IoT at the service of predictive maintenance

One of the major goals of effective maintenance is to reduce machine downtime as much as possible. To this end, the use of IoT in the service of predictive maintenance is a considerable asset, and one of the most important elements ofIndustry 4.0.

Predicting breakdowns before they occur makes it possible to carry out the necessary maintenance interventions at the chosen time and in a minimum of time. This implies adopting a 4.0 CMMS integrating IoT into its operation.

The advances made possible by this technology seem almost endless, and it is therefore important for industrial companies to have agile and scalable tools at the service of the constant improvement of their productivity and competitiveness.

IoT and maintenance

Industrial maintenance is far from being the only field concerned by IoT, but it benefits in particular.

What is IoT?

The IoT (Internet of Things, or Internet of Things), refers to the interconnection between the Internet and objects. In practice, it takes the form ofInternet-connected objects, whose physical existence is thus linked to a digital existence. The considerable quantity of data collected on these objects then makes it possible to improve their functioning and efficiency, but also to develop new knowledge. IoT is generally considered to be the Third evolution of the Internet.

For several years, theInternet of Things occupies an increasingly important place in industrial production. This development was made possible by the spread of optical fiber, Cloud computing, Big data or even SaaS software, but also by the appearance of sensors more and more varied and less and less expensive and, of course, by the explosion in the use of mobile devices.

The IoT thus makes it possible toimprove productivity in a large number of areas and to such an extent that it is estimated that it already has, and will have even more in the future, a significant impact on the GDP of the countries where it is used in industry.

How does the Internet of Things work in maintenance?

In practice, IoT allows, thanks to sensors, constantly monitor the operation of the machines through certain key parameters for detecting malfunctions and failures. Les vibrations of a machine are the most common parameter: the detection of abnormal vibrations in fact generally announces an upcoming failure.

The other parameters that the IoT allows you to track are, for example:

• The temperature Or the pressure of a machine,
• its consumption ofenergy,
• The rotation speed of a brooch.

Any unusual data transmitted by the sensors is collected and analyzed by the CMMS to which they are connected, and leads to maintenance intervention when necessary, before the failure occurs.

Moving from preventive to predictive maintenance thanks to IoT

The Internet of Things, combined with the latest generation of CMMS, allows companies to adopt a predictive maintenance strategy in order to optimize the productivity of their equipment.

From preventive maintenance to predictive maintenance

Preventive maintenance consists in intervening on machines at determined intervals or according to prescribed criteria. It aims to reduce the probability of equipment failure or degradation. This type of maintenance strategy is based on knowledge of similar machines and on feedback from experience.

La predictive maintenance, or predictive maintenance, allows you to move to another level of maintenance efficiency. It consists, according to the standard NF EN 13 306 X 60-319, to carry out maintenance operations “by following the forecasts extrapolated from the analysis and evaluation of significant parameters of the deterioration of the property, in particular thanks to sensors installed on the machines and connected.”

It thus becomes possible to predict the maintenance needs of each piece of equipment. based on data concerning him, and not by extrapolating from the operation of similar machines or based, with a certain margin of uncertainty, on experience. This avoids, for example, carrying out preventive maintenance interventions at regular intervals when they are not necessarily necessary.

Booming in recent years, predictive maintenance reduces maintenance costs by 10 to 40% and divides the number of failures by an average of two, According to a study by McKinsey.

CMMS 4.0, the essential ally of IoT for predictive maintenance

To be able to use IoT in industrial maintenance and therefore to set up a predictive maintenance strategy, the adoption of a last-generation CMMS, often called CMMS 4.0, is essential. This, based on the numerous data transmitted by the sensors installed on each machine and by using Big Data without which it could not process them, makes it possible to predict future equipment malfunctions with great precision.

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Thus, periods of downtime of machines and therefore of production, the need for spare parts or the schedules of maintenance teams can be organized more easily and with greater precision, and by greatly reducing the negative impact of interventions on factory productivity.

Technology that is constantly improving

The Internet of Things is constantly progressing, the sensors used being more and more efficient and less and less expensive. Some companies are thus beginning to design sensors that are “aware” of an operating state, for example, thanks to artificial intelligence.

But to take full advantage of these advances, it is necessary to be equipped with a CMMS that is also constantly evolving and adapting, like last-generation applications. These are very regularly updated and perfected by their teams of developers, based on the feedback of their users and on the needs they express.

IoT is therefore a great tool for optimizing industrial maintenance., by adopting a predictive maintenance strategy. Leaning against a agile 4.0 CMMS solution, it allows businesses to extend the life of machines while increasing productivity, today and tomorrow. In terms of maintenance, the joint use of IoT and the latest generation CMMS offers companies that adopt them sustainable guarantees in terms of competitiveness.