AI-CUBE · Project

AI Adoption Roadmap for 10 Heavy Process Industries — From Cement to Steel

manufacturingIdeaTRL 2Thin data (2/5)

Imagine you run a ceramics or steel plant and you keep hearing "use AI" but nobody tells you where to start or what actually works. AI-CUBE surveyed 10 heavy industries — cement, chemicals, metals, water, paper, and more — to map out exactly which AI and big data tools are already being used, which ones are ready to deploy, and where the biggest gaps remain. They built a consensus-based roadmap with guidelines so plant managers can skip the hype and focus on what delivers real results. Think of it as a GPS for AI adoption in heavy industry.

By the numbers

SPIRE industrial sectors analyzed (cement, ceramics, chemicals, engineering, minerals and ores, non-ferrous metals, steel, water, pulp & paper, refineries)

dimensions in the AI-BD conceptual matrix (technologies, application areas, sectors)

consortium partners across 3 countries

total project deliverables

The business problem

What needed solving

Heavy process industries like cement, ceramics, chemicals, and steel are under pressure to adopt AI and big data, but there is no clear map of which technologies are mature, which ones work for which processes, and what has already been proven in neighboring sectors. Companies risk investing in the wrong AI tools or missing opportunities that competitors in adjacent industries have already captured.

The solution

What was built

AI-CUBE produced an AI and big data roadmap for 10 process industry sectors, a 3-dimensional conceptual matrix mapping technologies to applications and sectors, implementation guidelines, a gap analysis identifying cross-sector AI transfer opportunities, and a Business Model Game for strategic AI investment planning. Total of 17 deliverables were produced.

Audience

Who needs this

Digital transformation managers at cement, ceramics, or steel plants evaluating AI investmentsCTOs at chemical companies building AI adoption strategiesInnovation directors at industry associations (SPIRE sectors)Technology scouts at non-ferrous metals or water treatment companiesConsultancies advising process industries on Industry 4.0 roadmaps

Business applications

Who can put this to work

Ceramics and Glass Manufacturing

mid-size

Target: Ceramics producers looking to digitize quality control and process optimization

If you are a ceramics manufacturer dealing with inconsistent product quality or high energy costs — this project produced an AI adoption roadmap covering your exact sector with guidelines for implementation. It mapped which AI and sensor technologies are mature enough to deploy and which ones are still experimental, across 10 process industry sectors. The Business Model Game tool can help your team evaluate AI investment scenarios before committing budget.

Chemicals and Petrochemicals

enterprise

Target: Chemical plants seeking to optimize processes with predictive analytics

If you are a chemical company struggling to identify which AI tools are worth the investment for process optimization — this project analyzed AI maturity levels across all SPIRE sectors including chemicals and refineries. The roadmap identifies exploitable connections between sectors, meaning a solution proven in steel might solve your chemical process problem. The gap analysis pinpoints where AI is underused in your specific operations.

Non-Ferrous Metals and Mining

enterprise

Target: Metal smelters and processors evaluating sensor and AI integration

If you are a non-ferrous metals processor wondering which sensors and AI algorithms your competitors are already using — this project consulted with industry associations across 10 sectors to benchmark current AI penetration. The 3-dimensional matrix maps AI technologies against specific application areas in your sector. The implementation guidelines give you a practical starting point rather than generic AI promises.

Frequently asked

Quick answers

How much would it cost to access the AI-CUBE roadmap and guidelines?

AI-CUBE was a publicly funded Coordination and Support Action (CSA), so its roadmap, guidelines, and consultation results are publicly available through the project website (ai-cube.eu) and EU dissemination channels. There is no licensing fee for the roadmap itself. Implementation costs would depend on which AI technologies you choose to adopt based on the roadmap findings.

Can these recommendations be applied at industrial scale in my plant?

The roadmap was specifically designed for industrial-scale process industries across 10 SPIRE sectors including cement, ceramics, chemicals, steel, non-ferrous metals, water, and refineries. Industry associations and company representatives validated the recommendations for feasibility. However, the project delivered guidance documents — not ready-to-install software.

Is there any IP or licensing involved with the tools developed?

As a CSA, AI-CUBE produced roadmaps, gap analyses, and a Business Model Game tool — not patentable technology. The Business Model Game was developed as a strategic planning tool. Based on available project data, outputs from CSA projects are typically openly accessible.

Which specific AI technologies does the roadmap recommend for my sector?

The project mapped AI and big data technologies against application areas across 10 process industry sectors using a 3-dimensional conceptual matrix. It assessed maturity levels and identified cross-sector opportunities where a technology proven in one sector could be transferred to another. The specific recommendations vary by sector and application area.

How current are these findings given the project ended in early 2023?

The project ran from September 2020 to February 2023, covering the pre-ChatGPT era of industrial AI. The foundational analysis of sensor applicability, process optimization use cases, and sector-specific gaps remains relevant, but the AI technology landscape has evolved significantly since. The cross-sector opportunity mapping is still valuable as those industrial process challenges have not changed.

Who validated the roadmap recommendations?

The consortium of 5 partners across 3 countries (Germany, Spain, Italy) included 2 industry partners and conducted a Multi-Actor Multi-Criteria analysis with broad industry consultation. Industrial associations across all SPIRE sectors validated the consolidated roadmap for solution feasibility and benefits.

Consortium

Who built it

The AI-CUBE consortium is compact — 5 partners from 3 countries (Germany, Spain, Italy) with a 40% industry ratio. The coordinator is PNO Innovation SRL, an Italian private company (not an SME), which is a well-known EU project consultancy. With 2 industry partners, 1 university, and 2 research organizations, the consortium is oriented toward analysis and consultation rather than technology development, which aligns with its CSA nature. Only 1 SME participates. For a business looking to engage, PNO Innovation's role as coordinator suggests strong connections to the broader EU innovation ecosystem, but the lack of major industrial end-users in the consortium means the roadmap's validation came through external consultation rather than internal testing.

PNO INNOVATION SRLCoordinator · IT
FUNDACION ZARAGOZA LOGISTICS CENTERparticipant · ES
CONSIGLIO NAZIONALE DELLE RICERCHEparticipant · IT
IRIS TECHNOLOGY SOLUTIONS, SOCIEDAD LIMITADAparticipant · ES

How to reach the team

PNO Innovation SRL (Italy) — contact through project website or SciTransfer for introduction

Order a report on this consortium See PNO INNOVATION SRL profile →

Next steps

Talk to the team behind this work.

Want to know which AI-CUBE recommendations apply to your specific plant? SciTransfer can map their sector roadmap to your operations and connect you with the right experts.

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