Predictive Maintenance

See machine failures coming and notify your team immediately, preventing downtime and informing your maintenance planning.

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Based on 268+ reviews

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150,000+
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eMaint CMMS equips your team to perform predictive maintenance: sensors alert you to coming failures, and work orders trigger automatically to inform your team.

  • Taps into asset data from Fluke sensors and SCADA systems & notifies you of faults or failures with alarms

  • Gives you deep insight into asset health with condition monitoring software
  • Empowers you to automate work orders that trigger when failures may be coming
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Downtime disasters are coming — and for some businesses, that can mean a loss of as much as $100,000 per hour of shutdown. eMaint gives you the ability to predict failures, respond to them quickly, and optimize your maintenance planning for the months and years ahead.

We want to hear from you: what’s your biggest challenge? Learn how eMaint CMMS can help.

Monitor Assets, Set Alarms, and See Failures Coming

eMaint gathers data from Fluke vibration sensors and can tap into SCADA/PLC systems.

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Don’t spend your days firefighting unplanned downtime — sensors give you the data you need to prevent failures

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Monitor asset health with sensors

eMaint connects seamlessly with Fluke 3563 Analysis Vibration Sensors. You can also tap into SCADA, PLC, BAS/BMS, and MES/MOM systems. Monitor your critical assets, gaining quick insights into vibration and temperature levels. Choose when and how often to capture measurements.

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Predict possible faults & failures with alarms

Set up alarms to update your on asset status and notify your team of possible faults. Trigger alarms when vibration levels exceed overall limits. Set alarms to go off when vibration signatures match narrowband indications of the four major rotating machinery faults: misalignment, looseness, imbalance, and bearing failure.

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Respond to failures immediately, boosting uptime

eMaint condition monitoring makes sure the right person at the right time is notified when vibration levels exceed your limits. Receive email alerts and updates. Automate work orders to trigger when asset data heralds a failure.

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“Since we chose eMaint, I’ve been able to reduce our work orders from about 500 a month to around 50—and now we do a lot of PMs… We’ve increased our uptime from an average of 80% to 95, 96, even 97% for some production lines”

James Kalinski, Facility Engineer at Advanced Atomization

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Simplified Condition Monitoring Software

eMaint condition monitoring simplifies vibration analysis and provides AI recommendations.

Your asset is in danger of failing. Now what? Our vibration analysis software can help — and our AI has a few suggestions.

Simple, flexible data exploration

Quickly navigate between assets and easily filter to the vibration data snapshots you need. Drag & drop vibration charts for comparison. Track & trend overall vibration readings and dive into the FFT spectrum to determine sources of excess vibration.

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Discover strategies that strengthen machine health & reliability

Explore historical data to get a complete picture of machine health over time. Review maintenance history, usage, and uptime in eMaint CMMS. Find common causes of faults and failures, document them, and eliminate them — increasing asset uptime.

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AI recommendations that help non-experts

eMaint’s AI analysis can recognize more than 1600 combinations of fault factors. Get AI-powered maintenance and corrective work suggestions based on specific faults. Receive email notifications with the urgency of the response action, severity of the fault, and prescribed corrections in easy-to-understand language.

Connect Your Teams & Automate Work Orders

Everything is connected. eMaint can tap into your condition monitoring data to automate notifications and work orders.

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Missing information, siloed teams, and slow downtime response lead to maintenance nightmares. Luckily, you have eMaint.

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Automate work orders & maximize uptime

Automate work orders to trigger based on Fluke sensor or SCADA/PLC alarms. Respond quickly to production line disasters. Set up automated work orders to include standard instructions, procedures, or tasks, compliance documents, expected tools and parts.

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Mobile makes life easy

Connect your teams in the field and offline with the eMaint mobile app. Send them work orders in the field that pop up as push notifications on their smartphone or tablet. Once your asset alarms go off and a work order is automatically generated, techs can perform predictive maintenance in the field, completing the work order from their phone.

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Build a winning maintenance strategy

See machine faults coming, sometimes months in advance, and plan accordingly, prioritizing work and allocating resources. Quickly and easily build enterprise-level reports and dashboards. Discover insights that boost KPIs and drive production with an eagle-eye view of both condition monitoring data and maintenance history.

Frequently Asked Questions for Predictive Maintenance

Predictive maintenance (PdM) is a proactive strategy that utilizes a combination of sensors and specialized software to collect, store, and analyze asset performance data. Maintenance teams use this data to detect when machine faults develop and schedule maintenance to repair these faults before failure.

Many modern PdM programs use a computerized maintenance management system (CMMS) to manage their maintenance data, tasks, and schedules. For instance, some CMMS platforms allow facilities and asset management teams to set up alarms that sound when performance data moves past a certain threshold. These alarms indicate that an asset requires maintenance as soon as possible. Some CMMS  programs can also trigger work order generation automatically so that maintenance is requested and completed right away.

Though the terms sound similar, there is a difference between predictive maintenance and preventive maintenance. Preventive maintenance focuses on developing and adhering to a regular schedule of proactive maintenance actions. Predictive maintenance, on the other hand, relies on machine data to determine which maintenance actions to carry out and when.

Predictive maintenance programs rely on data-collection tools like pressure, vibration, and temperature sensors. Maintenance professionals also use data analysis tools like handheld analyzers or a CMMS platform in order to get insight into how assets are performing. Armed with this data, teams can predict when issues will crop up and complete maintenance long before failure occurs. In a predictive maintenance program, teams don’t have to wait for regularly scheduled inspections and maintenance as per a preventive maintenance process.

As with any business or operational decision, there are pros and cons to a predictive maintenance approach.

There may be challenges specific to your industry or the products or services that your company offers. However, there are some challenges of predictive maintenance that nearly any company could face:

  • High initial cost: A good PdM program requires investing in specialized software (usually a CMMS) and a network of sensors to capture data. These sensors need to be compatible with each other and whichever platform you’re using to manage data. You will need to invest in a high-quality CMMS that offers all the benefits you need for PdM, such as an alarm notification system and automatic work order creation.
  • Complex implementation and rollout: Because of all of the components that support preventive maintenance, implementing and rolling out PdM operations can quickly become complex. You need to decide which sensors to use,, determine individual machine performance thresholds, and decide how to implement a PdM approach into current maintenance systems. Due to this complexity, it can also be time-intensive to train staff on new processes.

What Are the Benefits of Predictive Maintenance?

There are substantial benefits to a predictive maintenance strategy. While some are specific to certain industries, products, or services, several benefits are common across industries and organizations. They include:

  • Reduced unplanned downtime: By addressing issues early, you avoid asset failure that leads to unplanned downtime.
  • Safer work conditions: Proactive maintenance means that machines and equipment are far less likely to create unsafe conditions, like an overheated engine or an over-pressurized compressor, that could harm workers.
  • Longer asset lifespans: By servicing and repairing assets before issues get severe, they experience less physical strain. Assets last longer than they would with more reactive maintenance.
  • Lower maintenance costs: Because PdM helps maintenance staff address issues proactively, that typically means repairs are less expensive. And because assets have longer lifespans, costs for replacing equipment are lower over time.
  • Lower revenue loss due to asset failure: Asset failures create unplanned downtime that causes your team to run behind on production, eventually losing revenue. PdM prevents these situations so that your operations can run with fewer disruptions.

Any PdM program will involve using sensors to collect data and carrying out necessary maintenance based on asset condition. But different industries use specific tools and techniques to collect, analyze, and act on data, resulting in different predictive maintenance strategies.

These include:

  • Oil analysis – Used to monitor the condition of oil-based lubricants that help machines and systems physically operate with minimal friction. Includes testing for viscosity, acidity, and particulate contamination.
  • Vibration monitoring (i.e., vibration analysis) – Used to monitor the vibrations of oscillating machines, parts, or systems to look for abnormal frequencies, phases, and vibration amplitudes.
  • Temperature monitoring (i.e., thermal analysis) – Used to ensure systems stay at the appropriate temperature by helping spot signs of overheating or overcooling, both of which can damage equipment.
  • Electrical monitoring – Used to monitor the health of electrical systems by collecting data on electrical impedance, resistance, and surges.
  • Pressure monitoring (i.e., pressure analysis) – Used to collect pressure-related performance data, such as on pneumatic equipment and hydraulic equipment to spot issues like leaks, blockages, and excess load.