6 Best Predictive Maintenance Tools to Monitor Asset Condition

Predictive maintenance is a data-driven maintenance strategy that uses hardware and software tools to monitor the condition of a physical asset. In turn, that condition-monitoring data is used for predictive analytics and machine learning algorithms to determine when a piece of equipment might fail. While we know that unplanned downtime costs industrial manufacturers about $50 billion annually, predictive maintenance could be the ticket to lowering downtime costs and maximizing asset performance throughout its lifespan.

There’s just one caveat: Unlike preventive maintenance or other commonly used proactive maintenance strategies, predictive maintenance requires upfront investments in hardware. The specific IoT (Internet of Things) devices you need depend on the assets you want to monitor.

In this guide, we share the best predictive maintenance tools to use and how they fit into an effective predictive maintenance program that maintenance teams can implement. Since these six condition-monitoring tools track various aspects of an asset’s real-time data, a single asset may require multiple tools based on the parts or data you want to monitor. Here’s the rundown of all six:

Infrared Analysis Sensors

Infrared analysis sensors predict equipment failure through thermal imaging. They measure infrared radiation (heat) emitting from a machine and notify you when they detect abnormal temperature variations in components, which indicate wear, misalignment or impending failure.

Electrical panels, bearings, motors and mechanical systems typically generate excess heat when components start to degrade or there’s an increase in friction. Infrared analysis helps spot these temperature anomalies and prevent potential issues before they escalate.

Infrared IoT sensors are used in many industries. In data centers, they’re used to monitor HVAC systems and ensure consistent cooling of servers and IT infrastructure. Automotive manufacturers use them to monitor heat in paint drying ovens to ensure high-quality finishes.

Handheld infrared sensors are less expensive, with a starting cost of about $1,000 and up to $20,000 or more. Fixed systems are more costly, starting at about $10,000 and going up to hundreds of thousands. There’s also the cost of optimal placement, mounting brackets, wiring and calibration of a fixed system at the time of installation.

Motor Circuit Analyzers

Motor circuit analyzers (MCAs) are used to evaluate the health of motors and other rotating equipment. They measure various electrical parameters, such as resistance, capacitance and inductance, without disassembling motors or removing them from service. MCAs detect issues like insulation degradation, rotor bar issues, stator winding problems and imbalances — all of which can lead to motor failure if not fixed in time.

In high-demand manufacturing environments, MCAs are used to monitor motors in conveyor systems, robotics and other automated machinery. They’re also used in power plants to monitor the condition of large, expensive motors that drive turbines and generators. Early detection is critical here because these large motors operate under extreme conditions, and failure can lead to significant downtime.

MCAs are portable devices that cost about $5,000 to $20,000 or more, depending on their sophistication. While there’s no major set-up cost, you do need skilled technicians familiar with motor electrical systems and common failure modes to interpret data collected by MCAs.

Vibration Analysis Sensors

Vibration sensors are one of the most commonly used tools for predictive maintenance tasks. They monitor rotating equipment, including motors, pumps, fans and turbines, and measure their vibration patterns to detect imbalances, misalignment, bearing failures and other mechanical issues.

Vibration sensors can be of various types:

• Accelerometers: Accelerometers are the most widely used vibration sensors because they measure acceleration, which can be used to calculate both velocity and displacement. They’re ideal for monitoring high-speed rotating machines like motors and turbines.
• Velocity sensors: Velocity sensors measure the velocity of vibrating objects and are used to monitor low- to medium-frequency vibrations.
• Displacement sensors: Displacement sensors are also called proximity probes and eddy-current sensors. They measure an object’s physical displacement and are used in high-precision environments such as movements of shafts in turbines, bearings and large rotating machinery.

While the vibration sensors listed above are the most common, here are some other types for specific use cases:

• Micro-Electro-Mechanical (MEMS) sensors: MEMS sensors are miniature accelerometers built with semiconductor technologies. They’re smaller, require less power and are easy to integrate into wireless systems.
• Piezoelectric sensors: These use piezoelectric materials to generate electric charge in response to vibrations and measure acceleration, velocity or displacement depending on the sensor’s design, mechanical tuning and signal conditioning electronics.
• Strain gauge sensors: Strain gauge sensors measure changes in resistance due to strain (or deformation) of a material. It’s typically used to monitor the structural health of large mechanical structures like bridges.
• Laser Doppler Vibrometers (LDVs): LDVs measure the velocity and displacement of a vibrating surface without direct contact. They use the Doppler effect of laser light to capture the most subtle vibrations. They’re typically used in sensitive environments where physical contact with the object isn’t possible.
• Capacitive vibration sensors: Capacitive vibration sensors are generally used in highly sensitive applications like small electronics. They measure changes in capacitance between two conductive surfaces as vibration moves them relative to one another.

Ultrasonic Analysis Microphone

Ultrasound microphones detect high-frequency sounds generated by machinery and equipment. These sounds are typically outside the human hearing range. Issues like lubrication breakdown, cavitation in pumps, bearing wear and electrical discharge (such as corona or arcing in electrical systems) cause waves. The microphone converts these ultrasonic signals into audible sounds or digital data to monitor for early signs of mechanical failure such as friction, leaks or electrical discharge.

Ultrasonic microphones can be used to monitor bearings and gearboxes for bearing wear and lubrication failure, pumps and valves for cavitation as well as sounds of leaking air, gas or steam in air and gas systems. The cost of ultrasonic devices varies based on the use case. For example, handheld ultrasonic devices may cost between $1,000 and $15,000, while ultrasonic leak detectors range from $2,000 to $10,000.

Laser-Shaft Alignment Tool

Shaft misalignment leads to increased wear, vibration, energy consumption and eventual asset breakdown. Laser-shaft alignment tools can prevent this by providing real-time feedback on the degree of misalignment and helping technicians make the necessary adjustments.

A laser-shaft alignment tool uses a combination of laser beams and sensors to measure the alignment between two rotating shafts. They’re used across various industries for applications such as:

• Motor and pump alignment: Used in industries like chemical and pharmaceuticals in which maintaining perfect alignment is critical to avoid vibration, bearing failure and premature seal wear.
• Turbine alignment: Used in power plants where turbines and generators need to be aligned with extreme precision to avoid excessive vibration, which can lead to catastrophic failure.
• HVAC systems alignment: Used in commercial building maintenance (think hospitals or offices) where HVAC systems rely on fans, compressors and pumps for temperature control.

Laser-shaft alignment systems are typically portable and user-friendly. Cost may range between $3,000 and over $50,000 depending on the size of the equipment you want to use it for and the level of precision required.

Oil Analysis

Oil analysis involves examining the lubricant condition and the presence of contaminants or wear particles to gain insights into a machine’s health. Oil samples taken from machinery, such as engines, gearboxes, compressors and hydraulic systems, are tested in a laboratory.

The test typically looks at three things:

• Wear debris: Looks for metal particles that indicate breakdown of components like bearings, gears and other moving parts.
• Contaminants: Checks for external contaminants, such as dirt, water or coolant, that can lead to faster wear and failure.
• Oil condition: Assesses the oil’s chemical properties, such as viscosity, acidity, oxidation and additive depletion, to determine if the oil is fit for use or needs replacement.

Sampling posts are installed at points on equipment where oil can be drawn while the machinery keeps running. Automated sampling systems can be installed and monitored using predictive maintenance software in industries like power generation where frequent or continuous oil analysis is required.

The cost of sampling ports is negligible — about $100 to $500. Automated systems can be significantly more expensive, though, ranging from $10,000 to $50,000 depending on the size and complexity of the system.

How a CMMS Helps With Predictive Maintenance

Predictive maintenance technologies can pull data from the factory floor, but you need software to consolidate and track that sensor data in order to come up with an effective predictive maintenance strategy. That’s why you need a computerized maintenance management system (CMMS) that:

• Automatically records data sent from sensors.
• Helps users create an effective maintenance schedule and establish accountability by tracking who was assigned which maintenance task and when.
• Offers easy access to asset and equipment maintenance logs to simplify troubleshooting and build audit trails.
• Allows users to attach procedure docs, images and videos that highlight individual asset maintenance activities, operating conditions and other key information that’s critical to properly completing a work order.

Coast combines all these key factors that make up a good predictive maintenance solution — with the addition of extensive customizability. You can add, rename, reorder and remove fields within your asset management system and view personalized dashboards to get insight on what’s happening with individual assets, using table, calendar, list and board views. Coast centralizes all your asset data into a single, mobile-friendly platform, providing your team with real-time predictive insights needed to make data-driven decisions that increase equipment uptime and decrease maintenance costs.

Not sure if Coast is right for you? Book a demo today to learn more.