Network Computing is part of the Informa Tech Division of Informa PLC

This site is operated by a business or businesses owned by Informa PLC and all copyright resides with them. Informa PLC's registered office is 5 Howick Place, London SW1P 1WG. Registered in England and Wales. Number 8860726.

Wireless IIoT Helps Enterprises Perform Predictive Maintenance, Avoid Downtime

Network Automation
(Source: Pixabay)

Utilities, chemical plants, and manufacturers are embracing the Industrial Internet of Things (IIoT) systems made up of sensors and other devices connected to wireless networks to avoid downtime and optimize the performance of their plants.

The combination lets IT managers perform Predictive Maintenance (PDM) to better monitor assets such as machines and avoid operational downtime, which across industries is pegged at $260,000 an hour, according to the Aberdeen Group.

What is PDM?

PDM is a type of maintenance that monitors the condition of assets using sensors. These devices supply data in real-time, typically to a software system, which is then used to predict when the asset will require maintenance to prevent equipment failure.

PDM is seen as a superior approach to preventative maintenance because since it uses crucial knowledge about the current state of a part, device, machine, or piece of equipment. It helps determine the condition of in-service equipment to estimate when maintenance should be performed.

PDM can deliver cost savings over routine or preventive maintenance because tasks are performed only when needed.

PDM Evolves

Industrial PDM has come a long way since its inception decades ago. Companies in this space have long used vibration monitoring to detect problems in machines and equipment. Trying to detect issues before downtime, maintenance staff used high-end stethoscopes to listen to the machines just as a doctor uses a medical version on your chest while asking you to cough.

There are pros and cons to the high-end stethoscope approach, which is widely used today. Maintenance teams use these devices to take occasional readings (sometimes for a few seconds once every few months). This method has been criticized as staff typically spend far more time searching for problems than they do solving them.

Another approach is to install wired systems, which is seen as an overly expensive and extremely complicated undertaking.

Enter wireless PDM

Seeking a better/cheaper/more effective way to better maintain crucial equipment and avoid costly downtime, industrial facilities are monitoring more of their equipment on a round-the-clock basis using wireless infrastructure.

Replacing occasional manual stethoscope checks with 24x7 wireless monitoring has become a game-changer for many plants and mills. Enterprises report advancements in wireless monitoring have made observing machine behavior and eliminating downtime easier than ever.

Sensing trouble

A widening array of sensors is great news for plant and maintenance managers as they can go far beyond measuring equipment vibrations to measuring temperature, pressure, and other key operational metrics. Better still, a wireless PDM system collects critical data. Systems can generate a series of alerts that can be sent via text and email to managers at all hours.

One chemical plant implemented a wireless PDM system from KCF Technologies and was able to act on data collected, suggesting that a machine seal needed attention. It was fixed, and the plant avoided an expensive failure and extended downtime. The reliability manager was on vacation when he received the alert text and email. He contacted the facility, and action was taken quickly.

The company invested around $25,000 for a wireless system, which included 28 sensors installed on 14 assets. The sensors monitor vibrations and temperature. The chemical plant estimated that the discovery of the seal problem saved $80,000 in lost productivity. The investment paid for itself three times within the first month of the wireless sensor system's installation.

The wireless sensors enable plant managers to identify potential failures sooner. The alert texts reach those responsible parties regardless of location or time of the day and night.

Unlike their predecessors, wireless PDM systems support the most important function – real-time data analysis. By examining and interpreting data collected by the sensors, enterprises can act on why potential failures happen in addition to addressing the symptoms.

In the rotation

Utilities are another vertical that continue to invest in IIoT-enabled PDM. Arizona Public Services started with a pilot of a wirelessly monitored system from Petasense. It has since fully deployed the offering to cover all rotating assets at three of its eight power plants.

The utility asset reliability and optimization (ARO) system includes wireless sensors and predictive analytics software designed to help plants get real-time insights into the health of the equipment in the power plants.

The large electric utility uses the ARO system to monitor more than 1,000 rotating machines that deliver 2,500+ megawatts of power generation. Uptime is critical to utilities as the inability to generate power when needed means loss of revenue and fines from regulators.

The Petasense ARO system provides a machine learning-driven asset health score that it claims helped detect 14 critical failures in 2018, according to the supplier. APS might have missed catching them had the utility, like many other enterprises, still used the manual walk-around vibration analysis program that featured stethoscopes.

The bottom line

The ability to use an IIoT approach to perform PDM on plant assets enables companies to avoid or minimize costly downtime in their core operations while making far more efficient use of skilled staff than prior approaches.

The value is multiplied for enterprises with every-second counts, 24x7 operations such as energy generation and manufacturing. Moving from manual approaches to an IIoT-based system, while sidestepping wired networks, lets companies optimize their assets and better focus on meeting challenges along their supply chains.