Types of industrial maintenance and the role of IIoT

Industrial equipment varies in its level of criticality, which determines its importance to the production process. Typically, equipment is classified into three categories: Criticality Level A, B, and C.

The level of criticality dictates the degree of attention required from the maintenance team to prevent process interruptions.

• Criticality Level A refers to equipment essential for production continuity and product quality. A failure in this category almost inevitably results in production line shutdowns.
• Criticality Level B includes equipment whose malfunction may impact production efficiency but does not cause a complete halt. Temporary solutions can often be implemented to maintain operations until a scheduled downtime allows for proper repairs.
• Criticality Level C applies to equipment whose failure does not affect production. Repairs can be deferred, even if the device operates inaccurately or is non-functional.

The classification of criticality is significant because it influences the type of maintenance required. For example, planned corrective maintenance is generally associated with Level C equipment, as its failure does not immediately disrupt production. Conversely, Levels A and B often necessitate preventive or predictive maintenance strategies to avoid unscheduled downtime and ensure operational reliability.

Corrective maintenance is widespread daily occurrence in any industrial sector. This type of maintenance helps when a device fails during operation. Usually, there are two different types of corrective maintenance, the planned and the unplanned.

Unplanned corrective maintenance happens when a device with high-level criticality fails and you need to work on it as soon as you can to make the process run again. When it happens, you most probably have a shutdown and you are losing money for every minute the production is stopped. In some cases, you can also lose primary material and final products.

Planned corrective maintenance happens when a device or equipment with a low level of critically fails but has no effect on production. In this case it’s possible to plan its maintenance - but even this type of maintenance may not be the best solution.

When equipment fails, restoring functionality as quickly as possible is critical. IIoT solutions can significantly accelerate the corrective maintenance process by providing immediate access to essential information and tools.

For example, combining a smart handheld device, such as Field Xpert, with an IIoT service like Netilion Library enables rapid access to equipment documentation and device files. This integration supports efficient troubleshooting and device setup through an intuitive user interface.

Furthermore, transitioning to online condition monitoring with Netilion Health can help prevent similar failures in the future. By leveraging predictive insights, plants can reduce unplanned downtime and improve overall reliability.

Preventive maintenance refers to actions designed to reduce the likelihood of unplanned equipment failures by ensuring that devices remain in optimal working condition. This approach focuses on maintaining reliability and extending the operational lifespan of industrial assets.

Preventive maintenance can be scheduled based on different criteria:

• Time-based: Maintenance activities are performed at regular intervals, such as cleaning or replacing components every two months.
• Usage-based: Tasks are triggered by equipment utilization, for example, replacing oil after 2,000 movements.
• Production-based: Maintenance occurs after a defined output, such as cleaning and replacing parts after 5,000 products have been manufactured.

In industrial environments, preventive maintenance is widely implemented to minimize unplanned downtime and improve overall equipment efficiency.

IIoT solutions can play a key role in optimizing preventive maintenance activities. A comprehensive overview of the plant and its installed equipment is essential for planning which components require replacement or servicing.

Tools such as Field Xpert industrial tablets, combined with IIoT services, enable efficient access to device data and maintenance documentation. Netilion Analytics provides a clear visualization of the plant, supporting strategic planning for preventive maintenance tasks. Additionally, Netilion Health offers current and historical health data for connected devices, allowing maintenance teams to assess equipment condition and prioritize actions effectively.

Predictive maintenance is an advanced strategy that relies on continuous or frequent monitoring of equipment to assess its health and detect changes over time. By analyzing real-time and historical data, it becomes possible to anticipate potential failures and take corrective action before disruptions occur.

This approach often involves constant monitoring of big machinery using techniques such as spectrum Operating Deflection Shape (ODS) analysis. These methods enable early identification of anomalies that could lead to equipment failure.

In process automation, predictive maintenance depends on collecting and interpreting data from smart devices. Modern IIoT services provide efficient and intelligent tools for analyzing this information, allowing maintenance teams to make data-driven decisions that minimize downtime and optimize asset performance.

One of the primary challenges in implementing predictive maintenance is data acquisition. A significant portion of industrial devices still rely on analog 4–20 mA signals, which limits the ability to capture detailed diagnostic information.

However, recent technological advancements have introduced new possibilities for seamless data integration. Solutions such as WirelessHART and Bluetooth®-enabled devices provide efficient methods for transmitting data to field-edge systems and subsequently to cloud platforms. These innovations simplify access to critical device information, enabling advanced analytics and predictive insights

IIoT services are essential for implementing predictive maintenance effectively. Before initiating any maintenance actions, it is critical to validate the data and base all planning decisions on insights provided by IIoT platforms.

Modern IIoT ecosystems, such as Netilion, simplify the interpretation of complex data streams from field devices. These platforms present information in an accessible format, eliminating the need for specialized data analysis skills. This ease of use is one of the key advantages of IIoT services: they transform raw data into actionable insights, enabling maintenance teams to make informed decisions quickly and confidently.

IIoT supports corrective, preventive, and predictive maintenance by providing quasi real-time access to device data, documentation, and health insights. It enables faster troubleshooting during corrective maintenance, improves planning for preventive tasks through plant-wide visibility, and simplifies predictive maintenance with continuous monitoring and data interpretation. These capabilities reduce downtime, optimize asset performance, and enhance overall operational reliability.