At Sensor Partners, we believe that smart maintenance starts with insight. Modern machinery demands more than reactive action - it demands data, analytics and automation. In this article, we show you how Condition-Based Maintenance (CBM), Predictive Maintenance (PdM) and our NeuronSensors solutions can help you organize maintenance smarter. From measurement to prediction, and from insight to automatic action, we help you prevent downtime and improve processes.
The timely and targeted maintenance of machinery, plant and other assets is more complex than ever. Machinery is becoming more sophisticated and sensitive, while the cost of parts, manpower and downtime continues to rise. At the same time, stricter safety regulations, sustainability requirements and the pressure to keep production processes running continuously create additional challenges. Maintenance must therefore not only be well planned, but also smart and data-driven.
Traditional maintenance is often reactive, preventive or periodic. That means maintenance occurs after a malfunction, at fixed time intervals, or based on general guidelines - without looking at the actual condition of the machine.
Modern strategies such as Condition-Based Maintenance (CBM). and Predictive Maintenance (PdM). offer a better alternative here. They help reduce unplanned downtime and unnecessary maintenance costs through better insight into the true condition of installations.
Both CBM and PdM use wireless IoT sensors that measure parameters such as:
These sensors collect near real-time data about the operation and condition of machines. For example, vibration sensors can detect imbalance or wear of rotating parts.
Schedule a no-obligation appointment and find out what Predictive Maintenance can do for your business.
CBM is based on the current condition of an asset. Sensors measure parameters such as vibration, temperature or power consumption. As long as these remain within safe limits, maintenance is not required. As soon as abnormalities are detected, maintenance is scheduled.
PdM goes a step further: based on historical and real-time data, algorithms predict when a failure is likely to occur. This allows maintenance to be scheduled proactively and efficiently - even before there are visible anomalies.
The difference? CBM responds to anomalies, while PdM predicts when they will occur.
Collecting data is just the beginning. The NeuronSensors app from El-Watch provides tools to turn this data into actionable insights:
Example: setting thresholds
A motor normally generates vibrations between 2.8g and 4.5g and temperatures between 60°C and 80°C. Threshold values can be set as follows:
| Parameter | Normal range | Alarm limit low | Alarm limit high |
| Vibrations (g) | 2,8 - 4,5 | < 2,4g | > 4,9g |
| Temperature (°C) | 60 - 80 | < 55°C | > 85°C |
If these limits are exceeded, the app generates an alert and a maintenance action is initiated.
Machine learning for error detection
In practice, fault detection is often complex. Healthy and faulty states can be very similar in terms of data. The NeuronSensors app helps users to:
New features such as HTTP POST notifications make integration with external systems easy - such as dashboards, MES solutions or a CMMS (Computerized Maintenance Management System). Multiple notification methods can be bundled into one group so that notifications are managed efficiently.
PdM in practice: forecasting based on data
Predictive Maintenance requires sufficient historical data to make reliable forecasts. As more sensor data becomes available and models are trained with larger data sets, the accuracy of predictions increases.
PdM thus means:
Ready for the next step after PdM? From predicting to responding automatically
Predictive Maintenance helps predict failures and proactively schedule maintenance. But what if a system not only predicts, but responds independently - without operator intervention?
That is exactly what Neuron Actuators enable. These will be linked to sensors and feed automatic actions off as soon as a preset condition is reached. Consider:
This technology takes maintenance to the next level: from data-driven forecasting to autonomous process control. Systems not only monitor, they take immediate action. This reduces response time, increases safety and reduces reliance on manual intervention.
Neuron Actuators are thus a logical next step to PdM - for organizations looking to expand their maintenance strategy to include direct, automated response.
Want to discover how you can use smart sensors and predictive insights to improve your maintenance strategy? Or are you curious about how to prevent downtime and better align your maintenance plan with the actual condition of your machines?
Let's get into the conversation. During a free online demo, we'll show you how to use the NeuronSensors app and Predictive Maintenance:
Sensor Partners helps companies with this - both as a technology partner and as an advisor. You are not alone - we think along, look along and help you to convert data into concrete actions. This is how you lift your maintenance strategy to a higher level.
Easily schedule a no-obligation demo at a time that suits you best:
https://calendly.com/jeroen-sensor/predictive-maintenance?month=2025-10
Yes, you can.The NeuronSensors app supports integration with external systems via HTTP POST-requests. This means that notifications (alerts) can be sent directly to a URL, for example to:
In addition, multiple notification methods can be bundled into one group, giving you central control over e-mail addresses and other notification channels - without having to customize each line separately.
In short:the app is designed with flexibility in mind and fits well into existing IT and OT environments.
Yes, integration is quite possible.The IoT sensors used in the NeuronSensors solution are designed to be wireless and modular. They measure parameters such as:
These sensors can be easily added to existing machines and plants without requiring major infrastructure modifications. With Plug & Play functionality and wireless communication, no cabling is required, which speeds and simplifies integration with existing systems.
In addition, the sensors can interact with existing signals or systems via Neuron Actuators, which automatically respond to preset conditions - for example, turning off a machine when overheating or activating a fan when humidity is too high.
In short:the IoT sensors are designed to integrate flexibly into existing production environments, even if other sensors or automation are already in place.
Not necessarily.The sensors are designed asPlug & Play: wireless, no wiring, and easy to install. For advanced applications such as setting alerts or training algorithms in the NeuronSensors app, some explanation or guidance may be helpful, but the basic functionality is approachable.
Yes, absolutely.The IoT sensors used in the NeuronSensors solution are specifically designed for industrial applications. They are:
These features make them ideal for use in harsh industrial environments where reliability and durability are crucial.
Very low maintenance.Because they are wireless and contain few moving parts, maintenance is minimal. The sensors require little to no calibration in standard applications.
The batteries of El-Watch Neuron sensors last up to 10 years.
This is possible thanks to:
Long battery life means minimal maintenance requirements and low Total Cost of Ownership (TCO), even in environments where cabling is inconvenient or undesirable.
Yes. Especially with complex machines, we offer IoT-sensors a lot of value. By monitoring multiple parameters simultaneously (such as vibration, temperature and power consumption), anomalies can be detected early - even if they are not immediately apparent.
If a sensor fails, it becomes visible in the NeuronSensors-app by running out of data or generating an error message. This allows you to take action quickly. The sensors are also easy to replace.
Neuron sensors are designed for fast and flexible mounting in industrial environments. Multiple mounting options are available:
The cost depends on the number of sensors, the desired functionality (such as algorithms or integrations), and the scale of the application. Because the system is modular, you can start small and expand later.
Surprisingly simple and fast.Thanks to the wireless setup and user-friendly app, the sensors can often be operational within hours - without wiring or complex installation procedures
Through the predictive Maintenance system, your machines will be optimally utilized, extending the life of the equipment. No expensive & premature replacements (as with periodic and preventive maintenance) of parts, but through Just-in-time maintenance waste of parts is avoided. This reduces the need for frequent replacement and associated waste from obsolete machines, which is beneficial to the environment.
Machinery malfunctions can sometimes lead to leaks or other forms of environmental damage, such as the release of pollutants or contamination of water sources. By continuously monitoring your facilities, leaks or other anomalies are noticed immediately.... By setting alerts via email, text message or push notifications you are immediately alerted to dangerous situations so you can take appropriate action.
From data to insight: NeuronSensors app
Collecting data is just the beginning. The NeuronSensors app from El-Watch provides tools to turn this data into actionable insights:
Example: setting thresholds
A motor normally generates vibrations between 2.8g and 4.5g and temperatures between 60°C and 80°C. Threshold values can be set as follows:
| Parameter | Normal range | Alarm limit low | Alarm limit high |
| Vibrations (g) | 2,8 - 4,5 | < 2,4g | > 4,9g |
| Temperature (°C) | 60 - 80 | < 55°C | > 85°C |
If these limits are exceeded, the app generates an alert and a maintenance action is initiated.
