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.

How can predictive monitoring be applied in the food industry?

Technology is playing an increasingly important role. Predictive monitoring is one of the innovations that has profoundly transformed the food industry. 

This approach uses sensors, real-time data, and advanced analytics to predict equipment failures, optimize maintenance, and improve operational efficiency.

This article will explore how to apply predictive monitoring in food industries, discussing the benefits, challenges, and best practices for implementing this technology effectively.

Main challenges in industrial food plants

Maintenance in industrial food plants faces several crucial challenges to guarantee the continuity of operations and the quality of products. Some of the main ones include:

Risk Management

Risk management is a crucial obstacle in maintaining industrial facilities in the food sector. By their nature, operations involve inherent risks, making it essential to implement rigorous safety measures to safeguard equipment integrity and workers’ protection.

One strategy for tackling this issue is establishing a solid safety program, including a thorough risk assessment, identifying potential hazards, drawing up a standard operating procedure (SOP), and periodic staff training. In addition, predictive monitoring in the food industry is essential to mitigate the risk of failures and accidents.

Asset management

Asset management represents a substantial challenge in the maintenance of industrial facilities. Preserving the functional state of equipment and machinery is fundamental to ensuring their proper performance over time. However, asset management is a complex task that requires thorough planning and efficient execution.

One strategy to overcome this challenge involves adopting a data-driven approach, which entails collecting data related to equipment and machines to monitor their performance and identify potential problems at an early stage.

Availability of resources

The availability of resources is a third major challenge in the maintenance of industrial facilities. Maintenance requires a wide range of resources, including workforce, equipment, tools, and materials. However, ensuring these resources are readily available when needed can be challenging.

An effective strategy for tackling this challenge involves developing a detailed maintenance plan and efficiently allocating resources.  Ensuring that the necessary resources are available before maintenance execution is essential

Online predictive monitoring is the key to increasing plant performance.

Predictive monitoring in the food industry is a maintenance technique that uses sensors and analysis to predict failures in industrial equipment before they occur. This helps to: 

  • Avoid unplanned downtime;
  • Reduce damage to equipment;
  • Optimize the useful life of machines; 
  • Reduce energy costs;
  • Ensure the health and safety of employees;
  • Minimize environmental impacts.

Based on the analysis, ultrasound, and thermography results, periodic monitoring aims to reduce problems and increase the useful life of equipment. 

This approach allows for creating a targeted action plan to restore optimal equipment performance and increase your plant’s performance.

Why carry out online monitoring in the food industry?

By understanding maintenance models, it is possible to see the gains that can be made in the food industry through management based on planning, emphasizing predictive and preventive actions. These benefits include

  • More excellent continuity on the production line: by adopting predictive monitoring in the food industry, the company can significantly reduce the number of unscheduled stoppages on its production line;
  • Planned interventions: maintenance interventions are conducted in a planned manner without affecting ongoing production;
  • Increased equipment useful life: predictive maintenance helps to extend the lifespan of equipment, reducing the need for frequent replacements and saving resources.

In addition to these benefits, it is important to highlight another significant advantage. When maintenance management is based on predictive actions, corrective procedures become more precise because they are carried out according to prior planning.

The maintenance team is adequately prepared with the appropriate use of tools and protective clothing. It can handle the critical elements of the equipment with care, avoiding any direct contact with production.

How online predictive monitoring is carried out in plants

Online predictive monitoring in industrial plants is an essential strategy for efficient equipment maintenance and ensuring continuity of operations. It is based on advanced techniques that make it possible to identify problems before they cause unplanned downtime.

Use of online sensors

One of the bases of online predictive monitoring is the sensors installed in the plant’s strategic equipment. These sensors are chosen in advance by the technical team and the maintenance manager, taking into account the critical points of each machine. The great advantage is that these sensors are wireless, which means they are installed on several machines without complex cabling.

These sensors collect a range of data, such as vibration, temperature, pressure, and oil consumption. This information is sent to a central database that gathers data on the monitored equipment’s performance.

Implementing platforms for data monitoring

With the data collected by the sensors, it is possible to create a monitoring platform that is accessed remotely. This platform can be viewed on various devices, such as computers, tablets, and smartphones, giving maintenance managers flexibility.

When any anomaly is detected, even the slightest vibration, the platform sends an alert to the maintenance manager. This allows the technical team to act proactively, planning corrective actions before a serious fault occurs.

How SEMEQ can help with predictive monitoring in the food industry

SEMEQ is a company specializing in advanced predictive monitoring solutions, with expertise in meeting the specific needs of the food industry. Our innovative approach and cutting-edge technologies are designed to optimize equipment maintenance and ensure maximum operational efficiency in food processing facilities.

SEMEQ sensors

Our state-of-the-art sensors are designed to meet the highest standards of quality and reliability. They are ideal for the food industry, where precision and early detection of anomalies are essential. Wireless sensors monitor real-time vibration, temperature, pressure, humidity, and other critical parameters.


The My SEMEQ platform answers the need for real-time data monitoring and management. 

Maintenance managers in the food industry, with access to this platform, monitor the performance of their equipment remotely, receive instant alerts about any problems detected by the sensors, and access valuable information for informed decision-making.

If you are looking for reliable and customized predictive monitoring solutions for the food industry, SEMEQ is ready to help. 

Contact us

Contact us today to discuss your specific needs and find out how our sensors and platform can improve the efficiency and reliability of your maintenance operations.

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Smart sensors in Industry 4.0: learn how they remodeled predictive monitoring

Many American industries are undergoing a digital transformation, with the implementation of technologies such as artificial intelligence, the Internet of Things (IoT), advanced robotics, and cloud computing. These technologies are helping companies to optimize their operations, improve productivity, and create new business models and revenue streams.

In predictive monitoring in industries, one of the most innovative technologies in Industry 4.0 is smart sensors, which can generate a significant volume of data and constantly monitor the equipment.

Using this technology in industrial plants makes the machines maintain high performance throughout their use, which leads to a highly productive park and competitive advantage for the company.

In this article, learn more about the role of smart sensors in Industry 4.0 and its benefits in industrial parks.

Evolution of predictive monitoring and Industry 4.0

With the concept of predictive maintenance in the mid-1970s, software development allowed better planning, control, and monitoring of maintenance services.

However, despite these advances, the lack of interaction between the engineering, maintenance, and operation areas prevented the best results. Therefore, premature failure rates were still high.

From the 2000s on, with the consolidation of maintenance engineering activities, failure analysis was established to improve equipment performance.

In this context, predictive maintenance started to be increasingly used in the so-called Industry 4.0 – concept used for the first time in 2011, by the German government, in its quest to promote the computerization of manufacturing and data integration.

Industry 4.0 and the Internet of Things (IoT)

Also called the fourth industrial revolution, Industry 4.0 is characterized by intelligent technologies such as Artificial Intelligence, Machine Learning, Robotics, and Analytics based on big data. 

With these resources, it became possible for much greater interaction between machines, which gained greater integration capacity and autonomy. Thus, with the Internet of Things, devices are monitored through smart online sensors, allowing maintenance to be carried out more consistently and in the shortest possible time to predict and avoid unwanted occurrences.

In turn, Big Data resources enable the management of a large amount of data, contributing to the fact that machine maintenance decisions can be made before real problems occur.

Since then, thanks to the development of new technologies, predictive maintenance has been improving, indicating equipment failures with increasing accuracy and richness of detail.

Understand how smart sensors have changed the predictive market. 

The predictive monitoring of machines was done on-site until some time ago, which required the presence of technicians in factories to collect data. For this, a cable attached a sensor to the end of the equipment. The problem is that this process was much more laborious and expensive and therefore was usually only done on a monthly basis.

With smart sensors, predictive maintenance eliminates the need for in-person inspections. Data collection is done online and automatically, without disassembling and reassembling machines to determine if they are running well.

The sensors connected to the machines generate data that is captured and transmitted via the internet. This information is then analyzed to predict maintenance needs and limit the time this equipment will remain idle.

Benefits of using sensors for industries

* More accurate and frequent remote monitoring, which enables greater predictability of failures and avoids unnecessary repairs;

* Previously determines the need for maintenance, eliminating the need to disassemble the machines for inspections;

* Avoids problems that may generate the need for corrective maintenance, which is more complex and expensive;

* Decreased machine downtime, ensuring production continuity and increasing efficiency and safety on the production line;

* Increased useful life of equipment parts, reducing the need to stock spare parts;

*Generating a large amount of data can be combined to indicate the right moment to carry out predictive maintenance, increasing decision-making agility.

Applications of smart sensors in Industry 4.0

The use of wireless sensors in predictive maintenance enables the detection of wear and bearing defects, misalignments, imbalances, looseness, and other deficiencies that lead to machine failures and unexpected stops in the production line. This service can be applied in engines, electronic and power systems, boilers, steam system components, and transformers, among other equipment.

Industries from the most diverse sectors can benefit from this monitoring, even in dangerous places with difficult access.

What are the main types of smart sensors used in industry?

* Vibration: sees mechanical failures by analyzing the vibration of the equipment, such as unbalance, lousy bearing, or coupling.

* Temperature/Humidity measures the equipment’s temperature and humidity.

* Oil: analyzes the oil/lubricant viscosity present in the equipment.

* Ultrasound: Monitors leakage of compressed air, steam, and vacuum, detecting failures in bearings, valves, and electrical substations and saving energy.

Get to know the smart sensor we use in SEMEQ. 

The SEMEQ online vibration smart sensor can detect numerous potential electrical and mechanical failure modes. By analyzing temperature, vibration, electrical current, and other process variables, it is able to cover 100% of the potential failure modes in electric motors.

Besides, SEMEQ’s wireless sensors have high sensitivity, one of the most reliable in the market for detecting minimal vibrations indicative of potential failures.

This happens because we maintain an internal Research & Development department to produce sensors with the most advanced technologies in the market. Thus, we can guarantee efficient and reliable sensors for our customers.

SEMEQ wireless sensor features

  • 10kHZ sensitivity – detects bearing and gear failures.
  • Durable battery for up to three (3) years and replaceable.
  • No need to discard the sensor when the battery runs out.
  • 3G/4G connection and independent operation.
  • Triggers and variable charges.

Transform your industrial park: talk to our consultants.

Semeq has nearly 30 years of existence and has extensive expertise in monitoring wireless predictive maintenance in many industrial segments and small, medium, and large plants.

We are present in 40 countries and have more than 500 plants monitored with our technology. We have offices in North America, South America, Asia, and Europe.

Your company can also benefit from the effects of Industry 4.0 and the use of smart sensors in predictive monitoring.

Count on us to help you optimize production processes, reduce equipment failures, and increase plant performance.

Contact us now!