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Anyone who has ever had a car knows how easy it is for tires to fail if they are not maintained correctly. Air pressure needs to be checked, and owners must pay attention to signs of uneven wear. Ignoring proper maintenance can lead to early tire failure and accidents.
But consider the tire maintenance problem facing mining companies: Poor care may result in worker injuries and financial losses of millions of dollars.
Solutions based on the Internet of Things (IoT) are strategies that mining companies are adding to the predictive maintenance programs. These strategies are part of the larger trend in Industry 4.0: What’s Next, 2017.
Tires as IoT Objects
To improve worker safety and protect assets, the mining industry is turning to the IoT in many ways. Analysis of wear on tires is one example.
When fitted with data-gathering sensors that share information via the Internet, tires become IoT objects. The sensors measure information such as under-inflation, over-inflation, overloading, speed outside guidelines, interior and exterior temperatures, road conditions and impacts.
You might say the sensors make it possible for the tires to "talk" through the Internet. IoT solution software used by the company gathers and analyzes the data in real time. Engineers and company managers on and offsite then can perform planning and troubleshooting.
Many mining companies are embracing digital transformation. This involves connecting all their mines, buildings, equipment and vehicles to the Internet via sensors. The resulting flood of information is what we call big data.
IoT solution software works together to sort and analyze the data. Their work is coordinated by a higher level platform that can work rapidly so that engineers and other staff in offices far from the mine receive alerts almost as soon as an event -- such as a tire blowout -- occurs.
What's the big deal about a tire blowing? We'll get to that in a bit, but first we need to visit Western Australia's Roy Hill iron ore mine.
Remote Tracking of Tire Life
One way that Roy Hill is controlling costs is through its remote operations center in Perth, about 1,308 km (813 miles) away from the mine.
Australia's IT News reported last January that the center's business improvement team is using SAP IoT solutions to analyze data regarding tires, the loads on trucks and other rolling stock, environmental factors and driver behavior.
The team accesses the findings to shape "operator training, speed guidelines and road layouts," IT News stated. It added that "expected tyre life is now being achieved."
IT News further noted that Rio Tinto is using IoT data for predicting maintenance needs. It is also testing 3D visualizations -- sometimes referred to as "digital twins" -- to visualize its operations. Digital twin software can create a computerized replica of a piece of equipment. Engineers and managers at locations remote from a mine can use the twin to pinpoint maintenance needs and diagnose repairs, including those for tires.
To understand the costs of modern mining, it helps to consider a single vehicle that until recently was called the "world's biggest dump truck."
Tires for a Mammoth Earthmover
The driverless Caterpillar 797F for pit mining defines "monster truck." This YouTube video illustrates its size and power. At 5:19 minutes into the video, the CAT 797F turns a standard pickup truck into a pancake.
How big is this autonomous behemoth? The CAT 797F is about 15 m tall (48 ft) when its dump body is tilted up. At approximately 9 m wide (30 ft) and as long as it is tall, this earthmover covers almost half the area of a basketball court. When fully loaded with fuel and ore, the truck weighs about 624,000K (1.375 million lbs or about 624 tons).
Here is where we get back to the question of why a flat tire is such a big deal in mining.
The CAT 797F runs on six tires, each standing 13 feet tall and weighing nearly 12,000 pounds. The cost per tire is about $69,000 or just short of $500,000 for a complete set.
Of course, the cost of a massive tire's blowout does not take into account harm to workers or financial damage to the truck and any surrounding equipment or structures. It also does not indicate the amount of money a mining company may lose per day during the repair process.
As IoT expert Maciej Kranz explained in his July 2017 article at Medium, a large mining company such as Rio Tinto may lose up to $2 million a day for a single out-of-service truck. That figure is magnified by the fact that the company may need to pull another truck out of service to tow the damaged truck out of the pit.
Kranz noted that IoT tools improve the process of predicting when repairs and replacement will be necessary for mining equipment. "With preventive maintenance, " Kranz wrote, "you fix a problem before it happens — not after it has wreaked havoc inn your production schedule."
Future of IoT in Predictive Maintenance
Writing for software knowledge base publisher DZone in May 2017, Zana Diaz reported that predictive maintenance has become "one of the leading use cases for the Industrial Internet of Things."
Diaz noted DZone's analysis that the market for IIoT-based predictive maintenance may expand from $2.2 billion this year to nearly $11 billion in 2022. That's a lot of sensors and connectedness. It is also commonsense problem solving.
But consider the tire maintenance problem facing mining companies: Poor care may result in worker injuries and financial losses of millions of dollars.
Solutions based on the Internet of Things (IoT) are strategies that mining companies are adding to the predictive maintenance programs. These strategies are part of the larger trend in Industry 4.0: What’s Next, 2017.
Tires as IoT Objects
To improve worker safety and protect assets, the mining industry is turning to the IoT in many ways. Analysis of wear on tires is one example.
When fitted with data-gathering sensors that share information via the Internet, tires become IoT objects. The sensors measure information such as under-inflation, over-inflation, overloading, speed outside guidelines, interior and exterior temperatures, road conditions and impacts.
You might say the sensors make it possible for the tires to "talk" through the Internet. IoT solution software used by the company gathers and analyzes the data in real time. Engineers and company managers on and offsite then can perform planning and troubleshooting.
Many mining companies are embracing digital transformation. This involves connecting all their mines, buildings, equipment and vehicles to the Internet via sensors. The resulting flood of information is what we call big data.
IoT solution software works together to sort and analyze the data. Their work is coordinated by a higher level platform that can work rapidly so that engineers and other staff in offices far from the mine receive alerts almost as soon as an event -- such as a tire blowout -- occurs.
What's the big deal about a tire blowing? We'll get to that in a bit, but first we need to visit Western Australia's Roy Hill iron ore mine.
Remote Tracking of Tire Life
One way that Roy Hill is controlling costs is through its remote operations center in Perth, about 1,308 km (813 miles) away from the mine.
Australia's IT News reported last January that the center's business improvement team is using SAP IoT solutions to analyze data regarding tires, the loads on trucks and other rolling stock, environmental factors and driver behavior.
The team accesses the findings to shape "operator training, speed guidelines and road layouts," IT News stated. It added that "expected tyre life is now being achieved."
IT News further noted that Rio Tinto is using IoT data for predicting maintenance needs. It is also testing 3D visualizations -- sometimes referred to as "digital twins" -- to visualize its operations. Digital twin software can create a computerized replica of a piece of equipment. Engineers and managers at locations remote from a mine can use the twin to pinpoint maintenance needs and diagnose repairs, including those for tires.
To understand the costs of modern mining, it helps to consider a single vehicle that until recently was called the "world's biggest dump truck."
Tires for a Mammoth Earthmover
The driverless Caterpillar 797F for pit mining defines "monster truck." This YouTube video illustrates its size and power. At 5:19 minutes into the video, the CAT 797F turns a standard pickup truck into a pancake.
How big is this autonomous behemoth? The CAT 797F is about 15 m tall (48 ft) when its dump body is tilted up. At approximately 9 m wide (30 ft) and as long as it is tall, this earthmover covers almost half the area of a basketball court. When fully loaded with fuel and ore, the truck weighs about 624,000K (1.375 million lbs or about 624 tons).
Here is where we get back to the question of why a flat tire is such a big deal in mining.
The CAT 797F runs on six tires, each standing 13 feet tall and weighing nearly 12,000 pounds. The cost per tire is about $69,000 or just short of $500,000 for a complete set.
Of course, the cost of a massive tire's blowout does not take into account harm to workers or financial damage to the truck and any surrounding equipment or structures. It also does not indicate the amount of money a mining company may lose per day during the repair process.
As IoT expert Maciej Kranz explained in his July 2017 article at Medium, a large mining company such as Rio Tinto may lose up to $2 million a day for a single out-of-service truck. That figure is magnified by the fact that the company may need to pull another truck out of service to tow the damaged truck out of the pit.
Kranz noted that IoT tools improve the process of predicting when repairs and replacement will be necessary for mining equipment. "With preventive maintenance, " Kranz wrote, "you fix a problem before it happens — not after it has wreaked havoc inn your production schedule."
Future of IoT in Predictive Maintenance
Writing for software knowledge base publisher DZone in May 2017, Zana Diaz reported that predictive maintenance has become "one of the leading use cases for the Industrial Internet of Things."
Diaz noted DZone's analysis that the market for IIoT-based predictive maintenance may expand from $2.2 billion this year to nearly $11 billion in 2022. That's a lot of sensors and connectedness. It is also commonsense problem solving.