Your challenges > Ensuring predictive maintenance

AI for predictive maintenance

Reduce maintenance costs and unplanned downtime, while improving the lifespan of your key assets.

When it comes to maintaining equipment, machinery and other assets, decision-makers face trade-offs. A reactive maintenance strategy tackling unplanned disruptions can derail production and key operations. On the other hand, replacing equipment prematurely can result in unrealized value and unnecessary costs.

Preventive, condition-based,
or predictive maintenance?

Improve the lifespan of your assets, while reducing downtime, maintenance costs and inventory carrying costs.

With predictive maintenance, you can further leverage this approach to optimize your maintenance operations, spare-parts inventory and technician schedules. Having a greater understanding of the remaining useful life of an asset can help you make important trade-off decisions between delaying maintenance and meeting production objectives.

A predictive maintenance strategy can reduce capital expenditures by extending asset lifetime, while increasing overall productivity. For example, it can increase equipment reliability and availability by proactively addressing operational wear and tear, while reducing unplanned and unnecessary maintenance.

Predictive maintenance solutions are beneficial for a wide range of equipment, from ‘simple’ assets like HVAC systems (heating, ventilation and air conditioning), to highly complex assets like aircrafts. Thanks to advancements in AI, big data analysis and advanced signal processing, predictive maintenance can provide benefits to a wide range of industries, including manufacturing, automotive, retail, hospitality and service, among others.

6 key advantages of AI for maintenance processes

Reduce downtime by 20-50%

Cost effective

Minimize unplanned downtime costs, improve production or service delivery schedules and increase customer satisfaction by proactively detecting and addressing potential failures.

Decrease maintenance costs by 10-30%

Cost effective

Eliminate unnecessary parts replacement and optimize labour and equipment utilization by strategically focusing resources on critical components. Performing maintenance tasks proactively rather than reactively—and only when necessary—minimizes emergency interventions and reduces the need to deploy field engineers on urgent assignments.

Improve asset lifespan

Preventive

Identify and address issues before they escalate into major failures.

Optimize spare parts inventory

Cost effective

Reduce inventory carrying costs and minimize stockouts by ordering and stocking spare parts based on the actual equipment condition, failure probabilities and prioritization under supply chain constraints. Advanced predictive maintenance strategies can determine which equipment should be serviced first, ensuring optimal use of limited resources and available parts.

Enhance worker safety

Safety

Mitigate safety hazards, protect employees and minimize costs associated with workplace accidents by reducing the risks of dangerous equipment failures.

Reduce your environmental impact

Eco-conscious

Reduce emissions by ensuring that equipment is running optimally.

IVADO Labs' expertise in predictive maintenance solutions

1. Enable condition monitoring

In partnership with AI practitioners and data scientists, IVADO Labs has developed robust methodologies for analyzing and flagging sensor signal anomalies in near-real time using a spectrum of techniques, from codifying rules leveraging expert technician knowledge to using deep neural networks within a single framework. This activates automated condition-based maintenance within your existing software stacks.

2. Diagnose anomalies

To further push the boundaries, we have developed diagnostic modules that can leverage technical documents, technician knowledge and statistical methods to automatically detect the most probable root cause(s) of degradation, fault or failure.

3. Establish a prognostic

Our prognostics modules leverage predictive analytics as well as standard reliability methods to predict the future state and timing of potential faults of assets using both historical maintenance data and operational degradation to determine the remaining useful life of the component and system.

Process enhancements with AI

Flag issues and generate insights

Predictive maintenance tools can assist you in flagging equipment issues that require attention and generate insights to ensure your assets are functioning correctly. Machine learning algorithms can also provide you with a better understanding of upcoming work, allowing you to procure and kit the required components in a timely fashion. This helps to avoid urgent procurement requests, which can stress an already fragile supply chain.

Prioritize upcoming work orders

By understanding the criticality of maintenance work, you can better prioritize work orders, which is a challenge in most industries. Increased visibility of upcoming work orders allows you to better address any backlogs by scheduling a larger proportion of maintenance jobs. And, over time, a reduction in unplanned maintenance means you don’t need to leave your calendar open to accommodate unplanned downtime.

Easily detect anomalies

Struggling to find a solution that meets your needs?

At IVADO Labs, we’ve designed each module of our predictive maintenance software to operate independently, allowing for targeted improvements without impacting the rest of the system. This flexible, adaptable and dynamic system is designed to grow with your business, giving you a strategic advantage in price optimization—and helping you stay ahead of the market.

Discover the concrete impact of our solutions

We create AI solutions that blend advanced predictive, prescriptive and generative capabilities.

Discover our expertise

Our promise: proven cutting-edge artificial intelligence solutions to solve your most complex problems.

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