Smart retrofit solution for the industrial sector: sustainable digitalisation on legacy machines

This work presents a systematic methodology and a modular Smart Retrofit Architecture (SRA) to digitalise legacy machinery through interoperable hardware, software and a communication layer that enable data acquisition, analytics, and human-centred decision support. The approach was progressively refined through preliminary experiments, materialised in a dedicated toolkit (Smart Retrofit Toolkit, SRT), and subsequently applied in pilot implementations developed within the framework of the European AIDEAS project. It was first operationalised in the AIDEAS Smart Retrofitter (AI-SR) and validated on industrial and laboratory testbeds. At PAMA S.p.A., AI-SR was applied to large machine tools, demonstrating non-invasive sensing, real-time monitoring, AI-based analysis, and measurable operational and environmental improvements; scalability was verified on a second machine through rapid model transfer and a shared ontology. At D2 Technology, AI- SR was implemented on a testbench with a configurable database and a three-panel UI for monitoring, historical data analysis, and scenario simulation. Finally, at IKERLAN, a Real- Time Data Simulator digitally retrofitted a crank–slider testbench, streaming data for near- real-time condition assessment using statistical and AI models. Overall, the methodology, SRA, SRT and AI-SR demonstrate that smart retrofit provides an efficient and sustainable pathway to achieving Industry 4.0 and 5.0 functionalities without full equipment replacement.