#IndustrialAutomation

For decades, industrial maintenance relied on two straightforward principles: repair when something fails or perform scheduled inspections. Today, Artificial Intelligence is transforming this paradigm. Thanks to real-time data analysis, robots can anticipate failures before they occur, optimise their performance, and extend their operational lifespan. What’s more, this technology isn’t limited to new robots: it can also be applied to refurbished industrial robots, combining sustainability with operational intelligence.
Predictive maintenance powered by AI is based on gathering sensor data—such as vibration, temperature, electrical consumption, and motor torque—and analysing it with algorithms that detect anomalous patterns. If a shaft overheats or a gearbox vibrates slightly outside its normal range, the system issues an alert before the issue causes a breakdown. This enables interventions to be planned at the ideal time, reducing costs and avoiding unexpected downtime.
Leading manufacturers like ABB, KUKA, FANUC, and Yaskawa have developed platforms compatible even with refurbished robots equipped with modern controllers. For instance, a refurbished ABB robot with an IRC5 system can connect to the ABB Ability™ cloud platform for remote monitoring and mechanical health analytics. KUKA provides solutions compatible with KUKA Connect, enabling performance data logging and automatic maintenance scheduling. Even FANUC and Yaskawa offer APIs that, when paired with additional sensors, transform refurbished robots into intelligent units capable of generating predictive reports.
Integrating AI into refurbished robots doesn’t just extend their lifespan; it also maximises return on investment. By detecting faults early, costly repairs are minimised and production stoppages—which can cost thousands of euros per hour—are avoided. Furthermore, the accumulated data enables engineers to improve trajectory programming, optimise energy use, and compare performance between different cells.
A real-world example comes from an automotive plant in Italy, where three refurbished KUKA KR 60 robots fitted with vibration sensors and a local AI system detected micro-wear in gearboxes within six months, preventing a complete line stoppage. In another case, a Polish electronics factory using a refurbished ABB IRB 4600 with predictive diagnostics software reduced maintenance times by 25% and extended its expected operational cycle by over two years.
These experiences show that refurbished robots can not only match but even surpass the efficiency of new ones when combined with artificial intelligence and advanced monitoring. The key lies in integration: strategically placed sensors, secure connectivity, and continuous analysis.
From a sustainability perspective, this evolution also has a positive environmental impact. Extending a robot’s lifespan by five years means avoiding the production of a new one, saving thousands of kilos in materials and energy. Properly applied AI makes refurbished robotics a model for the digital circular economy: reused technology with an updated brain.
At URC, we integrate predictive maintenance solutions and smart connectivity into refurbished ABB, KUKA, FANUC, and Yaskawa robots, ensuring precision, reliability, and long service life. We combine engineering and data so each robot works more intelligently, efficiently, and sustainably.