7 benefits of wireless sensors in predictive maintenance

Industry 4.0 combines various digital innovations and technologies, such as the Internet of Things and artificial intelligence, which can revolutionize industrial operations.

Today, the wireless sensor is one of the most widely used technologies in predictive maintenance. This device provides more accurate results on the state of the equipment since it has a very high sensitivity for detecting anomalous minimum vibrations. It can also be monitored online, even in industrial parks far from major centers.

If you still doubt the effectiveness of these devices, here are 7 benefits of wireless sensors in predictive maintenance.

1. Greater efficiency in production processes

Through process simplification and enhanced data accessibility, wireless sensors empower industrial parks to optimize productivity and minimize resource utilization on the factory floor.

According to Senai’s research, Industry 4.0’s digital technologies can increase the productivity of micro, small, and medium-sized companies by an average of 22%.

Industry 4.0, with its reliance on wireless sensors, significantly reduces maintenance and labor costs, allowing manufacturers to enhance productivity, quality, and revenue growth.

2. Safer, data-based decision-making

The benefits of the wireless sensor in predictive monitoring are significant. Using artificial intelligence technologies, a large volume of data can be collected to generate valuable insights for the operation of industrial parks.

Some examples are the performance of each piece of equipment, the useful life, the availability and reliability of each industrial plant, and the production potential of each park.

This data is collected using big data & analytics resources and read by professionals in predictive monitoring.

3. Savings on repairs and downtime

One of the main benefits of the wireless sensor in predictive maintenance is the regular checking of assets in advance, thus avoiding unexpected problems with repair maintenance.

In addition, because it is a wireless sensor, it is possible to save on cabling and labor for data capture since the process is automated.

4. Ease of monitoring hard-to-reach locations

One challenge before Industry 4.0 was carrying out predictive monitoring in places that needed to be made accessible or far from the center. This is because data collection was done manually, and the logistics of professionals at each piece of factory equipment had to be considered.

Today, wireless sensors monitor equipment in dangerous environments and places that are difficult to access or far from urban centers since the data is sent directly to the monitoring company’s database and analyzed by professionals with expertise.

5. Much more frequent monitoring

The wireless sensor for predictive maintenance allows monitoring to be done remotely much more frequently than traditional predictive maintenance, which used to be done once or twice a month, depending on the park’s size and the company.

In the traditional method, asset maintenance in the field requires the periodic dispatch of technical teams, which involves high costs in terms of time, resources, logistical complexity, and a low collection rate.

6. Avoids losses from downtime costs

According to a study by Emaint, factories lose between 5% and 20% of their production capacity due to downtime. This happens when equipment is unavailable, forming bottlenecks in the production line.

Around 82% of companies have experienced unplanned downtime in the last three years, according to a survey by Aberdeen Research. The report says unplanned downtime can cost a company up to $260,000 per hour.

The good news is that using predictive maintenance and artificial intelligence resources in data analysis helps prevent these machine failures and avoid unplanned downtime. Research by McKinsey shows that predictive maintenance reduces machine downtime by 30-50% and increases the useful life of assets by 20-40%.

7. Faster responses to problems

When a predetermined limit for machine operation is reached, an alert is generated immediately, and analysts have instant access to machine condition data. They can then conduct precise analyses through asset management software, in real-time and from anywhere.”

Avoid unforeseen events! Have wireless sensors monitoring your equipment 24/7

Your industrial park can also benefit from Industry 4.0 technologies in predictive maintenance. SEMEQ has know-how and experience in this area and uses traditional and predictive maintenance techniques. We currently have one of the most technological and sensitive sensors on the market, capable of identifying even minimal vibrations in each piece of equipment.

SEMEQ wireless sensor

  • 10kHZ sensitivity – detects bearing and gear failures;
  • Up to 3 years of battery life and replaceable;
  • No need to discard the sensor when the battery runs out;
  • 3G/4G connection and independent operation;
  • Triggers and variable load.

Our company has over 300 employees and a portfolio of more than 500 monitored factories in 45 countries.

Contact us to have your industrial park fully monitored.

Wireless sensors for online monitoring: why they are the best option on the market? 

Wireless online monitoring sensors have changed how machine data is collected, transported, and analyzed.

They have been used by companies that want to have more effective control of the situation and performance of their machines since it is possible to obtain data collected with high frequency and precision by being done remotely.

This type of sensor is especially interesting for large industrial parks, which have continuous or intermittent production, or those located in difficult access points or far from large centers, thus avoiding installing large and wired networks.

In this article, we will show the benefits of using wireless sensors for online monitoring and why it has been the best choice for those who want to maintain high performance in industrial plants.

Technology in predictive maintenance: software’s help has changed how we do the monitoring. 

Predictive maintenance began in the 1940s in the US air force. In the 1970s, the use of offline data collectors increased, but today we know that they demand much manpower.

Traditional predictive maintenance consisted of making collections with data collectors, also called datalogs, through a single sensor attached to the end of the equipment from a cable. It was a portable instrument that required the presence of a person to collect data at the factory, usually on a monthly basis.

With Industry 4.0, as of mid-2015, the wireless sensor system for online monitoring began to emerge; at that time, the installation involved investments in infrastructure, with large cable networks to transmit the information.

The quality of remote monitoring of the machines has improved significantly since the cadence of collection, which was monthly, can now be 700 times greater.

In this way, online inspection became much more accessible. It began to be carried out in bulk, always with the same objective: to guarantee the proper functioning and availability of the machines.

Nowadays, remote monitoring with wireless sensors has virtually no limitation in its expansion, changing the amount of monitored equipment from hundreds to thousands. One of Semeq’s customers will install around 50,000 sensors in the next few years in its manufacturing plants.

Benefits of using wireless sensors for online monitoring

Wireless networks dramatically reduce the costs of installing, maintaining, and performing asset monitoring systems.

Check out some benefits of using wireless sensors for online monitoring.

Association of vibration sensors with analysis of electrical circuits.

Vibration analysis and electric motor circuit analysis sensors cover 100% of faults; 67% of failures are covered by vibration analysis, and 33% by circuit analysis of electric motors.

Prescriptive insights 

The most modern approaches to preventive maintenance use machine learning and AI to discover valuable insights from data. With these capabilities, sensor solutions identify potential failures and predict how long a machine or process may have before it fails.

It is important to note that artificial intelligence and machine learning systems need much historical data to learn.

Thus, unlike other predictive monitoring companies, Semeq has the largest database on the market, around 70TB, allowing the application of AI and ML to be more accurate and application development to be faster. 

Companies that do not have a robust database will have to wait for machines to break down numerous times before they can “train” their AI systems, exposing their equipment to failure.

Spectral Analysis

When capturing frequencies, they are transmitted in grouped (mixed) form. In Semeq’s algorithms, they are classified mathematically, which allows interpretation of the various failure modes leading to accurate determination of potential failures.

Our algorithms also rely on Artificial Intelligence and Machine Learning based on our extensive databases, as mentioned above.

Prescriptive analytics report

MySemeq, our report delivery platform, allows viewing the diagnoses of all predictive techniques and performing results management in a single place.

Integration with the ERP allows for automatic service orders with fast and consistent feedback. It also improves the follow-up of work orders and ensures the execution of reports.

Wireless sensors for online monitoring: online vibration and temperature analysis.

Due to technologies such as Bluetooth, many more wireless sensors can now be connected to machines. These wireless sensors for predictive monitoring service capture critical data online that is transmitted to a central cloud server via a wireless gateway.

Our online vibration sensors detect numerous potential failure modes in equipment. By associating vibration and temperature analysis, they broaden the detection possibilities, significantly increasing system reliability.

Learn about some advantages of our wireless sensors for online monitoring.

Early-stage failure detection

When a limit determined by our algorithms is reached, an alert is generated, and analysts have access to the machines’ condition data. In addition, SEMEQ’s algorithms allow forecasts leading to the estimation of the time available for the execution of the maintenance.

Quick Setup

Wireless sensors for online monitoring can be installed very quickly, without wires, compared to traditional wired monitoring. After all, the energy for its operation comes from replaceable batteries.

Some companies offer sensors with non-replaceable batteries, leading to the need to completely replace the sensors, which ends up being financially unsustainable. For example, imagine a plant with thousands of sensors discarded every time the batteries run out; ultimately, the budget becomes impractical for many companies.

With a configurable and scalable system, you can add hundreds of wireless sensors and configure each individually.

Flexibility in applications

The most diverse equipment benefits from online monitoring. The predictive maintenance service can be applied to engines, power systems, boilers, steam system components, gearboxes, bearings, etc.

Find out how we carry out online monitoring of machines in industrial plants.

SEMEQ cares about machine health, while other companies care about disease. SEMEQ’s significant role is to bring this predictive and preventive culture, allowing potential machine breakdowns to be identified early enough for interventions to be more effective.

Installation of sensors for data collection

With the online system, sending a person to collect data is unnecessary, as it is done automatically. With these remote monitoring features, around 720 data collections are made monthly, a much more significant number than the offline collection, usually done only once or twice a month. In this way, the chances of a failure occurring are drastically reduced.

Results Management

Semeq’s wireless sensors for predictive service and our team collect data, and our labs analyze these algorithms. Then, our engineers manage the results, presenting the best machine maintenance solutions.


Our predictive service and remote monitoring of plants identify gaps in industrial parks, suggesting actions and corrections that should be prioritized.

Choosing the most suitable technique depends on the type of machine and the needs of each company. Our team of professionals with expertise in predictive maintenance performs this analysis.

We are a reference in online predictive maintenance monitoring.

SEMEQ has 300 employees and over 500 monitored factories, with a presence in 40 countries. To meet customer needs, our predictive monitoring company has teams to advise on installing and improving maintenance models distributed worldwide. In contrast, the analysis team is concentrated in our control rooms.

Talk to our consultants and avoid surprises at your industrial plant!