IIoT transforms industries and predictive maintenance

December 14, 2021

We live in a new era focused on analysis, process digitalization, and consequently mass data processing (big data).

The truth is that Industry 4.0 has arrived to revolutionize the most diverse areas of the economy, and this has transformed scenarios in terms of digitalization, distribution, and data processing, including in the industry.

This quiet revolution has generated significant growth for those who have invested in innovation and the implementation of the IoT (Internet of Things) that connects machines, systems, and operators by aggregating information interactivity in network-connected devices, transforming operations, and facilitating predictive maintenance techniques.

In this way, the control of the equipment is done in an integrated and autonomous way, and can pave the way to the future implementation of artificial intelligence and machine learning.

IIoT for the Industry

A subcategory of the Internet of Things (IoT), which includes applications targeted for clients such as usable devices, smart home technology, and autonomous cars, is the Industrial Internet of Things (IIoT), which for its part refers to devices, machines, and the infrastructure of integrated systems for the industry. 

In fact, IIoT aims at generating greater operational efficiency by developing completely new business models. This subcategory works to increase the safety and efficiency of production facilities. Communication between devices can take place via Bluetooth, Ethernet, Wifi, and radio frequency.

Check out examples of how IIoT technology can be applied in the most diverse industrial sectors:


The truth is that this is the sector that has applied the IIoT the most, as equipment and machines can be autonomously monitored and predict potential problems, which means less downtime, more efficient maintenance and production overall.

Supply Chain

Warehouses are now managed by radio frequency sensors and tags (RFiD), making it possible to map supplies before stocks run out, considerably reducing waste and also the need for replenishment.

Facility Management

The management of industrial facilities and their applications should be simpler and more secure with the arrival of IIoT, with device-based climate controls and the monitoring of entry and exit points of operations.


With devices that monitor equipment remotely and wirelessly, centralizing data in the cloud, that notify those responsible for maintaining the machines by signaling the status of failures and critical points, the trend is that this will take us towards Artificial Intelligence, which in the near future will be able to signal the causes of failure, allowing technicians to act more quickly and efficiently.

IIoT Concepts and Tools

Some concepts guide the applicability of technologies to industrial reality. They are:

Digital Twins

This practice aims to create a computer model based on data collected from a particular piece of equipment, design, or machine. With this concept, industries can use the data to simulate tests prior to any manufacturing or maintenance, reducing time and increasing efficiency of action.

Electronic Logging Device (ELD)

Integrated sensors that monitor speed, travel time, and how often drivers apply the brakes, for example, help save fuel, improve driver safety, and reduce idle resources. If the driver makes a dangerous maneuver or has been driving for too long, he will be alerted, and the controller will be notified. This technology can replace the paper records that drivers had to fill out every day.

Intelligent Edge

The place where data is generated, analyzed, interpreted, and treated, aimed at intelligent monitoring, sustainability, and traceability of industrial products and equipment.

Radio Frequency Identification (RFID)

A system involving tags and readers, as a smarter version of barcode technology. The readers identify RFID tags using radio waves, meaning that the tags can be read by multiple readers at once and at a greater distance than traditional repeaters. RFID tags allow you to easily track and monitor the things they are attached to.

Sensors, Cameras and Systems

A system that involves a machine or component with sensors that collect and transmit data, and then analyze and store them in a database. This database then provides comparison points for events as they occur. The system eliminates unnecessary maintenance and increases the probability of avoiding failures. Another reality is the cameras and other systems that monitor the industrial production process, evaluating the performance of the equipment. 

IIoT and Maintenance Techniques

Some techniques used to measure if the machines are in perfect condition or if they have any unusual critical factor, which highlights the need for a (planned corrective) maintenance intervention and that can be linked to an Asset Monitoring Center. Check some of them out: 

Vibration Analysis

An older method that allows the detection of potential failures such as unbalance, misalignment, shaft warping and wear in gears and bearings. Also, poor machine or internal component fixation, abrasion, backlash, bearing wear, electrical problems, and more.

Oil Analysis

Used to detect wear on moving parts in machinery and the presence of contaminating substances. There are four types of oil analysis: physical-chemical analysis, contamination analysis, spectrometry, and ferrography.


In the quantification and analysis of the morphology of wear particles (swarf) found in lubricant samples are determined, among other things, the types of wear, contaminants, and lubricant performance.


Non-destructive technique for temperature measurement and observation of heat distribution from infrared radiation.


The method in which internal discontinuities are detected by the way sound waves propagate through a machinery component.

Statistical Time Series Analysis

The use of dataloggers with temperature and acceleration sensors allows you to know the behavioral signature of a machine, identifying its tendency towards health or failure. Learn about the advantages of vibration monitoring here.

While spectral analysis generates a high-resolution snapshot, statistical time-series analysis generates a low-resolution movie, which, because of its data richness, allows the creation of a true machine medical record.

All these techniques are used to detect possible defects that can impede the operation of the equipment. Dynamox acts directly with vibration and temperature sensors that, when applied to the equipment, can identify failures and the need for preventive or corrective maintenance, still in early stages.

The Dynamox Solution has the ability to identify the early failure trend in monitored machines and components, as well as perform spectral analysis, with modern wireless technology.

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