanned outages, adversely affecting productivity. Detecting leaf spring failures online ( while the car is in service) is challenging, especially during the operational phase of the Torpedo vehicle. Over the past four financial years, there have been many leaf spring failures, causing unplanned outages in the hot metal logistics process. Addressing this issue is imperative to enhance safety, prevent productivity disruptions, and optimize the reliability of the Torpedo vehicle system.
We are seeking solutions that enable real-time monitoring and early indication of the Torpedo’s leaf spring stack failure while in operation, thus indicating the health of spring stack. This approach aims to mitigate safety hazards and minimize unplanned outages in crucial hot metal logistic lines.
Successful submissions should consider the feasibility of implementing the solution within the existing infrastructure. Additionally, providing information on existing, readily available systems or identifying potential startups or companies capable of developing such solutions will enhance your chances.
Awards:- 5,000,00
Deadline:- 23-06-2025
