The majority of predictive maintenance solutions cost organizations millions of dollars to answer a single question: When will a part fail? 

While knowing when equipment will fail can solve a lot of headaches, there are more benefits—and savings—in knowing what you need to do to keep a piece of machinery from failing in the first place. It leads to increased uptime, lower costs, and improves the overall productivity of your entire operation. According to McKinsey, it’s critical for organizations to shift to “a proactive, comprehensive and well-thought-out approach to their digital maintenance and reliability strategy.” However, most people consider “proactive maintenance” to be predictive maintenance—the practice of calculating when a part will fail, then scheduling it to be worked on before that point. But that isn’t the whole story. For a part to be properly maintained, you need the equipment and people to do the work. 

Calculating failure isn’t enough; you have to be able to strategically manage every resource and opportunity. This is where the Virtualitics solution called Integrated Resource Optimization comes in. 

What is Integrated Resource Optimization?

Integrated Resource Optimization (IRO) is a data-driven approach that provides a big-picture view of maintenance operations. It goes beyond predictive maintenance so you can spend more time and resources on truly strategic preventative actions, rather than reactively fixing broken systems. IRO empowers maintainers and leaders to be more strategic in managing and executing the work that keeps their business running smoothly. 

How Intelligent Exploration powers Integrated Resource Optimization

Maintenance operations produce and collect a lot of information: parts inventory lists, staffing plans, procedures, repair times, repair logs, shift planning, and so much more. With such vast amounts of data, it’s challenging for data science teams and analysts to find insights that will maximize the lifespan of equipment and then, find them in time to make a difference. 

Intelligent Exploration is what makes IRO possible. By using AI to guide teams through their data, the Virtualitics AI platform helps users accomplish the kind of exploration that yields real results:

• Analyze historical data and current data across multiple sources, aggregate data from disparate sources, highlight the most relevant insight, and create powerful 3D visualizations.
• Empower analysts with embedded AI-guided exploration, providing recommendations that are backed by clear explanations for the reasons behind them.
• Steer leaders towards targeted actions that enhance equipment reliability and maintenance practices, while building trust in your analysts’ data capabilities. 

Integrated Resource Optimization at work

Let’s look at how Virtualitics enables leaders and maintainers to manage and maximize the average lifespan of wind turbines. 

Dashboards that actually make sense

The leader dashboard fuses wind turbine data from different sources, like maintenance activity, sensor data, inventory personnel, and supply chain data, to provide situational awareness at the enterprise level. From this dashboard, leaders monitor their KPIs and full risk and production profile over a 12-month period. 

Traditionally, aggregating all this information would take analysts’ hours of manual data cleaning, validation, and merging in spreadsheets. With the Virtualitics AI Platform, the process takes seconds and the platform analyzes an unlimited number of attributes at once using no-code AI routines. 

Prioritize the right risks and outliers

Knowing where to prioritize resources can be incredibly difficult, especially when your operations are spread out across many different locations. Virtualitics’s exploratory environment enables analysts to do deep analysis on complex, interrelated data sets, while also automatically surfacing the most significant insight within every analysis.

In the case of the wind farm, the system identified that a wind turbine has an average failure risk of only 38%, but the risk of gearbox failure is 95% and will break in about 10 days. It might seem counterintuitive to focus on a wind turbine with low average risk, but this is an important AI-generated insight. By fixing this one component, we can take proactive measures to ensure the overall production of this wind turbine remains high over the course of its lifespan.

Bring everything into focus

Being able to review data using 3D visualizations brings more clarity to assessments and better explains issues and solutions to stakeholders. Virtualitics takes analysts inside the affected wind turbine so they can examine its multidimensional components and investigate what’s causing the seemingly healthy gearbox to fail. 

Now that Intelligent Exploration has helped pinpoint an opportunity to reduce risk, analysts can alert leaders to the issue and help them build the correct repair and maintenance strategy on the turbine. This would include exploring data around maintenance activities, such as mean time to repair, as well as the resources available so that any purchasing could be worked proactively. 

The end result of this data exploration is an awareness of the remaining useful life of a part, knowing what is needed to maintain it, and how teams can manage those repairs with minimal disruptions to operations. By strategically managing every resource, not just predicting failure, teams increase their availability rates and minimize the risk to their operations. Those actions protect revenue and customer experience, building a profitable and trusted business.  

To see more of the Integrated Resource Optimization and Intelligent Exploration process in action, check out the video below or request a demo with our team.