Dirty power is one of the biggest threats to operational uptime in the mining industries. It frequently results in costly unplanned shutdowns and escalates expenses. Even as mining companies seek to maximize reliability, few if any truly account for this insidious problem, jeopardizing their whole operation’s productivity and ultimately their profitability. For Denis Kouroussis, CEO of Volta Insite, the crisis highlighted the need for smart solutions. He’s an evangelist for incorporating AI-assisted maintenance tools to help fill this gap. These innovations help them quickly detect early warning signs of electrical degradation. As a result, they notionally mitigate the harmful impacts of fossil fuel-derived electricity on mining activities.
Along with Kouroussis, a PhD computer engineer who became an experienced entrepreneur and founder of several companies. As co-founders of Atom Power, they created the world’s first UL-listed solid-state circuit breaker. His extensive background in technology and entrepreneurship positions him uniquely to address the pressing challenges faced by the mining sector today.
The Challenge of Dirty Power
Dirty power is an umbrella term for faulty electrical supply that’s irregular or has transients that interrupt equipment operation. This concern is often time-squeezed in the mining world, where dependability of operations is king. The ripple effects of dirty power result in unanticipated downtimes that are expensive and hurt productivity across the board.
For decades, the mining industry has focused on reactive solutions to solve electrical problems when they occur. This way does not consider what causes the electrical degradation in the first place. Organizations unwilling to acknowledge dirty power as a top existential threat do so at their own peril. This exclusion can result in costly unplanned shutdowns that drastically impact their bottom line.
Through her work, Kouroussis aims to help people experience dirty power firsthand so they can better understand and confront it. He wants to shine a light on the challenge and its perilous implications because he feels the first step in defeating this challenge is understanding that it exists. In taking these actions, mining companies will be in a much stronger position to proactively adopt high-impact strategies that significantly improve operational reliability.
Leveraging AI for Predictive Maintenance
AI-powered predictive maintenance provides a proactive solution to help mitigate the impacts of dirty power. These intelligent tools enable mining operations to detect the early warning signs of electrical deterioration. This proactive, preventative approach prevents one small issue from becoming a bigger, more expensive problem. AI systems utilize data analytics and machine learning algorithms to track equipment performance in real-time. Their predictive capabilities provide important foresight that allows more proactive and timely interventions to take place.
Kouroussis adds that when you have AI-assisted maintenance tools, a problem can be diagnosed remotely, resulting in dramatically decreased downtime. In reality, saving a single day of unplanned shutdowns can pay for the entire predictive maintenance program. With this capability in their hands, mining companies can make both operational efficiency and increased profitability core tenets of their business.
Plus, deploying these AI solutions fosters a culture of continuous improvement across mining organizations. As companies gain insights into their processes and equipment performance, they can refine their strategies and optimize their operations over time.
Bridging Skills Gaps Through Partnerships
Transitioning to AI-powered predictive maintenance does not come without its challenges. Most of the mining companies we work with experience significant skills gaps that would undermine their capacity to do this effectively. To combat this concern, Kouroussis suggests collaborating with vendors that can provide technical support as well as training.
These collaborations help ensure that the transition is done right. Most importantly, they make sure that mining personnel develop the knowledge and skills to use AI-assisted tools properly and make better decisions through them. By investing in training programs and ongoing support, organizations can empower their teams to fully capitalize on the benefits of predictive maintenance.
Ultimately, going beyond technical capabilities and making the collaborative process create a culture of innovation within the organization is key. As workers get better at making use of AI technologies, they’ll help produce a safer, more reliable operation with better long-term performance.