S m a l l S p a r k . U K

Predictive Maintenance

  • Proactive alerts enable maintenance before failures occur.

  • Early trend analysis supports smarter, scheduled repairs.

  • Continuous monitoring predicts wear and degradation over time.

  • Secure, offline insights empower pre-emptive asset management.

Predictive Maintenance: Maximising Uptime, Minimising Costs

Predictive Maintenance: Maximising Uptime, Minimising Costs

Unplanned equipment failures can be catastrophic—leading to downtime, high repair costs, and lost productivity. Predictive maintenance transforms asset management by identifying failures before they happen, enabling proactive repairs and optimising equipment performance.

Traditional predictive maintenance often relies on cloud-based analytics, requiring continuous data uploads that introduce latency, high costs, and security concerns. By shifting maintenance insights to the edge, SmallSpark enables real-time, ultra-low-power monitoring—delivering instant fault detection, reduced operational expenses, and improved asset longevity.

Why Local Processing for Predictive Maintenance?

🔹 Instant Failure Detection & Response – >90% lower latency enables immediate action before small issues escalate into critical failures.

🔹 No Dependence on Internet Connectivity – Equipment monitoring works offline, ensuring predictive insights even in remote or mission-critical environments.

🔹 75% Reduction in Operating Costs – Edge-based processing eliminates the need for continuous cloud data uploads, cutting data transfer and storage expenses.

🔹 Ultra-Low Power Consumption – SmallSpark’s energy-efficient solutions ensure continuous monitoring, even in battery-powered systems, without draining resources.

🔹 Enhanced Security & Privacy – On-device real-time encryption protects sensitive operational data from cyber threats and unauthorised access.

  • Real-World Applications

    ✅ Industrial & Manufacturing Equipment

    • Detecting early signs of motor degradation, overheating, and component wear, preventing costly breakdowns.
    • Automated scheduling of maintenance, reducing unnecessary servicing and increasing equipment lifespan.

    ✅ Aerospace & Transport Systems

    • Aircraft component monitoring, predicting engine and system failures before takeoff, ensuring maximum safety.
    • Rail and automotive maintenance, analysing vibrations, pressure, and temperature to prevent disruptions.

  • ✅ Energy & Infrastructure

    • Power grid failure prevention, identifying electrical faults before they cause blackouts or costly outages.
    • Pipeline and structural monitoring, spotting leaks, stress fractures, or pressure abnormalities in real time.

    ✅ Spacecraft & Remote Systems

    • Onboard anomaly detection in satellites and space missions, reducing reliance on delayed ground-based diagnostics.
    • Drone and UAV system monitoring, ensuring long-term reliability without manual inspections.

    By integrating predictive maintenance with ultra-low-power edge computing, SmallSpark reduces downtime, optimises operations, and cuts maintenance costs—delivering smarter, more resilient infrastructure across industries.

By integrating predictive maintenance with ultra-low-power edge computing, SmallSpark reduces downtime, optimises operations, and cuts maintenance costs—delivering smarter, more resilient infrastructure across industries.