Data, the new raw material for industry
The industry is no longer transformed solely by modernizing equipment or automating production lines. Today, data is becoming a central lever of competitiveness, and constitutes a new raw material which, once correctly captured, structured and analyzed, makes it possible to fundamentally rethink industrial performance.
Each industrial machine now generates a considerable amount of information. A single production line can produce several tens of terabytes of data per day. However, due to a lack of suitable architecture and clear governance, the vast majority of this data remains unusable or simply ignored.
At the house of GYS, French industrial group specializing in the design and manufacture of welding equipment and battery chargers, each charging or welding cycle, each electrical drift, each diagnostic signal potentially constitutes usable information. You still have to be able to capture it, structure it and interpret it. It is at this stage that proprietary software and artificial intelligence intervene, not as a miracle solution, but as tools capable of transforming raw signals into operational anticipations.
Data, a long under-exploited industrial asset
For years, machine data was stored without an overall strategy. They were sometimes used for one-off analyses, but rarely to support a long-term industrial vision. In many industrial IoT environments, only a marginal fraction of the data is actually analyzed. McKinsey cites the case of an oil platform where around 1% of sensor data is subject to in-depth examination.
At GYS, this observation led to a thorough overhaul of its industrial approach. In a group which manufactures nearly 2,000 machines per day and whose equipment is used in 132 countries, the challenge no longer consists only of designing and producing robust and efficient machines, but of developing proprietary software capable of transforming real use into usable knowledge. Behind each piece of data there is an operator, a technician, an engineer, and know-how accumulated over time. Data only has value when it extends human intelligence, instead of pretending to replace it. Understanding precisely how a machine behaves in the field, in industrial, climatic and cultural contexts sometimes very far from the ideal conditions of test benches, has thus become a major strategic issue.
“ Our machines already generate all the information necessary to understand their real state, their areas of weakness and their areas for improvement. The real challenge is no longer to produce data, but to structure it and use it intelligently to decide faster and better. », explains Bruno Bouygues, CEO of GYS.
Artificial intelligence: an accelerator, not a miracle solution
In this context, artificial intelligence appears to be a formidable accelerator, but certainly not a magic solution. Without clean, harmonized and contextualized data, AI can only produce limited results. On the other hand, when it is correctly integrated, it makes it possible to identify correlations invisible to the human eye, to anticipate breakdowns and to optimize the manufacturing and maintenance of machines.
The benefits are concrete. Reducing production breakdowns and predictive maintenance can reduce unplanned downtime, extend the lifespan of equipment and reduce overall maintenance costs. It transforms a curative logic into a preventive approach, driven by better understood data.
The often invisible obstacle of architecture
Another key issue lies in systems architecture and data sovereignty. The industry today suffers from extreme fragmentation of protocols and standards. Each manufacturer, each machine, each technological generation speaks its own language with its own dictionary. This heterogeneity greatly complicates the centralization and use of data.
Faced with this reality, GYS favors a pragmatic approach: local processing of data, security of flows and complete control of sensitive information stored in proprietary software. This in-house architecture makes it possible to reconcile operational performance, data security and industrial sovereignty.
Data as a new lever of industrial sovereignty
Controlling usage data is gradually becoming a strategic issue. The person who structures the data has a detailed understanding of the real functioning of the machine, its limits and its margins for optimization. The question of data localization remains sensitive. A report from the Swedish National Board of Trade indicates that around 85% of European companies transfer data outside the European Union via standard contractual clauses. Without specifically targeting industry, this figure illustrates the persistent dependence on extra-European infrastructure.
For GYS, designing the hardware, developing the embedded OS, building the analysis tools and maintaining control of the data is part of a long-term logic. This is a condition for guaranteeing technological compatibility over ten or twenty years, in an industrial environment where investment cycles are particularly long.
From predictive to prescriptive, a still partial course
Industrial tools were first descriptive, then predictive. The transition to prescriptive, that is to say automatic recommendation of actions, still remains limited. Industry 4.0 maturity indices show that a minority of manufacturers today reach these advanced levels.
In the most advanced configurations, machines learn not only from their own history, but also from that of thousands of devices operating in varied contexts. Each cycle enriches the overall knowledge base. However, this increase in power remains gradual and requires strong discipline in data management.
A new frontier of industrial competitiveness
When carried out with rigor and ambition, Industry 4.0 projects are no longer about experimentation but about economic survival. They allow you to drastically reduce downtime and increase labor productivity by 15-30%. The most advanced manufacturers in terms of artificial intelligence already attribute more than 10% of their EBIT to advanced analytics. It is no longer a technological promise, it is a measurable competitiveness differential.
Data is not everything, but without data, European industry is condemned to suffer. Depriving yourself of the intelligent exploitation of your machines means accepting a progressive loss of control, margins and sovereignty. Conversely, players capable of transforming their data into operational intelligence create a structural advance, often irreversible, which permanently redraws the industrial balance of power.
In a world where the costs of energy, capital and labor are increasing simultaneously, data is becoming one of the last internal levers of competitiveness. Those who delay activating it will not fall behind: they will simply exit the game.
While other continents are industrializing data at high speed, Europe is still hesitant on this subject. This hesitation is no longer neutral: it widens a competitiveness gap which becomes, quarter after quarter, more and more difficult to fill.
“ Structuring your data in your machines today means giving yourself the ability to decide and innovate more quickly tomorrow. It is a real dividing line between the industrialists who will control their destiny and those who will suffer it.» concludes Bruno Bouygues, CEO of GYS.
