Technologies and processes in this field

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Introduction and testing of semi-solid die casting technology (rheocasting) for zinc alloys in a hot chamber, with the aim of improving the aesthetic quality and mechanical properties of castings.

The development of an automated, digitised jeans packaging line aimed at making on-demand production sustainable and competitive in Western countries by encouraging reshoring.

The project aims to develop an automated and digital production line for the assembly of electronic products, optimizing productivity and reducing costs.

The project implemented for Fater Spa created a digital twin of the warehouse to validate technical solutions and optimize processes, supporting strategic decisions.

The project introduces innovation into machine design and development processes through the adoption of digital twin technology.

The Connected Infrastructure is the cornerstone of industrial digital transformation, enabling the collection and utilization of data from machines, sensors, and software. The digital backbone ensures a continuous flow of information between departments and plants, allowing for predictive analytics and faster decision-making. The use of Big Data Analytics transforms large volumes of data into actionable insights to improve quality, energy efficiency, and productivity. Industrial cybersecurity protects sensitive data from cyber threats, ensuring operational continuity. With this digital infrastructure, companies can reduce waste, anticipate failures, and make processes more sustainable.

Artificial Intelligence optimizes every stage of production, reducing costs and improving operational quality. In quality control, artificial vision systems and machine learning detect defects before they impact production. Predictive maintenance analyzes critical parameters to reduce machine downtime. Autonomous guided systems manage material handling with optimized routes. Advanced industrial data analysis improves planning, energy efficiency, and supply chain management. Indeed, AI for operator assistance provides support with intelligent chatbots and augmented reality, enhancing safety and efficiency.

The digital transformation of logistics and production enables intelligent control of the supply chain and production processes. Thanks to IoT and smart sensors, it is possible to collect real-time data to optimize transportation routes and inventory management. Cloud platforms and predictive analytics support dynamic planning, reducing operational costs. The process Digital Twin allows for the simulation of production scenarios and the identification of inefficiencies before they occur. This integrated approach enables more flexible, responsive production that can quickly adapt to market demands.

Quality 4.0 represents an evolution in industrial quality control, leveraging advanced digital technologies. Computer vision systems and AI monitor every stage of production, detecting anomalies before they become critical defects. Integration with IoT sensors ensures complete product traceability throughout the supply chain, enhancing the safety and reliability of supplies. Techniques such as X-ray tomography and other non-destructive inspection methods allow for the verification of internal quality without compromising component integrity. This approach reduces waste and rework, optimizing production processes.

The Intelligent Product and Process enables a new industrial paradigm, where products and machinery are connected and capable of exchanging information in real-time. Thanks to IoT and Smart Connected Products, companies can collect operational data, monitor product conditions, and improve predictive maintenance. Advanced process monitoring allows for the optimization of production and the reduction of waste, while servitization transforms business models, shifting from product sales to the provision of services based on actual use. These technologies enhance operational efficiency and promote more flexible and sustainable production.

Modern industry requires flexible and optimized production systems. Smart Manufacturing integrates advanced digital solutions to improve performance and efficiency. Cobots support operators in repetitive tasks, reducing errors and fatigue. 3D printing enables on-demand production and material optimization. Digital machine monitoring, thanks to IoT and AI, allows anomalies to be identified and consistent quality to be guaranteed. The digital twin of the process allows production scenarios to be simulated and informed decisions to be made. Thanks to these tools, production becomes more responsive, efficient, and sustainable.