Predictive maintenance

Predictive maintenance tools watch equipment while it runs and warn you before a failure stops a line. Most start with sensors: vibration and temperature sensors on motors, pumps, fans and gearboxes, sometimes with current or ultrasound data added. Software learns what normal looks like for each machine and raises an alert when the pattern drifts.

The tools listed here take different routes. Augury, Tractian, KCF Technologies and Nanoprecise sell their own wireless sensors together with the analysis software, so a plant can start with a few critical assets and add more over time. Uptake and IBM Maximo lean more on data you already collect from historians, SCADA tags and maintenance records, and they fit sites that instrumented their equipment years ago.

Before you buy, list the assets that hurt most when they stop, and check what each vendor can monitor on them. Slow-turning shafts, variable-speed drives and machines in hazardous areas need sensors rated for that duty. Ask how alerts reach the people who act on them. An email to a shared inbox gets ignored; a work order in your CMMS gets scheduled. Most of these tools connect to maintenance systems such as Maximo, Fiix, MaintainX or UpKeep, so confirm the link with the one you run.

Expect a learning period. Models need weeks of normal running to set a baseline, and early alerts need a technician to confirm them. Keep a record of which alerts led to real findings, because that is how you show whether the program pays for itself. Data ownership matters too: ask where sensor data is stored, whether you can export it, and what happens to your history if you change vendors.

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6 AI manufacturing tools in predictive maintenance

Augury

Machine health monitoring with wireless vibration and temperature sensors and AI diagnostics for rotating equipment.

Runs as a cloud service

Uptake

Asset analytics software that uses sensor and maintenance data to predict failures and prioritize work on heavy equipment.

Runs as a cloud service

IBM Maximo Application Suite

by IBM

Enterprise asset management suite with asset monitoring, health scores and predictive maintenance alongside work management.

Runs as a cloud service
Can run on premises

Tractian

Wireless condition monitoring sensors paired with a maintenance app, aimed at plants starting predictive maintenance.

Runs as a cloud service
Mobile app

SMARTdiagnostics

by KCF Technologies

Wireless vibration and temperature monitoring for plant equipment, with software that flags machines needing attention.

Nanoprecise

Wireless multi-sensor units and AI analytics that estimate the condition and remaining life of rotating equipment.

Runs as a cloud service

Costs vary widely between approaches. Sensor kits carry hardware, installation and subscription costs per asset, while software that runs on existing data costs more in integration and data work. Ask vendors to price the same list of assets so you can compare them fairly, and include the time your own team will spend reviewing alerts and confirming findings in the first months. If your plant runs shifts, decide who sees alerts at night and on weekends, and what counts as urgent enough to stop a machine.

Reliability engineers often pair these tools with simple root cause reviews, so each confirmed fault leads to a fix in lubrication, alignment or operating practice that stops it coming back.

These tools support your reliability team and your safety systems. They do not replace machine guarding, lockout and tagout, or the protective devices already on the equipment.

Questions about predictive maintenance

How many machines should a predictive maintenance pilot cover?

Start with a small group of critical assets that fail often enough to prove the point, often ten to thirty machines on one line or utility system. That gives the models enough data and lets the team build a routine for reviewing alerts before you scale up.

Do I need sensors, or can I use existing data?

It depends on what you already collect. Vendors such as Augury and Tractian bring their own sensors. Uptake and IBM Maximo can work from historian data, SCADA tags and maintenance records when those exist and are reasonably clean.

Will predictive maintenance replace our preventive schedule?

Usually it adjusts it. Condition data can stretch or shorten fixed intervals on monitored assets, but lubrication, inspections and regulatory checks still need a schedule. Keep both until the data shows a task can safely change.

What should we ask about data security?

Ask how sensors and gateways connect, whether data leaves your network, where it is stored and who can see it. Involve your IT and OT security teams before installation, since gateways sit close to production equipment.