Predictive Maintenance

Reduce unplanned downtime. Improve the safety and reliability of your assets.

Detect faults early

Identify abnormal asset behaviour early with temperature, pressure, vibration, acoustic, and other readings. Time to failure forecasting lets you plan maintenance before any damage occurs.

Assist maintenance staff

Every alarm comes with failure modes, data playback, and recommended actions. Maintenance staff can tell sensor faults apart from asset faults and make informed decisions.

Lower maintenance cost

Over-maintenance is just as costly as under-maintenance. You can find the cost optimum between regular and preventive maintenance using in-built case management and CMMS integration.

Why do companies choose INEA?

We focus on the user

Humans must design the inputs and outputs of an AI system. Our decades of experience let us talk with your staff as advisors, and listen to what matters to them. We use the input from experienced maintenance technicians to train the system that will help them decide easier and shorten the learning curve of less experienced staff.

Pilot, then scale

Making any overnight changes to an entire enterprise can be devastating. This is why we prefer a staggered approach, where we train and deploy predictive analytics on a smaller line or subsystem first. Once you experience the benefits yourself, we can scale across your business while prioritising the costlier, intensive processes that will return your investment faster.

Lifecycle support

Acting as integrators, advisors, and seasoned engineers, we support you through the development cycle and beyond. We take care of licensing, additional data connections, retraining, and system upgrades. Our phone line goes directly to project-relevant engineers that can be available to you up to 24/7 with no call centre bots in your way.

AVEVA Predictive Analytics

We partner with AVEVA to integrate AVEVA Predictive Analytics, a platform with worldwide support and installations in asset-intensive industries, such as chemical and petrochemical, steel, construction, and power generation. Its templated, no-code dashboards make it easy for users to customise and scale the system – or have a developer add a fully custom model. After installation, you can spend your time maintaining the assets that run your business.

With us as AVEVA Endorsed System Integrators by your side, you can take full advantage of native , MES, SCADA, and CONNECT digital reliability center. Custom integrations also support existing non-AVEVA platforms. Predictive analytics becomes a valuable tool learning on your own data and feeding your other systems, not just another tool to maintain.

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The Predictive Maintenance Development Cycle

The predictive maintenance development cycle

The prediction that lies underneath is fundamentally AI, which means that plug-and-play solutions rarely work. Development involves training specific models on your own data, which means that documenting and organising inputs is an important and extensive step. Even patented industry-leading models need co-monitoring and retraining, through which experts on both sides can adjust their behaviour and spot potential misalignments.

After that come dashboards, events, and workflows. They can be developed into a single diagnostic centre or a dispersed user-based set of screens depending on your needs. Since the system informs, but does not act on its own, responsible staff need to be assigned and trained on the use of the system. The interfaces are still user-adjustable without programming knowledge.

Key Technologies

Dedicated models

Just like no human is a jack of all trades, neither are AI models. Alongside AVEVA Predictive Analytics’ wide array of pre-adjusted models, we can develop custom models and train them on data from your exact process for maximum fit. Transient models let us better monitor startups and shutdowns, while can be adapted to batches and product types.

Situational awareness

Not every anomaly is a cause for alarm, and not every alarm requires action. This is why we work closely with your key personnel to select conditions that maintenance staff should actually see and respond to, and which endpoints the alarm needs to reach to be effective. Supports ERP, CMMS, or custom API integrations with any existing systems.

Explainable AI

In order to trust the system, it needs to reliably tell you why any alarm was raised. You are able to drill-down into the components of each model right from the diagnostics screen and see which signals are contributing to the deviation. Custom instructions in specific contexts inform you of the possible causes and effects of each anomaly.

Fully local installation

To protect from data leaks, external threats, and comply with cybersecurity as well as AI guidance (AIA, NIST2, ALTAI), the predictive maintenance system can run fully locally once the models are trained. The lean hardware requirements mean that the system functions in day-to-day operations on your existing enterprise IT infrastructure without specialised GPUs.

Get in touch

Tell us about the challenges in your production environment and learn what’s possible. We will get back to you within 24 hours to set up a 30-minute discovery call.

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