At LACROIX plants, the “Smart Industry” development plan  is geared towards pragmatic objectives: industrial and energy performance.

Based on the accumulation of data in real time and the automation of repetitive tasks with no added value, the performance aspect of the Smart Industry is reflected in specific projects.

Real Time Monitoring, a fount of learning for artificial intelligence

Also known as real-time data monitoring, Real-Time Monitoring contributes to industrial performance improvements at our plants by identifying deviations in production performance.

Connecting all our production machines to an integrated information system that collects all production data in real time allows at the Electronics activity of LACROIX to generate the massive data.  Presently, connecting different production machines presents a veritable challenge due to the number of computing languages in use. The company is trying out the IoT platform Thingworx® to address this need. Gathering data makes it possible to subsequently automatically generate alerts and production reports.

But how do we then harness the power of this immense quantity of information?

Gaining the ability to capture all this production data is an essential step that comes before the final phase – allowing the machines to correct themselves through artificial intelligence. By analysing the “Machine Learning” and “Deep Learning” solutions available on the market, the Electronics activity of LACROIX is opening the door to a world brimming with potential.


Automate to achieve excellence

Component placing operations have already been heavily automated for years thanks to “Surface Mounted Devices” production lines. The production steps that follow however are generally manual.

With the goal of improving industrial performance in our factories, our “Smart Industry” team is studying the large-scale automation of the so-called “back-end” production steps. This refers to all production steps to be carried out on the electronic boards coming off the SMD production lines. Currently, “back-end” production tasks are primarily carried out by operators, including certain repetitive tasks that have little added value.


Automation of repetitive actions such as loading or unloading boards from racks, screwing, and bonding is under study at our factories by means of:

  • Robots set up in closed environments to optimise the speed and productivity of the function.
  • Experimentation with cobots also known as collaborative robots, a solution that is automated, flexible, and adaptable for several different types of manipulations on the same day.