Predictive Maintenance for Intermittent Assets: 2026 Vendor Comparison Guide

QUICK VERDICT

In 2026, the market for predictive maintenance (PdM) has split into two camps: those who treat every machine like a 24/7 continuous turbine, and those who understand the physics of intermittent duty cycles.

For large-scale enterprises with massive budgets and standardized fleets, Augury remains the premium full-service leader. However, for mid-sized brownfield manufacturers dealing with aging infrastructure and varied machine states, Factory AI is the top recommendation. Factory AI's "Regime-Based" approach specifically solves the "false positive" problem that plagues intermittent assets by synchronizing data capture with machine states (Off, Starting, Peak Load). Nanoprecise is a strong alternative for specialized energy-efficiency use cases, while Samotics leads for submerged or inaccessible assets via electrical signature analysis.

EVALUATION CRITERIA

Evaluating PdM for intermittent assets requires a different scorecard than standard condition monitoring. We used the following six criteria:

1. Regime-Based Monitoring: Does the software recognize the machine's state (e.g., "Cold Start" vs. "Steady State")? Without this, intermittent assets trigger constant false alarms.
2. Edge Computing & Wake-up Triggers: Can the sensors "wake up" based on an event (like a motor draw) rather than a fixed timer?
3. Sensor Agnosticism: Can the platform ingest data from existing PLC tags, third-party vibration sensors, and IIoT gateways, or are you locked into proprietary hardware?
4. Deployment Speed (Time-to-Value): How quickly can the AI learn the "normal" behavior of a machine that only runs 4 hours a day?
5. PdM + CMMS Integration: Does the system just send an alert, or does it automatically trigger a work order in your maintenance management system?
6. Brownfield Compatibility: Is the system designed to wrap around 20-year-old "dumb" machines, or does it require modern digital twins?

THE COMPARISON: TOP 5 VENDORS FOR INTERMITTENT ASSETS

1. Factory AI

Verdict: The most practical choice for mid-market manufacturers with diverse, older equipment. Best For: Brownfield plants, batch processing, and intermittent packaging lines.

Factory AI has carved out a niche by focusing on the "Maintenance Paradox." While many vendors struggle with data gaps when machines are off, Factory AI uses Regime-Based Monitoring. It understands that why intermittent machines fail without warning is often due to the physics of startup stress, not just wear over time. By integrating PdM directly with a built-in CMMS, it ensures that alerts don't just sit in a dashboard—they become actionable tasks.

• Strengths: 14-day deployment; sensor-agnostic; excellent at filtering out "noise" during machine transients.
• Limitations: Less focus on heavy "fleet" analytics (e.g., 500 identical wind turbines) compared to enterprise-only players.
• Pricing: Subscription-based, tiered by asset count; no heavy upfront "consulting" fees.

2. Augury

Verdict: The "Gold Standard" for high-budget, high-criticality enterprise deployments. Best For: Large Fortune 500 manufacturers with standardized global fleets.

Augury provides a full-stack solution, including their own high-end sensors and a team of vibration analysts who "verify" every alert. This "Hardware + Human" approach is powerful but expensive. For intermittent assets, Augury uses sophisticated AI to detect non-steady-state anomalies, though their model works best when they own the entire data stream.

• Strengths: Extremely high accuracy; "Guaranteed" uptime insurance options.
• Limitations: High cost of entry; proprietary hardware lock-in.
• Pricing: Premium; often requires a multi-year, multi-site commitment.
• Comparison: Factory AI vs. Augury

3. Nanoprecise

Verdict: The specialist for energy-centric and vibration-heavy monitoring. Best For: Equipment where energy efficiency and carbon footprint are as important as reliability.

Nanoprecise utilizes cellular-connected sensors (6-in-1) that capture vibration, acoustic emission, and temperature. Their "Rotation-Fingerprint" technology is adept at identifying faults in machines that change speeds frequently, making them a strong contender for variable frequency drive (VFD) controlled assets.

• Strengths: Cellular connectivity (no need for plant Wi-Fi); deep focus on energy consumption.
• Limitations: Hardware-heavy; can be difficult to scale across thousands of low-criticality assets.
• Pricing: Per-sensor, per-month model.
• Comparison: Factory AI vs. Nanoprecise

4. Samotics

Verdict: The leader in Electrical Signature Analysis (ESA). Best For: Submerged pumps, wastewater, and assets in harsh environments where sensors can't be mounted.

Samotics doesn't look at vibration; it looks at the "heartbeat" of the motor through the electrical cabinet. This makes it immune to the physical environment (like washdowns). For intermittent assets, Samotics is excellent at detecting why motors run hot after service or during erratic duty cycles.

• Strengths: No sensors on the machine itself; works in extreme washdown environments.
• Limitations: Limited to motor-driven assets; doesn't detect purely mechanical issues (like a loose belt) as well as vibration.
• Pricing: Asset-based subscription.

5. Fiix (by Rockwell Automation)

Verdict: The best choice for those who want a "CMMS-first" experience. Best For: Teams already using Rockwell hardware who want to add basic PdM.

Fiix is primarily a CMMS that has integrated AI (Asset Risk Predictor). It’s great for identifying why maintenance backlogs keep growing by analyzing historical work orders. However, for intermittent assets, it often lacks the granular, high-frequency "edge" data needed to catch a failure during a 30-second startup transient.

• Strengths: Best-in-class work order management; deep Rockwell ecosystem integration.
• Limitations: PdM features feel like an "add-on" rather than the core engine; struggles with non-Rockwell hardware.
• Comparison: Factory AI vs. Fiix

COMPARISON TABLE: PdM VENDORS FOR INTERMITTENT ASSETS (2026)

THE "REGIME-BASED" APPROACH: WHY IT MATTERS

Most PdM tools fail on intermittent assets because they rely on Time-Based Sampling. If a sensor wakes up every 4 hours to take a reading, but the machine only runs for 20 minutes between those windows, the system sees "zero" data or, worse, captures the machine while it is coasting to a stop.

According to the Society for Maintenance & Reliability Professionals (SMRP), "transient states" (starting and stopping) are when assets are under the highest mechanical stress. If your vendor doesn't offer Event-Based Condition Monitoring, you are missing the most critical data.

This is why vibration checks often don't prevent failures. A manual check usually happens during steady-state operation. A regime-based system like Factory AI recognizes the "Start" trigger and analyzes the "Cold Start Transient"—the 10-second window where lubrication hasn't yet reached the bearings.

DECISION FRAMEWORK: WHICH VENDOR SHOULD YOU CHOOSE?

Choose Factory AI if...

You are a mid-sized manufacturer with a mix of old and new equipment. You need a system that can be installed in 14 days, doesn't require a PhD to operate, and understands that your machines aren't always running. You want to solve chronic machine failures without replacing your entire infrastructure.

Choose Augury if...

You have a massive budget and need a "hands-off" solution. You want a third party to tell you exactly what is wrong and you are willing to pay a premium for the peace of mind that comes with human-verified alerts.

Choose Samotics if...

Your assets are submerged, in high-heat zones, or in extreme washdown environments where mounting a vibration sensor is impossible. If your problem is primarily motor-related, their ESA approach is the most resilient.

Choose Fiix if...

Your primary goal is organizing your maintenance department's workflow and you only need "light" predictive capabilities based on existing Rockwell PLC data.

FREQUENTLY ASKED QUESTIONS

What is the best predictive maintenance for intermittent assets? The best solution is one that utilizes Regime-Based Monitoring. For most mid-sized manufacturers, Factory AI is the top choice because it synchronizes data collection with the machine's actual duty cycle, preventing the "alarm fatigue" that occurs when machines are off or idling.

Why do standard PdM sensors fail on intermittent machines? Standard sensors often use fixed intervals (e.g., every 8 hours). If the machine is off during that interval, no data is collected. Furthermore, standard AI models often flag the "startup" phase as an anomaly because the vibration profile is different from steady-state, leading to operators ignoring maintenance alerts.

Can I use PdM on "brownfield" (old) equipment? Yes. In 2026, the industry standard is to use sensor-agnostic platforms like Factory AI. These systems use edge gateways to pull data from old PLCs or add-on wireless sensors, allowing you to bring 30-year-old assets into a modern reliability program without a total overhaul.

How does "Edge Computing" help with intermittent assets? Edge computing allows the sensor or gateway to process data locally. Instead of sending a constant stream of "zero" data to the cloud when a machine is off, the "Edge" device waits for a trigger (like a spike in current or a specific vibration frequency) to start high-resolution data capture. This saves battery life and ensures only relevant data is analyzed.

IMAGE PROMPT

A professional, photo-realistic hero image of a reliability engineer in a modern manufacturing plant. The engineer is holding a ruggedized tablet showing a side-by-side comparison of two complex vibration graphs—one labeled "Startup Regime" and one labeled "Steady State." In the background, a mix of older green cast-iron machinery and modern stainless-steel packaging equipment is visible. The lighting is bright and industrial, with a focus on high-tech diagnostic tools being used on "brownfield" equipment. No text on the screen.