The connectivity of industrial equipment represents a major challenge for companies looking to modernize their machine fleet and strengthen their competitiveness. Industrial IoT is radically transforming how manufacturing companies monitor their production assets. Whether you own recent machines with standard protocols or older equipment without native communication capabilities, IoT solutions now offer monitoring possibilities adapted to each configuration. This article explores different approaches to connecting your industrial devices and optimizing their real-time supervision, with a particular focus on using IoT sensors as a universal solution.
You may be wondering how to approach the connectivity of your heterogeneous machine fleet. The fundamental question to ask is: does your equipment have native communication capabilities?
Recent machines are often equipped with control systems that allow communication via standardized protocols. Among the most commonly used, we find OPC UA, an open and secure protocol compatible with many manufacturers, particularly Allen Bradley. The S7 protocol is dedicated to Siemens controllers, while FOCAS is mainly used for FANUC equipment. For machine tools and CNC systems, the MT-CONNECT standard is generally preferred. When these protocols are available, the most direct solution is to establish a connection via these existing interfaces. This generally allows access to a wide range of data with relatively simple implementation.
You've probably already noticed that the majority of industrial devices, especially those over 10 years old, don't have these standardized communication protocols. Does this mean you should give up integrating them into your monitoring system? Absolutely not!
The common element of all industrial equipment lies in their electrical signals. Regardless of the age of the equipment, it uses sensors and generates electrical signals (typically 24 volts) to operate. It's precisely this characteristic that opens the way to industrial IoT connectivity.
Equipment monitoring through IoT sensors represents a major advancement in industrial digitalization, creating a true bridge between existing installations and new Industry 4.0 technologies.
Industrial IoT gateways operate on a simple yet powerful principle: intercepting existing electrical signals from machines to transmit them to the cloud. These devices connect directly to the sensors or control signals of equipment without disrupting their normal operation.
In practice, an industrial IoT box is placed in parallel with existing circuits and captures critical information such as operating/stoppage states, production cycles, alerts and errors, as well as various operating parameters.
Using IoT sensors to modernize your equipment offers several significant advantages. Their universality allows them to be adapted to devices that are 5, 10, 20, or even 40 years old, while their non-intrusive installation doesn't require deep modification of existing installations. The deployment of these sensors is generally faster than integrating new control systems, and their scalability offers the possibility of progressively extending the system to the entire machine fleet. Additionally, real-time transmission of data to the cloud facilitates immediate analysis of equipment performance.
To maximize the efficiency of your monitoring system, a hybrid approach is often recommended. Let's review the key steps to succeed in your machine connectivity project.
Industrial equipment monitoring should no longer be limited by the age or technology of machines. As we've seen, the pragmatic approach consists of evaluating each piece of equipment individually and choosing the most suitable connectivity method: standard protocols for recent machines and IoT sensors for older equipment.
The fundamental principle to remember is that "if there's electricity in the machine, we can connect it." This approach democratizes access to Industry 4.0 for all companies, regardless of the age of their machine fleet, and paves the way for significant improvements in terms of productivity and quality.
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