The Silicon Review
“Our patent-protected, cutting-edge technologies aim to ‘extend machine senses’ so that mines can work smarter.”
Technology is transforming the way the mining industry operates. Increased demand for efficient production, a focus on worker safety, and greater interest in day-to-day data management have all driven the industry to embrace innovation – and a new generation of technology companies are providing mines with the tools to make positive change.
Motion Metrics is leading the charge among innovative mining suppliers. Their industry-leading equipment monitoring solutions leverage the latest in machine learning technology and rugged imaging to improve safety, efficiency, and productivity at mines and quarries worldwide. Motion Metrics was the first to apply artificial intelligence to mining technology, and their advanced monitoring solutions are the result of more than 15 years of research and development. They provide a range of products for mining equipment like shovels, loaders, and conveyor belts.
Motion Metrics was incorporated in 1999 and is headquartered in Vancouver, British Columbia. Dr. Shahram Tafazoli, Motion Metrics International Corp. CEO, spoke exclusively to the Silicon Review. Read on to learn how this industry-disrupting leader brought artificial intelligence to the mining industry.
Making Mines Smarter
Dr. Tafazoli first envisioned a market for smarter mining solutions while earning his Ph.D. from the University of British Columbia. “During that period, I was exposed to some of the toughest mining challenges,” he explains. “That’s when I realized that I could use a camera system and software to do image processing and address mining complexities.”
Breaking into the Market
His first product, a missing tooth detection system for mining shovels, put Motion Metrics on the map. “Shovel teeth can break off and cause a lot of damage,” Dr. Tafazoli explains. “People have lost their lives or been injured trying to remove jammed teeth from crushers.”
Providing accurate and reliable missing tooth detection in the harsh mining environment is a challenging task, but Dr. Tafazoli found success in the application of leading-edge technologies. “After considering several different approaches, we settled on a machine vision solution,” says Dr. Tafazoli. “We installed rugged cameras on the shovel so that the system could see the bucket teeth throughout the digging cycle, then analyzed the scene using deep learning and artificial intelligence. Essentially, when a tooth goes missing, an alarm notifies the shovel operator and a cloud-based system notifies the upper management.”
Today, Motion Metrics’ state-of-the-art missing tooth detection solution continues to be a favourite among mines worldwide. “I am proud to say that a number of large mining companies have made it policy to equip their shovels with our missing tooth detection system,” he says. “We feel good to have used the latest technology – machine vision and artificial intelligence – to make mining safer. Our missing tooth detection system is currently installed on more than 350 shovels around the world.”
Helping Mines Compete Under Challenging Conditions
With the golden era of mining behind us, mines must operate more efficiently to stay profitable. One way of reducing inefficiencies is mine-to-mill optimization – a holistic systems approach to minimizing energy and operating costs in mineral processing by optimizing all stages in the size reduction process (comminution). In recent years, Motion Metrics has focused much of its research and development efforts on designing products to help mines better understand – and optimize – stages in their comminution process. The potential savings these technologies promise are mammoth. “Today, roughly four percent of the world’s electrical energy is consumed by comminution,” Dr. Tafazoli explains. “If we can reduce that number from four to three percent, the savings would be amazing. We are talking about millions of dollars per operation. Moreover, it’s better for the environment.”
Looking to the Future
The newest product Motion Metrics has released, BeltMetrics™, marks an important development in their product line for mine-to-mill optimization. With this new solution, mines can analyze unit operations along the entire comminution circuit.
BeltMetrics™ uses 3D machine vision to analyze material on mining conveyor belts and is currently being trialed. So far, feedback has been overwhelmingly positive. “We are field testing the product with a big mining company in Western Australia and the results have been amazing,” says Dr. Tafazoli.
The Importance of Client Relationships
Dr. Tafazoli believes that much of his company’s stellar reputation is owed to prioritizing client relationships. “Sometimes we have challenges, but we don’t give up,” he explains. “We work closely with our customers to see how we can address their concerns, and we communicate quite efficiently. Internally, we hold a lot of meetings and debriefing sessions to streamline operations. We have a team that has helped us to succeed and thrive in the market.”
The numbers confirm his instincts. This summer, Motion Metrics announced its third consecutive year of 30%+ revenue growth. The company secured a record number of service and support agreements, and also opened a new office in Perth, Australia to accommodate growing client demand. Continued growth requires an organization-wide commitment to strategic objectives, and Motion Metrics is eager to meet that challenge.
Dr. Shahram Tafazoli: A Brief Background
Dr. Shahram Tafazoli is the CEO of Motion Metrics International Corp., a private Canadian corporation dedicated to improving mine safety and efficiency using artificial intelligence, computer vision, 3D imaging, and cloud computing. Dr. Tafazoli conducted his thesis in Electrical and Computer Engineering at the University of British Columbia, where he is now an adjunct professor. Dr. Tafazoli is also an avid inventor holding several patents, an angel investor in several promising tech start-ups, and an active member of the Creative Destruction Lab.