INDUSTRY SECTOR

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ENSURE BOTH THE SUCCESS OF NEW CONSTRUCTIONS AND THE IMPROVEMENT OF EXISTING INFRASTRUCTURES.

UNDERSTAND YOUR ENVIRONMENT BETTER AND ACT AGILELY TO MEET THE NEEDS OF INDUSTRY TODAY AND TOMORROW.

Energy

The use of data offers a transition to the industry sector. It helps to understand
and control energy consumption, accelerate the production of renewable energy
and optimize transport and maintenance operations.

Construction

The development of high-performance data repositories is an essential component
of a data centrics strategy. One can derive an advantage in the increase of
safety on construction sites, skills development.

Railway

The railway sector is already committed to digital transformation. The advantages offered
to this evolution are diverse. Thus, modeling and data can optimize network rehabilitation,
to measure preventive maintenance, etc.

BECOME A PIONEER THANKS TO DATA

Deployment monitoring

The data will allow you to optimize operational management. By analyzing the different data: energy, external, technical... Thus, being supported throughout the building life cycle is paramount. As a result, you will be guided to get the most out of your data with a better decision-making and better priority management.

Anticipation of breakdowns and preventive maintenance of machines

The data can be used by companies to anticipate machine failures by examining sensor data and applying machine learning algorithms. These forecasts are useful for optimally planning maintenance, avoiding unplanned shutdowns and extending the life of equipment.

Quality monitoring

In the management of non-conformities, it is necessary to identify the stages of the process which are most at risk of causing defects. It is necessary to analyze and interpret data to find ways to improve processes. To do this, we examine each stage of production and study the measurements recorded in the logs of the sensors that follow the production, looking for anomalies in the semi-finished products.

Demand and stock forecast

It is possible to predict future demand and adjust their stock levels accordingly. Thanks to machine learning, which takes into account different factors such as market trends, seasons and special events, demand forecasts can be used to improve the efficiency of business planning and logistics.