“Infor as a partner is allowing us to move from paper to mobile to sensors. It allows us to move from being reactive to proactive to predictive.”
The mining industry is fraught with complexity and can greatly benefit using advanced data science to manage the facilities, equipment, and operational processes. For example, tires used in the mining industry are mammoth, standing over twice as tall as humans and 50 times heavier in some cases. This ultra large machinery drives up costs since highly trained technicians using specialized tools and processes are required to change these tires effectively and safely.
Applying artificial intelligence (AI) to this complex process is an industry game changer, and Kal Tire’s Mining Tire Group is at the forefront of this transformation. It has developed its own Tire Operations Management System (TOMS), an industry-leading productivity tool built on Infor’s cloud-based enterprise asset management (EAM) system to address the highly specialized needs of mining. More than 150 mine sites across five continents rely on Kal Tire to help track, plan, and manage all tire-related processes. With TOMS, site operators and technicians also have visibility into performance trends to identify more ways to improve uptime and safety for mining equipment.
“Our goal is to help customers manage their tires and wheels on mine sites and to make sure the trucks run with the least downtime and as safely as possible,” says Christian Erdélyi, TOMS System & Implementation Manager Global at Kal Tire’s Mining Tire Group.
Kal Tire began its AI journey earlier this year by integrating TOMS with Pitcrew.ai to bring autonomous detection of hot tires, tire separations and other damage without the vehicle needing to stop. Infor’s cloud technology layers in more automation and intelligence capabilities to the Pitcrew integration to further help miners avoid unnecessary downtime, risk, and cost.
“Infor as a partner is allowing us to move from paper to mobile to sensors. It allows us to move from being reactive to proactive to predictive. That's a journey. It'll have bumps, but it's a cleared path and we're heading down it,” says Erdélyi.
Infor’s cloud technology platform, which includes Infor Coleman AI, addresses two fundamental areas of tire management: tire fitment and visual inspection. The AI-driven tire fitment process predicts tire replacement time to better forecast demand at each customer site, optimizing fleet availability and tire utilization. AI-driven visual inspection with Pitcrew sensor integration proactively detects tire issues and generates work orders to improve site productivity and safety. Kal Tire expects the following results after final implementation and testing is complete:
- 20% reduced downtime with more accurate tire forecasting so that each site has the right quantity and mix of tires at any time
- More effectiveness in detecting and diagnosing tire issues with autonomous visual inspections and system-generated work orders on mobile devices
AI also addresses the recruitment and retention challenge in the mining industry. It can be difficult to find people to manage and replace tires on mine sites. With Kal Tire starting to deploy autonomous vehicle inspection systems, they will be able to fulfill more contracts where recruitment proves particularly challenging. In fact, Pitcrew will enable Kal Tire to automate and reduce the more than 900,000 manual visual inspections it conducts annually.
Kal Tire Mining Group has found that moving to autonomous platforms enabled by AI will do work significantly more effectively than existing processes. Mining customers are reacting positively to these next generation services. Kal Tire has acquired three new contracts to provide automated inspection services to existing customers since the Pitcrew partnership was announced.
Infor solutions will provide the “glue,” or cloud technology, needed to apply and scale AI to key workflows for site operators and technicians. Junior and less-experienced personnel will especially appreciate the added confidence that comes from AI-driven issue recognition and system recommendations.
“We all have data, but it's the interoperability of that data and being able to use it to make better decisions that is critical. AI is just one piece of the puzzle. What makes this solution stand out is the connectivity from sensors to system processing to the delivery of insights on mobile to our field workers and customers in a consistent, user-friendly way,” says Erdélyi.
He goes on to explain the value of connectivity between systems, a detail that is often overlooked and underestimated. “The building blocks of successful use of AI is the engineering behind it and the ability to move data consistently in a usable form,” says Erdélyi.
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