Background of Predictive Maintenance

For decades, predictive maintenance programs have had a cyclical existence at continuous process plants. When budgets tighten or teams reorganize, these programs are often the first to be cut — until an unexpected, costly failure reminds leadership just how valuable they are. This flow and ebb happens because predictive maintenance has long been viewed as important, but not essential. In the short term, suspending a program may not seem to matter. But over time, machine wear, age, and unpredictable breakdowns always prove otherwise.

But that mindset has shifted. As technology advanced and downtime has became more expensive, predictive maintenance has evolved into a connected, data-driven discipline powered by remote monitoring. Today, it is defined by connectivity and real-time insight — the era of remote monitoring is well established.

The Rise of Remote Monitoring

A combination of factors has reshaped predictive maintenance, leading to the rise of remote monitoring and analysis.

Advances in digital technology, connected sensors, and cloud-based platforms have automated data collection and analysis, removing the limitations of traditional, manual routes. This shift allows maintenance teams to focus on what matters most: interpreting results and acting on insights.

With secure online dashboards and mobile access, teams and reliability experts can view live equipment data anytime, anywhere—on-site, in the field, or off duty—and make faster, more informed decisions together.

But the impact of remote monitoring goes beyond convenience — it represents a fundamental change in how assets are managed. Instead of applying the same inspection schedule to every machine, teams can now prioritize based on criticality. Critical equipment can be monitored continuously, while less essential assets are checked less frequently.

This data-driven approach wasn’t practical in the era of manual collection. Many critical assets were difficult to reach, required extra safety precautions, or demanded costly travel and labor. Automated monitoring changed that completely. Health metrics can now be captured as often as needed, without the risk, downtime, or expense of traditional walk-around rounds.

The value of this evolution becomes even clearer when viewed against the challenges facing today’s industrial operations:

  • Intense global competition. Companies are under pressure to produce more while reducing operating costs.
  • Rising energy costs. Higher fuel and utility expenses continue to impact profitability.
  • Shrinking skilled workforce. As experienced technicians retire, fewer qualified workers are available to take their place.

Powered by Wireless Technologies

The driving force behind this evolution is wireless connectivity.

Modern wireless sensors and industrial networks now make it possible to stream machine data continuously, without the need for complex wiring or manual transfers. What once required expensive infrastructure or frequent site visits can now be done from virtually anywhere.

A reliability engineer can review machine health data in the office, on the plant floor, or halfway around the world. With secure connectivity and browser-based tools, insights travel instantly between the equipment and the people who keep it running.

Wireless technology brings several clear advantages:

  • Widely available and cost-effective. Reliable wireless devices are now standard in industrial environments.
  • No cabling or complex installation. Sensors can be deployed quickly without disrupting operations.
  • Minimal IT burden. Modern platforms integrate easily with existing systems and security standards.
  • True mobility. Teams can access data and collaborate from anywhere, anytime.

Benefits of Remote Monitoring

As predictive maintenance continues to evolve, plant leaders are adopting wireless, cloud-connected systems that drive efficiency and reliability. Here are ten reasons why remote monitoring remains one of the most valuable strategies in modern maintenance:

  1. Focus on analysis, not collection. With smaller teams and growing workloads, remote monitoring allows analysts to spend more time interpreting data and less time walking routes with sensors.
  2. Access hard-to-reach assets. Automated systems collect data from equipment in hazardous, confined, or remote areas. There is no need to send personnel into risky environments.
  3. Improve safety. Cranes, conveyors, open drives, and gear sets all pose dangers to workers performing manual inspections. Automated collection keeps people out of harm’s way.
  4. Collect data around the clock. Machines don’t stop for weekends or holidays, and neither does remote monitoring. Data flows continuously, unaffected by shifts, sick days, or staff turnover.
  5. Capture more metrics. Go beyond vibration. Integrated sensors can track speed, temperature, pressure, and flow, providing a fuller picture of equipment health.
  6. Ensure consistent data quality. Manual routes often miss readings when machines aren’t running. Automated systems capture data when conditions are optimal for analysis.
  7. Increase frequency for critical assets. Problem machines can be monitored more often or continuously without added labor or travel costs.
  8. Gain plant-wide visibility. A unified database aggregates data from all sites, giving maintenance and reliability teams a single, real-time view of performance.
  9. Set more accurate alarms. With hundreds of automated data points instead of a handful of monthly readings, alarm thresholds can be statistically defined and more reliable.
  10. Detect issues sooner. Remote systems catch vibration or temperature changes well before a trip or shutdown reducing downtime and preventing costly failures.

Remote Monitoring Philosophies

Remote monitoring can take many forms, from simple alert-based systems to advanced analytical platforms that process full waveform and spectral data.

Monitoring Type Description Insights Gained
Basic Monitoring Tracks general vibration levels or status indicators (e.g., high, normal, low). Ideal for a quick view of overall machine condition. Provides limited detail. Elevated readings indicate a potential issue but don’t identify root causes due to lack of spectral data.
Advanced Monitoring Collects comprehensive vibration data including spectra, waveforms, and trend information. Can capture transient events such as startups, coastdowns, and critical speed behavior. Enables in-depth fault detection and diagnosis, revealing not just that a problem exists—but what’s causing it and how severe it is.

At its core, the choice between simple and complex monitoring depends on who will interpret the data. A sophisticated monitoring system delivers deeper insights such as waveform trends, startup and coast-down data, or critical speed identification but only when qualified analysts are available to interpret those results.

That’s where the true power of connectivity comes in. With modern cloud platforms, data and expertise no longer need to exist in the same place. Off-site specialists can securely access machine information, review live or trended data, and provide actionable recommendations directly to maintenance and operations teams.

Connectivity also allows specialists to adjust analysis settings remotely, increasing sampling rates, changing frequency ranges, or capturing high-resolution spectra when anomalies appear.

For analysts and engineers, the most valuable features of a connected monitoring system include:

  • Automatic alerts and notifications when conditions exceed normal thresholds.
  • Secure, anytime access to vibration and process data through web and mobile interfaces.
  • Remote control of analysis parameters, enabling more targeted data capture when needed.

The Web-Based Approach

Modern remote monitoring systems can be deployed in several ways, depending on how data needs to be accessed and shared.

Earlier setups often relied on remote desktop connections or on-site servers accessed through VPNs—solutions that required heavy IT support and limited flexibility.

Today, browser-based and cloud-hosted platforms have become the preferred standard. With secure login credentials, users can access machine data from any device—no client software or local installation required.

This approach offers clear advantages:

  • Universal access. Plant staff, analysts, and even OEM partners can view data simultaneously and collaborate in real time.
  • Minimal setup. Web-based platforms require no special software, and most users are already familiar with their navigation.
  • Lower IT overhead. Data management, updates, and security protocols are handled automatically through the platform.

Acquiring Data: Wired vs. Wireless

There are several ways to transfer vibration and performance data from equipment to the systems where analysts can review it.

Approach Description Typical Use Case
Wired Network Sensors are hardwired to a data acquisition unit that transfers data directly to an on-site computer. Reliable for stationary installations where cabling is practical.
Hub-Based Ethernet Sensors connect to a local hub, which then sends data to a central server through an Ethernet cable. Common in facilities where sensors are clustered near each machine.
Wireless Network Sensors transmit data wirelessly to an on-site or cloud-based server, with some systems streaming directly to off-site analysts. Ideal for remote or hard-to-access assets where running cables is costly or unsafe.

Today, most facilities are adopting wireless data acquisition, which offers greater flexibility and scalability. There are two main ways to collect wireless data:

1. Battery-powered sensor/transmitter combinations.
These devices mount directly to a bearing or housing and transmit data wirelessly. However, they can face challenges such as:

    1. Exposure to heat that may damage electronics.
    2. Risk of wear or impact damage in high-traffic areas.
    3. Poor signal strength if mounted in obstructed locations.
    4. Higher replacement costs when combined components fail.

2. Standard sensors connected to a nearby wireless hub.
This approach separates the sensor from the transmitter, improving durability and flexibility.

    1. The hub samples and transmits data wirelessly to the monitoring system.
    2. It can be positioned for optimal transmission—away from heat, above the machine, or in an accessible area.
    3. Battery-powered hubs work well for periodic measurements, while line-powered hubs support continuous monitoring.

Connectivity and Security Today

Modern wireless systems use secure industrial communication standards designed for high reliability and low latency. These networks are built with layered security—authentication, encryption, and segmentation—so data remains protected from unauthorized access. The result is seamless, real-time communication between assets, analysts, and enterprise systems—without compromising safety or performance.

Conclusion: Remote Monitoring Defines the Future of Predictive Maintenance

As technology continues to advance, predictive maintenance has moved far beyond its early roots. Modern wireless systems and cloud-based platforms deliver real-time data to maintenance teams and off-site experts alike—bridging gaps in skill, time, and location.

For plants facing workforce shortages or operational complexity, remote monitoring transforms how reliability work gets done. With standardized sensors, intelligent hubs, and secure connectivity, organizations can continuously capture the data that matters—without adding strain to their teams.

The result is smarter, faster decision-making that protects uptime, extends equipment life, and maximizes efficiency across every site.

Author Bios

Nelson Baxter has 30+ years experience in vibration analysis and advanced testing of industrial equipment in nuclear and fossil power plants, steel mills, and paper mills.

Heather De Jesús 10+ years experience in vibration analysis, including experience with Modal Analysis and Finite Element Analysis (FEI) for various mechanical systems. She has extensive knowledge of Balance of Plant systems for nuclear power plants and has performed rotor balancing and engine harmonics testing on Naval helicopters.