In 2025, industrial competitiveness hinges on more than just product quality. What truly makes the difference are a host of other factors: the ability to slash time to market, to reconfigure production lines on demand, and to handle micro-lots and just-in-time orders with both flexibility and speed. The challenge is clear: produce well, quickly, custom-tailored, and continuously. But how?
Challenges On the Road to the Smart Factory
Companies recognize that meeting market demands requires pervasive digitalization of production processes. By 2025—and following several rounds of incentives—this imperative extends even to SMEs, which are increasingly part of integrated, dynamic, and hyper-competitive supply chains.
Although we’ve been speaking for years about Industry 5.0 and the smart factory (or smart manufacturing), certain structural barriers still impede full-scale transformation. The toughest obstacle is embedding operational data at the core of decision-making. Many production environments remain heterogeneous, with machinery from different eras, varied communication protocols, and non-standardized data sources. Add to this a shortage of skills capable of turning raw data into actionable insights, and it’s clear there’s still a long way to go.
There’s no shortage of talk, rightly, about intelligence in production processes and AI as a strategic lever for competitiveness, with investments forecast to grow by 45% annually through 2030. Yet in many settings, the conditions for AI to deliver its full potential simply aren’t there. Without a reliable, structured, contextualized, and accessible data ecosystem, even the most advanced algorithms struggle. Effective transformation must rest on solid foundations—first and foremost, the MES.
The MES as a Pillar of Factory 5.0
The Manufacturing Execution System (MES) is an indispensable element on the path to sustainable, data-driven manufacturing. Originally designed to monitor, supervise, and synchronize real-time production execution, the MES has evolved into a strategic connector between the physical world of equipment and the domain of management systems. From this interconnection, a synergistic data ecosystem can emerge.
In industrial environments with heterogeneous machinery, the MES provides the framework for collecting, normalizing, and—crucially—enhancing information. It sits between the shop floor (the machines, sensors, and production lines) and enterprise systems, enabling bidirectional communication between the two faces of the business: operations and corporate management.
But the MES does more than connect, it optimizes factory processes. Through a robust MES, you can:
- Dynamically schedule production, adapting tasks to current shop-floor conditions.
- Monitor real-time performance of equipment and lines, quickly detecting inefficiencies or anomalies.
- Optimize use of material resources, preventing stock outages and enabling smarter, sometimes fully automated supply flows.
- Record real-time consumption and trigger alerts for any deviations.
- Manage workforce allocation, forming the most suitable teams for each line or operation based on skills and availability.
- Ensure full production transparency, meeting traceability requirements in many sectors.
- Gather data for quality control, enabling a proactive approach to non-conformity management.
The MES thus becomes an enabler of automation, sustainability, and productivity. Without it, talk of a “smart factory” risks amounting to little more than a slogan.
Not Just Productivity: MES as an Enabler of Innovation
For decades, the MES has been a cornerstone of industrial digitalization. Companies adopted it to boost operational efficiency, improve finished-product quality, gain process transparency, and increase productivity. These remain the fundamental pillars on which the robustness of any production facility is measured: where a well-managed MES exists, you’ll find reliable KPIs.
Today, however, a new perspective is emerging: the MES not only brings efficiency and control but also becomes the launchpad for building a competitive edge through innovation—innovation that in 2025 is increasingly taking the form of artificial intelligence.
AI promises to revolutionize manufacturing by offering enterprises multiple opportunities, including:
- Predicting problems before they occur, the classic case of predictive maintenance.
- Real-time optimization of production parameters, adjusting operational sequences based on sensor data analysis.
- Supporting operators with GenAI-based virtual assistants, capable of answering technical queries and guiding them through complex setups.
As mentioned, none of these capabilities can materialize without a solid foundation of reliable, coherent, and accessible data. Here, the MES transforms from an execution system into an intelligent platform. Today’s advanced solutions integrate machine learning algorithms for continuous production-flow optimization and generative AI features for automatically drafting operational reports or providing virtual assistance to operators.
Alternatively—or alongside—data gathered and managed by the MES can be fed into external AI platforms, yielding custom predictive models, digital twins, bespoke solutions, or dashboards beyond merely depicting production status to delivering contextual recommendations for improvement.
It is thus the presence of a well-configured, actively used MES that makes a data-driven innovation journey both realistic and sustainable, aligning production processes with ever-more demanding market requirements.
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