AI Isn’t Magic – The Role of Domain Expertise in Predictive Maintenance

From our position at the forefront of predictive maintenance in the offshore drilling sector, we’ve seen the excitement around AI and machine learning continue to grow. When implemented effectively, these technologies offer a powerful way of reducing unplanned downtime, extending equipment life, and improving operational efficiency.

However the reality is AI is not a silver bullet, and predictive maintenance doesn’t succeed on algorithms alone.  In ADC’s experience, equipment domain expertise and a deep understanding of real-world operations is just as critical as data science when implementing practical and scalable predictive maintenance.

Where Theory Meets Practice

There’s a common misconception that if you feed enough sensor data into a machine learning model, it will “figure out” when things will fail.  The reality is a completely different picture.

We’ve worked with sensor data that spans years of operations. And we’ve seen how failure patterns can be rare, noisy, or completely masked by how equipment is used and the operational context in which it is used. Without a deep understanding of the underlying equipment and its limits, operating conditions, and known failure modes it’s easy to build a model that looks statistically impressive but performs poorly in the field.

Domain Knowledge in Action

This is where real-world equipment and operational experience is essential.

At ADC, we combine domain expertise with data science to:

• Pre-filter data based on realistic equipment behaviour
• Distinguish meaningful anomalies from normal variation
• Train models to recognise real equipment degradation, not irrelevant noise.
• Ensure predictions align with real-world equipment condition.

Models are just the starting point. We work with domain experts and the end user to ensure outputs are accurate, meaningful, and operationally useful.

Predictive Maintenance Requires Cross-Disciplinary Collaboration

Effective predictive maintenance doesn’t come from algorithms alone. It happens when technical expertise, operational content, data-science and the end user come together, not in isolation.

Involving experts in the loop enhances results – delivering faster, more reliable insights that can be trusted to perform reliability in real-world conditions.

How ADC Can Help?

At ADC, we develop predictive maintenance solutions that combine equipment, operations and engineering insight with advanced data science. No matter where you are on your predictive maintenance journey, we help turn raw data into operational value.

If you’re navigating the world of predictive maintenance and want to make sure you’re not relying on “black box” solutions, we’d be happy to share our perspective.