In critical sectors like logistics, manufacturing, energy, and transportation, unexpected equipment failures and operational risks can lead to costly downtime, safety incidents, or supply chain disruptions.

Solving this challenge ensures greater safety, cost efficiency, and operational continuity.

The Challenge:

• Traditional models rely on reactive maintenance (fixing things after failure)

• Hard to detect non-obvious or non-linear risk patterns in large asset networks

• Preventive maintenance schedules often waste resources on assets that don’t need repair

• Lack of dynamic optimization across multiple machines, conditions, and risk factors

Quantum-Inspired Solution

This is where Quantum-Inspired Optimization becomes transformative. By analyzing complex interdependencies in data, it can forecast potential failures, uncover hidden risks, and help organizations take proactive action — before problems occur.

Early Detection of Risk & Failure Points

HessQ uses QUBO models to identify critical failure paths before they occur — even when signals are subtle.

Replaces fixed schedules with data-driven maintenance plans that reduce downtime and costs.

Detects hidden patterns of risk across connected systems — predicting chain reactions or correlated failures.

Optimized Maintenance Scheduling

System-Wide Risk Correlation Mapping

The Results:

• 40% reduction in unplanned downtime

• 25–30% savings in maintenance costs

• Improved safety and reliability

• Continuous monitoring and adaptation in real time