AI Industrial Analytics and Digital Twin

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Dettagli azienda

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Funzionalità

•Data integration and guided onboarding. A structured onboarding layer maps, aligns and contextualises the product, machine, process, maintenance and quality data the company already holds, reading from existing sources through database connections, APIs or file exchange.
•Factory-specific digital twin. The core of the platform. It links products, operating modes, machine behaviour, maintenance events and quality outcomes into one model that represents expected behaviour under comparable conditions, giving every downstream analysis its operational context.
•Cross-functional analytics layer. Analytics models detect anomalies, recurring failure patterns, degradation and quality risk, and estimate remaining useful life and time to next intervention. Optimisation and what-if logic compare alternative actions and rank them by expected impact on selected KPIs.
•Explainability and GenAI-supported guidance. The platform shows which factors contribute to risk, the expected operational impact and the recommended next action, and translates model results into plain-language guidance for operators, technicians, engineers and quality teams.
•Human-in-the-loop decision support. Role-specific interfaces present alerts, ranked contributing factors, scenario comparisons and recommended actions. Users can confirm, correct or enrich outputs with domain knowledge. Operational decisions and machine-parameter changes remain under human control.

Descrizione del software AI Industrial Analytics and Digital Twin

smartFAB is an Italian deep-tech SME developing AI-powered industrial analytics and digital-twin solutions that transform production, quality, machine and planning data into faster, explainable operational decisions for SMEs and multinational manufacturers.

smartFAB acts as the manufacturing intelligence layer above existing factory systems. It connects fragmented operational data into factory-specific digital twins, detects risks and recurring losses, explains root causes and KPI impact, simulates options where relevant, and translates results into ranked, human-reviewable actions for operators, technicians, engineers and managers.

The platform builds on manufacturers’ existing data infrastructure, connecting data across silos and applying modular analytics for anomaly detection, root-cause analysis, quality risk, tool life, energy waste, scheduling and process performance. Human-in-the-loop validation keeps factory experts in control. Outputs are explainable, role-specific decision views showing what is changing, why it matters, which KPI or process is affected, what action should be reviewed and who should own the next step.

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