The Benefits of Predictive Maintenance

There are real operational, financial and quality benefits to implementing condition-based monitoring and predictive maintenance. The effects of these benefits are not limited to the maintenance department of an organization, but can create a positive organization-wide impact.

How to Reap the Advantages of Predictive Maintenance

Predictive maintenance is the data-driven approach to achieving machine reliability. In the highly connected, Industry 4.0 age, the ability for organizations to overcome any deficiencies in data depends heavily on the technology that they use and the capabilities of that technology. Predictive maintenance benefits are only possible with a well-executed and cohesive program that contains certain elements:

  • Technology that captures sensor data. Condition-based monitoring technologies are used in critical areas of machines to assess condition and performance.®’s Camera-as-a-Sensor™ platform is an example one such technology gathering data for predictive maintenance by enabling monitoring and inspection in difficult to access areas of machines.
  • Technology that distributes data. Using technology and devices that are IoT-enabled facilitates the distribution of data to the cloud or an onsite data center where the data can be analyzed. Wireless capability of the sensor devices is extremely important here as remote monitoring has become a near necessity in many maintenance scenarios.
  • The use of data analytics to make predictions. Both historical and real-time machine data are fed into AI and machine learning algorithms to predict when a machine will fail and what maintenance remedies will be needed.

Predictive Maintenance Increases Uptime of Machines and Processes

Increasing uptime of machines and processes is one of the top goals for many organizations that deploy condition-based monitoring and predictive maintenance. Being able to forecast machine failures using advanced data analytics can improve machine uptime by as much as 20 percent.

With condition-based monitoring and predictive maintenance, machines and systems remain in operation until maintenance is actually justified, limiting downtime to what is necessary for maintenance or repair. This is a stark difference from other maintenance approaches, such as preventive maintenance, that actually increase downtime by implementing either insufficient or excessive maintenance.

Predictive Maintenance Improves Machine Reliability

On average, organizations will lower their machine failure rates by 70 percent using a predictive maintenance program. Conducting condition-based monitoring using technologies that are able to gather and distribute sensor data enables maintenance teams to obtain real-time data on the health of a machine. This provides enough forewarning to apply the appropriate maintenance tasks that will prevent failure.

Using’s visualization sensor technology as an example, maintenance teams in the aviation or mobility industry that have to oversee rotating equipment can use the technology to conduct real-time monitoring of bearing malfunctions and deformations while the machine is in operation.

With providing automated real-time data visualization, they can detect minuscule deformations that will eventually leave the bearings vulnerable to surface fatigue. AI algorithms can then forecast the time of failure. This not only helps ensure that the bearings are replaced when necessary, it also prevents the collateral damage to nearby components, machines or systems that would occur should the bearings fail.

Predictive Maintenance Reduces Overall Maintenance Costs

Predictive maintenance cuts maintenance costs by 5 to 10 percent. This is savings on costs related to inventory management, the personnel needed to install replacement components and more. Under conventional maintenance programs, in cases of emergencies and unexpected machine breakdown, these costs can multiply.

With the foresight predictive maintenance provides into the health of a machine, organizations mitigate machine breakdowns and schedule downtimes for maintenance and repair at times that will have the least financial impact on the organization. Using predictive maintenance in lieu of other maintenance approaches that rely on rigid maintenance scheduling also means that costs are saved on servicing and replacing machine components that are still in good working order.

Predictive Maintenance Extends Machine Lifetime

As physical assets, machines are vulnerable to deterioration. However, the data analytics that are used in predictive maintenance provide maintenance teams with the insights that help machines to provide optimal performance as long as possible. The analysis of machine data will highlight the situations in which components fail or breakdown frequently. Maintenance teams can use this information to minimize breakdowns.

Predictive Maintenance Improves Worker Safety

Predictive maintenance enhances worker safety without sacrificing productivity and while minimizing planned and unexpected downtime. This is made possible by not only the more strategic planning that maintenance teams are able to do, but also by the technologies that are being used in predictive maintenance programs.

Let’s return to the use of’s visualization sensor technology, which can endure extreme environments and has wireless capability, features that allow maintenance teams to conduct monitoring and visual inspection remotely.

It is the smart approach to data collection by placing sensors on or near the moving parts of machines, allowing workers to assess the condition of a component or machine without having to touch the machine, eliminating potential hazards of being exposed to extreme environmental conditions, rotating equipment, accidents while climbing ladders, etc. enable maintenance teams to conduct remote monitoring.

In the railway industry,, among others, is used for the inspection and monitoring of train brake pads. It is important to be able to monitor the conditions of train brake pads while the train is in motion, a task that would be extremely hazardous for maintenance teams to conduct in person.’s platform helps alleviate the risks to workers by providing informative visual data in extremely dangerous conditions and AI-generated notifications of real-time brake pad wear. Helps Organizations Obtain Predictive Maintenance Benefits

Predictive maintenance can improve efficiency and productivity—if organizations are using the right technologies to implement it.’s visualization-based AI platform is created for automated real-time data visualization, analysis, reporting and prediction for difficult to access areas.

Contact us for a demonstration on how our technology can help your organization reduce machine downtime and benefit your entire organization.

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