Predictive Maintenance Equipment: Types, Analysis & Tools

In today's technology-driven world, industries across the spectrum face significant challenges to maintain the reliability and efficiency of their machinery and equipment. Downtime and unexpected failures can be costly, leading to production delays, increased maintenance costs, and reduced profits.

Using predictive maintenance equipment technologies, businesses can operate more strategically by forecasting the probability of equipment failure and when repairs will be needed.

Predictive equipment maintenance analytics and computerized maintenance management system (CMMS) software are becoming more prevalent among industry businesses to decrease the rate of unexpected equipment breakdowns and the associated expenditures.

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What Is Predictive Maintenance?

Predictive maintenance is essentially a proactive approach to managing maintenance. The primary advantages of predictive maintenance and its features are increased asset dependability and efficiency.

The primary goal of the predictive maintenance equipment approach is to determine the machinery's current state and predict the need for repairs. 

According to Statista, the global predictive maintenance market is expected to reach around 23.5 billion U.S. dollars by 2024. Between 2018 and 2024, the market is expected to grow at a compound annual growth rate of almost 40 percent.

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How Does Predictive Maintenance Equipment Work

Predictive maintenance solutions have the most moving components compared to other maintenance approaches.

Condition-monitoring devices are employed to assess the efficiency of assets through embedded sensors within the machinery to determine the asset's performance.

These sensors record information about the machinery, including variables like temperature and pressure. When equipment has condition-monitoring sensors, technicians can collect information about the machine's operational status without physically opening it.

Teams can prevent excessive downtime with this diagnostic automation.

Multiple sensors incorporated into the devices can gather and transmit real-time data to a centralized database using the Internet of Things (IoT), which operates through WLAN or LAN-based connection or cloud technologies.

Predictive algorithms look for patterns in the data to determine when an asset needs repair or replacement. They compare the asset's actual behavior with its predicted behavior and apply rules.

The data sharing allows the maintenance managers to see all physical assets together, which helps them understand the equipment's operations and spot problem areas.

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Types of Predictive Maintenance Equipment Tools

• Infrared Analysis Sensors: Detect anomalies in temperature to preempt potential failures.
• Oil Analysis Tool: Analyze oil samples to detect contaminants, wear particles, and degradation. 
• Motor Circuit Analyzers: Ensure electrical systems are running optimally to prevent breakdowns.
• Vibration Analysis Sensors: Identify abnormal vibrations indicating machinery issues.
• Ultrasonic Analysis Microphone: Pinpoint leaks, friction, and electrical problems through sound frequency analysis.
• Laser-shaft Alignment Tool: Maintain precision by aligning machinery shafts accurately, reducing wear and tear.

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Top 6 Construction Equipment Maintenance Tools

1. Infrared Analysis Sensors

A predictive maintenance scheme relies heavily on sensor data. Internet of Things (IoT) sensors can measure various machine parameters, such as pressure, temperature, noise, etc.

One use of infrared sensors is the time-series comparison of component temperature differences in a single or multiple viewpoints. Sensors detect current or impending problems with many kinds of assets, parts, and materials using infrared radiation (IR).

The sensor determines an object's temperature by analyzing its response to variations in the wavelength of radiation, which are undetectable to the naked eye. IR can assess its temperature differences if you have more than one view of a component.

Uses for infrared analysis are numerous and varied, including but not limited to:

• Measuring piping conditions
• Calculating process temperatures
• Estimating plumbing conditions
• Checking the condition of solar panels
• Evaluating the condition of electrical components (standard in ARC flash analysis)
• Checking the temperature variations of mechanical components (like motor cases)
• Verifying the insulation situation

Advantages

• Managers often purchase infrared thermography cameras and sensors when planning a PdM program. 
• Thermal imaging is an excellent tool for rapidly measuring and comparing invisible heat signatures to the human eye without disrupting operations or jeopardizing staff members.
• Employees can utilize it to find out-of-the-ordinary issues that other pieces of machinery have covered up. 

Disadvantages

• It does not work when tested on surfaces that reflect light.

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2. Oil Analysis Tool

Oil analysis determines the quality of oil samples and whether equipment malfunctions. This tool checks the oil for signs of wear, such as water and viscosity. Metal particles found in oil samples might be a sign of metal fatigue.

High-speed or mission-critical machinery often undergoes oil analyses. Predictive oil analysis is usually required to maintain equipment warranty requirements. The original oil analysis method was to gather oil samples on-site and send them to a distant facility.

Oil analysis helps in the following:

• Detecting early signs of machinery wear
• Detecting contamination and degradation
• Identifying potential issues before they escalate
• Optimizing maintenance schedules
• Minimizing downtime
• Extending the lifespan of equipment

Advantages

• Provides an accurate snapshot of the state of the lubricant
• Reduces oil usage by extending the time between oil changes
• Anyone, including those without formal training, can gather samples 

Disadvantages

• Potential equipment damage is due to the time lag between sample collection and analysis reporting.
• A dedicated area is necessary for portable or on-site equipment.
• Lab technicians doing on-site and portable analyses must undergo extensive training.

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3. Motor Circuit Analyzers

A motor circuit analyzer is one PdM tool that can help you understand the electrical health of an equipment's motor system. By analyzing the components of electric motors, motor circuit analyzers can identify problems and possible equipment breakdowns.

Motor circuit evaluation finds these issues using electronic signature analysis (ESA). ESA can detect motor problems by measuring their operating current and supply voltage. Various motor types, including AC and DC, are compatible with ESA.

Motor circuit analysis is used to locate issues with: 

• Incoming electricity and the mechanical parts of the motor
• Stator winding
• Bearings
• Rotors
• Coupling
• Attached load
• Efficiency
• System load

Advantages

• Inspect machinery's health while it's in operation through motor circuit analysis.
• Most motor circuit analyzer tools make it possible to do tests in around two minutes.
• It can only be used to test electrical components; it can test linked components but not the whole equipment chain.

Disadvantages

• Testing is limited to electrical components alone. (In this case, we examine individual parts rather than the whole equipment chain.)
• Complete analysis requires the input of nameplate data and operating parameters.

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4. Vibration Analysis Sensors

Sensors that measure vibration can pick up on signals from moving components and transmit that data to a database in case of an issue. 

When linked to an up-to-date CMMS, it's feasible to see changes across time by comparing present and past data.

Furthermore, CMMS machine learning sorts data into useful information.

Vibration analysis helps in the following:

• Finding the most telling signs of upcoming rotating equipment problems. 
• Vibrations that are too strong are a sign of equipment wear and tear, which, if left unchecked, can lead assets to fail.
• Vibration analysis is used to identify issues such as corrosion, resonance, rubbing, cavitation, mechanical looseness, gear flaws, and lack of lubrication. 
• Consequently, it is used in various equipment types across all sectors.

Advantages

Vibration analysis has several potential applications.

• It measures an item's displacement, vibration frequency, and velocity (the speed of the vibration) in real-time. 
• As soon as sensors collect data, action may be taken within a month. However, you need to know which tools to use to get the best outcomes.

Disadvantages

• Not adept at fixing electrical problems
• If you want perfect outcomes, you must know which instruments to use.

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5. Ultrasonic Analysis Microphone

Ultrasonic analysis (UA) can identify potential faults in equipment by using a sensitive microphone to take up high-frequency noises.

The CMMS software receives the sound waves and converts them into digital data and audio.

Like vibration analysis, construction equipment maintenance software for performance tracking compares current UA data with known records.

Portable UA sensors can gather data on the spot or save it for later study in a database.

Specific UA devices come with inbuilt thermometers, cameras, and spectrum analyzers for even more advanced data processing.

The use of ultrasound analysis has many potential applications in the fields of: 

• Electrical inspection
• Steam trap maintenance
• Leak detection
• Mechanical inspection
• Testing of valves
• Electric arc flash detection.

Specific UA instruments are equipped with thermometers and cameras for more advanced data collection and analysis.

Advantages

• Cheaper than that of other predictive maintenance technologies
• The noises may be heard by technicians using the program, making it straightforward to use and comprehend
• The ability to quickly identify and pinpoint the exact location of any problems is another advantage of using UA
• From that vantage point, technicians can often take measurements without physically touching the object.

Disadvantages

• The distance between the detector and the test subject makes repeatability difficult.

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6. Laser-shaft Alignment Tool

Laser shaft alignment instruments can test a facility's precision-aligned rotating shafts. Improper installation procedures during equipment startup are a common source of mechanical failure.

It is used for:

• When parts of an asset aren't lined up properly, whether an angle or offset misalignment, the whole drive train takes a beating. It helps in alignment.
• In most cases, misplaced shafts put the most strain on the bearings.
• Laser-shaft alignment instruments use single-laser measuring technology to reduce inaccurate results caused by the backlash.

Advantages

• Machine alignments may be completed with ease using laser-shaft alignment instruments.
• It ensures the shaft is aligned correctly and drastically reduces mechanical failures.

Disadvantages

• The need to halt equipment to do analysis is one of the disadvantages.

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Why Choose Clue for Predictive Maintenance Equipment

Is your backhoe acting up again? Well, you don't have to worry, Clue steps in as your reliable predictive maintenance equipment manager, offering a practical solution. 

Say goodbye to outdated spreadsheets and welcome streamlined equipment management with our construction equipment maintenance software. Clue efficiently tracks everything from location to maintenance needs, ensuring your equipment is always ready for action. 

Forget about frantic searches for missing tools; Clue provides real-time updates and empowers your team to tackle issues proactively. With Clue, your projects stay on track and within budget thanks to its user-friendly interface that's easier to navigate than a foreman's instructions.

Say farewell to guesswork and embrace Clue for efficient equipment management.

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Powerful Features for Predictive Maintenance

• Centralized Equipment Management lets you get a consolidated view of your entire fleet of assets and equipment, including vehicles, attachments, and tools.
• Streamlined Work Order Management: Enables better control of the flow of work orders, which puts timely equipment maintenance and repairs at the forefront.
• Optimized Dispatch: Users can efficiently allocate resources by matching the right equipment with the right task.
• Simplified Inspections: Streamline safety and compliance by leveraging smart digital inspection checklists and annotating photos of any issues.
• Proactive Maintenance Alerts: Set automated alerts to avoid equipment breakdowns. It will notify you in advance of any upcoming maintenance needs.
• Effortless Equipment Tracking: Location can be efficiently monitored to help keep asset track via real-time, intuitive scanning technology.

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Conclusion and Future Outlook

Leveraging cutting-edge predictive maintenance equipment technologies is the future, and the future is now. As PdM manufacturers keep upgrading their solutions, this approach to maintenance will become more cost-effective. 

In any case, PdM implementation takes time. To successfully deploy a CMMS system, one must allocate sufficient time and resources and procure easy-to-use construction equipment maintenance software.

You can trust Clue, a cloud-based maintenance management solution since it prioritizes your convenience, cost, and security. Are you prepared to take your newly streamlined and standardized procedures live? 

Try Clue Today!

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FAQs

Which is better: Preventive or Predictive Maintenance Equipment Software?

Predictive maintenance reduces downtime and manual labor by accurately forecasting failures, though it requires more investment and infrastructure. Preventive maintenance is cheaper and simpler to implement but may result in more downtime. The best choice depends on your organization's resources and equipment needs.

What are the four types of Construction Equipment Maintenance Software?

Here are the four types of construction equipment maintenance software

• Corrective Maintenance: Repairs equipment after a fault is detected.
• Preventive Maintenance: Regular, scheduled maintenance to prevent failures.
• Predictive Maintenance: Uses data to predict and prevent potential equipment failures.
• Condition-Based Maintenance: Monitors real-time equipment conditions to perform maintenance based on actual needs.

What is an example of predictive maintenance machine learning?

Predictive maintenance leverages machine learning to analyze data from various sensors and predict equipment failures before they happen. Common examples include:

• Vibration Analysis: Uses sensors to detect abnormal vibrations that indicate potential mechanical issues.
• Oil Analysis: Monitors oil quality to detect contaminants or wear particles that signal equipment degradation.
• Thermal Imaging: Utilizes infrared cameras to identify overheating components, preventing potential failures.
• Equipment Observations: This department employs machine learning algorithms to assess operational data, such as temperature, pressure, and usage patterns, predicting maintenance needs with high accuracy.

These techniques allow for real-time monitoring and early detection of issues, optimizing maintenance schedules and reducing downtime.