Predictive Maintenance for Mining Equipment: A Game-Changer by HiQ

Client: A leading global manufacturer of mining and construction machinery
Industry: Mining & Heavy Machinery
Solution Area: Predictive AI-powered Maintenance Systems

The Challenge: Downtime at a Heavy Cost

Operating in some of the world’s toughest environments, the customer’s machinery—including stone crushers—runs outdoors 24/7, all year round. However, unplanned downtime poses a major challenge. When machinery breaks down, it costs operators between SEK 5-10 million per day and can lead to operational shutdowns lasting up to a week.

Faced with these high stakes, the customer sought an innovative solution to minimize disruptions, prevent breakdowns, and maximize efficiency. The challenge was to build a system that could predict potential failures, provide timely alerts, and align seamlessly with operators’ workflows in complex mining environments.

The Solution: Leveraging Predictive AI for Proactive Maintenance

HiQ partnered with the client to develop a cutting-edge predictive maintenance system using advanced AI models. This system analyzes real-time sensor data from stone crushers to detect anomalies and alert operators to potential issues before they occur.

Key Features:

• Proactive Alerts: The AI system identifies abnormal patterns in machine operations and provides timely warnings, enabling operators to address issues before they escalate into costly breakdowns.
• User-Centric Design: HiQ’s service designers worked closely with operators, shadowing them in a mining site in Chile. This approach ensured the system’s interface and workflows aligned with real-world operator needs and control device interactions.
• Seamless Integration: The solution bridges the gap between physical control devices and business processes, ensuring smooth adoption and high functionality across multiple sites.

HiQ’s agile team brought together expertise in predictive AI models, connected products, data management, and UX design to deliver a solution that meets the demands of high-pressure mining operations.

Results: Transforming Maintenance into a Competitive Advantage

The deployment of the predictive maintenance system has delivered significant results:

• Reduced Breakdowns: Operators reported a noticeable decrease in machinery failures, directly lowering downtime costs.
• Improved Workflow Integration: The system’s intuitive design and close alignment with operators’ processes drove rapid adoption and effective usage.
• Scalable Rollout: Following its success, the solution was implemented in additional mining sites, further enhancing operational efficiency and minimizing disruptions.

The project not only delivered measurable cost savings but also positioned the customer as a pioneer in leveraging AI to optimize industrial operations.

HiQ’s Role: User-Focused Innovation

HiQ’s collaborative and agile approach ensured that the end-user was at the heart of the solution. From shadowing operators in the field to developing predictive models tailored to their needs, HiQ delivered a solution that was:

Scalable and Sustainable: Designed to scale across multiple sites while maintaining ease of use.

Human-Centered: Designed with the user experience in mind to ensure seamless integration with existing workflows.

Technically Robust: Built on advanced AI capabilities for accurate and reliable predictions.

HiQ’s Edge: Driving AI Adoption with Real-World Impact

What sets HiQ apart is its ability to bridge cutting-edge AI technology with practical, user-centric applications. By combining technical expertise with deep insights into user behavior, HiQ ensures its solutions are impactful, scalable, and seamlessly integrated into daily operations.

Through this project, HiQ reinforced its reputation as a trusted partner in harnessing the transformational potential of AI to solve some of the most challenging problems in industrial operations.