Predictive Maintenance: Current Landscape and Future Directions

Preventive maintenance is a routine equipment check that typically relies on operating hours or scheduled intervals. For instance, an airline might conduct a “100‑hour teardown” of a jet engine after it has logged 100 hours of flight time.

Predictive maintenance (PdM) goes a step further by forecasting potential failures before they happen and gathering data for operators and OEMs to analyze. While wired bus protocols such as Profibus and Modbus have enabled continuous monitoring for decades, the challenge now is delivering that data out of the factory and into the hands of third‑party service providers.

Choosing the Right Wireless Solution for M2M

In this article we explore how predictive maintenance works today, the obstacles it faces, and what we expect to shape the practice in the coming years.

Current Challenges and Practical Solutions

Easier Data Harvesting with LPWA Networks

One of the biggest obstacles for PdM programs is extracting data from equipment. This information is valuable not only to the plant owner but also to the OEM that built the machinery. Without continuous data flow, modeling and forecasting become unreliable. LPWA (Low‑Power Wide‑Area) networks—such as Symphony Link—provide a cost‑effective way to pull data from third‑party assets without disrupting operations.

Typical PdM data streams fall into two categories:

1. Internally generated data – machine‑generated metrics like battery status, fault codes, and performance indicators.
2. Externally observable data – non‑intrusive measurements such as infrared heat, acoustic signatures, vibration, sound levels, oil viscosity, and current draw.

When deployed correctly, a PdM system can tap into existing sensors and instruments and begin harvesting data immediately, preserving uptime.

Uptime as a Service

Predictive maintenance enables OEMs to shift from selling a product to selling uptime. Rather than simply selling an engine, an OEM could charge customers for each hour the engine operates, handling all maintenance in return. This model is most viable where the OEM’s service team can access the site and replace equipment quickly.

Significant Cost Savings

Traditional troubleshooting often involves sending a technician to identify a fault, which can be costly and time‑consuming. PdM data pinpoint the exact failure and prescribe the necessary repairs, cutting service costs and minimizing downtime.

Accelerated Feedback Loops

A robust PdM system offers real‑time design insights. Early product releases can be evaluated immediately, allowing rapid iterations and reducing the overall development cycle. It also helps uncover root causes of failures during the design phase.

What the Future Holds for Predictive Maintenance

Standardization of Sensor Interfaces

Future industrial automation hinges on standardized sensor interfaces. Standardization reduces friction for OEMs and customers, fostering interoperability. Although many vendors favor proprietary solutions, industry‑driven standards will become essential. Companies can start by piloting PdM on a small scale, learning from varied use cases before full adoption.

LTE‑M and NB‑IoT: Low‑Cost, Low‑Power Connectivity

Cellular technologies such as LTE‑M and NB‑IoT enable direct sensor connectivity with minimal cost and power consumption. Battery‑powered sensors can now connect straight to the cellular network, eliminating the need for costly data hubs (often priced at $1,200) and reducing monthly data fees to $10‑$30. This opens the door to widespread deployment of PdM across remote or challenging sites.

Choosing the Right Wireless Network

In predictive maintenance, the value comes from the sensor and application layer, not the transport protocol. While wired and wireless options may deliver similar performance, factors like cost and deployment feasibility differ. For example, a nuclear plant cannot rely on a public Wi‑Fi network for critical data.

For a deeper dive into the benefits and trade‑offs of various wireless technologies, download our free white paper.