1. THE CONTINUOUS DIGITALIZATION OF THE MANUFACTURING MARKET INVOLVES THE ADOPTION OF TECHNOLOGIES SUCH AS AI, BIG DATA, IOT AND MES, JUST TO NAME A FEW. WHAT KIND OF SUPPORT CAN WE AT ENGINEERING PROVIDE TO THIS MARKET?

At Engineering, we support companies in their transformation journey toward an intelligent and connected factory, where technologies such as Artificial Intelligence, Internet of Things, Big Data, MES (Manufacturing Execution System) and PLM (Product Lifecycle Management) become drivers of competitiveness and efficiency, enabling the transformation of production processes, optimization of efficiency and improvement of competitiveness.

Each of these technologies contributes in a specific way to the evolution of the Smart Factory: AI enables the automation of complex processes and improves product quality; IoT provides a large amount of data which, thanks to Big Data, can be used for performance monitoring, process optimization and predictive maintenance; finally, MES monitors production in real time, ensuring operational efficiency across the entire value chain.

In this context, Cloud is also an enabling technology that makes it possible to integrate machines and systems, ensuring scalability, interoperability and real-time data access. Thanks to hybrid and multi-cloud models, IT and OT environments can be securely connected and advanced solutions such as Digital Twin, AI and collaborative platforms can be supported.

Engineering’s contribution to Digital Manufacturing is based on a strategic vision and an end-to-end approach to digital transformation capable of integrating processes, technologies and ecosystems.

We can turn data into value through Analytics, Artificial Intelligence and Digital Twin, and protect the industrial future with Cybersecurity solutions dedicated to the OT/IT world - all while leveraging research ecosystems, partnerships and specialized skills.

In this sense, Engineering positions itself as a key partner to guide companies toward more efficient, connected and sustainable manufacturing.

3. THIS DIGITALIZATION PUSH ALSO AFFECTS AREAS THAT UNTIL RECENTLY WERE CONSIDERED SUPPORT FUNCTIONS, SUCH AS PROCUREMENT. AUTOMATING THE ENTIRE PURCHASING CYCLE BRINGS STRATEGIC ADVANTAGES TO MANUFACTURING COMPANIES. IN YOUR VIEW, WHAT ARE THE MOST IMPORTANT?

Digital procurement is now one of the pillars of industrial transformation because it enables a function traditionally seen as support to evolve into a true strategic lever for business.

Automation and digitalization of the entire purchasing cycle first bring greater visibility and control over spending, suppliers and performance thanks to integrated real-time data. This is accompanied by a significant increase in operational efficiency, with automated processes that reduce time, errors and administrative costs.

Another benefit is stronger supplier collaboration through digital platforms and transparent workflows, as well as the ability to make data-driven decisions supported by analytics, AI and predictive models to manage risks and opportunities. Finally, two fundamental aspects should not be overlooked: sustainability and compliance, enabled by digital tracking of materials, suppliers and ESG impacts, and supply chain agility and resilience, with faster and more flexible management of demand, procurement and critical issues.

In short, digital procurement unlocks value, accelerates productivity and strengthens the competitiveness of manufacturing companies.

5. FOR SMART FACTORIES AS WELL, AI IS A KEY ELEMENT FOR OPTIMIZING AND STREAMLINING PRODUCTION PROCESSES. WHAT ARE THE FUTURE SCENARIOS?

In Smart Factories, Artificial Intelligence is already a transformation driver, but in the coming years its role will become even more strategic and pervasive.

Among future scenarios, factories will progressively evolve toward increasingly autonomous systems capable of self-adjusting production parameters in real time thanks to AI. Machines will communicate with each other (Industrial IoT + AI) and make data-driven decisions to reduce waste, downtime and defects.

Intelligent Digital Twins will emerge, virtual replicas of plants and processes capable of simulating scenarios and optimizing production before events occur in the real world.

Predictive maintenance will evolve into prescriptive maintenance, where AI will suggest and autonomously schedule the most effective interventions. AI will also support operators with decision-support systems and augmented reality for real-time assistance.

A central role will be played by monitoring and optimizing energy consumption of machinery and plants, contributing concretely to sustainability and carbon-neutrality goals.

All data generated across production, logistics and distribution will ultimately converge into connected digital ecosystems, enabling integrated and more efficient supply chain management.