Through the information collected by devices and sensors, with edge analytics we collect data from machinery, speeding up the process of creating datasets and decentralizing smart analysis activities. This solution allows to reduce the data evaluation times, allowing to obtain early warnings from the signals coming from the field.

We optimize logistics through A.I., for a correct distribution of products and an efficient supply of raw materials from suppliers, reducing lead times and improving the efficiency of the entire process.

We apply AI to the digital twin of a machine, an entire production line or an entire factory. In this way, we can not only simulate its operation but also predict short and long term problems and evaluate in advance the best action to take to improve the process.

We help companies to improve the quality level of the product going beyond traditional objectives. We integrate artificial intelligence algorithms to detect product quality in a granular way, avoiding quality decay. We use computer vision techniques to support and make quality control activities more efficient at all stages of the production process.

The identification of bottlenecks within the production process allows to improve it by reducing production times and costs. We use artificial intelligence and process mining techniques to identify and highlight these elements and support managers in continuous improvement.

We improve the accuracy of demand forecasts, with positive impacts on the design and construction phases of a product. In this way it is possible to optimize the planning, procurement and use of resources, in relation to raw materials and the actual production process.

We make production robots intelligent, dedicated to phases such as assembly, welding and painting. With the addition of artificial intelligence, robots are able to monitor and improve their performance and accuracy, managing to extend their life and reducing the production of waste.

We make the forecasts of raw material price trends more accurate, with immediate impacts on procurement costs and helping to improve the quality of the final product. We use artificial intelligence algorithms by integrating external data to evaluate the correlation of the right factors affecting price volatility.

We use the most modern machine learning techniques to optimize warehouse planning, a fundamental activity for maximizing product sales and reducing unsold or expired products.

Through artificial intelligence we can improve the failure predictions of products and production machinery, drastically reducing product maintenance costs and minimizing downtime in production.