Predictive maintenance and prescriptive analytics are gaining popularity as businesses realize the benefits of applying data and analytics to achieve intelligent asset maintenance.

What is Asset & Maintenance?

According to ISO 55000, an asset is defined as “A thing, item or entity that has actual or potential value.” Therefore the primary objective of asset maintenance is to ensure that assets maximize value to the business and stakeholders in the value chain through effective asset maintenance strategies.

The Need for Maintenance

Businesses are shifting from Run-to-Failure and preventive maintenance to smarter maintenance solutions to avoid huge losses associated with repair cost, labor cost and among all, opportunity loss for the business. As Run-to-Failure is a costly affair, the companies have started looking for alternatives as preventive maintenance has proven ineffective over time. With changing trends, companies realized that technicians are performing routine maintenance tasks when everything is still running smoothly, while this could always be a valid maintenance strategy, something better is needed.

Shift to Intelligent Maintenance

Ascension of the Internet of Things (IoT) is fundamentally changing the way that companies create value, compete and partner with other businesses. Companies are using IoT to boost operational performance and enhance customer experience by data fusion from sensors and asset management systems. The IoT data provides value-driven insights about asset conditions that enable the maintenance based on the asset condition instead of routine scheduled checks.

Intelligent maintenance refers to predicting the probability of failure in advance and alerting the business unit to start planning the preservation of assets well in advance, eliminating breakdown and ensuring increased asset availability.

Remaining Useful Life (RUL) is another intelligent maintenance technique that is useful for life left on an asset at a particular time of operation. Its estimation is central to condition-based monitoring and prognostics and health of asset and centered on statistical data-driven approaches which rely on available past observed data and machine learning models. RUL should enable the business to make an informed decision about whether to perform the maintenance or plan for replacement, which may deem it to be cost-effective.

Core Capabilities of Intelligent Maintenance Solution

An IoT enabled intelligent maintenance platform must facilitate communication, data flow, device management, core functionality around asset inspections enabled with advanced analytical capabilities to provide predictive maintenance. It should also employ better connectivity and data flow with low power IoT devices.

Core capabilities include:

01. Device & Asset Management

The platform should centrally manage the IoT devices from registration to firmware upgrade and support the edge shift to push the inferencing models on to the devices for the noise cancellations. The ability to map the device to the asset should be done seamlessly with intuitive user experience.

02. Inspection Management

The solution should be capable of creating asset inspections based on the collected data, analyze past performance and co-relate with current performance, to keep the assets safe and yield optimized performance. The inspection process management must adhere to the organization’s assignment and approval strategy and enable workflow management capabilities.

03. Mobility

The widespread adoption of smartphones and tablets is bringing rapid change in information management and pushing IT to meet its objectives to find patterns in data and aid in business decisions around data. Field technicians and other staff are using smart mobile devices to capture the vital data points, and asset images through mobile-specific high-resolution cameras and voice-to-text capabilities to get their work done smartly. Therefore the platform should have the ability to capture the inspection data on the go and should be powered with route guidance.

04. Analytics

The ability to collect & analyze data from IoT devices and other IT systems allows companies to move from preventive maintenance to predictive maintenance. The IT & business staff need to be able to gain insights through the right analytical capabilities from the intelligent maintenance platform to make smarter decisions and improve operational efficiency.

05. Value of Intelligent Maintenance

Over the past few years, businesses are increasingly becoming aware of how maintenance operations could be strategic to their business goals. With the benefits offered by cloud computing, automation, and IoT, it is increasingly affordable for asset-based companies to optimize their maintenance operation. Intelligent maintenance will play a key contributing role in pushing productivity and eliminating breakdowns.


Preventive maintenance is scheduled maintenance based on the manufacturer guidelines and experience gained while managing the asset.

Predictive maintenance is based on condition monitoring and health of assets.