EcoPRISM

Electrochemical polishing plays a critical role in achieving high‑precision surface finishes across various industries. However, the traditional approach often relies on conservative maintenance cycles, with fixed‑interval replacements of electrolytes to ensure quality and equipment reliability. This can lead to premature waste, increased operational costs, and avoidable environmental impact.

EcoPrism introduces a data‑driven layer of intelligence to polishing systems by combining real‑time sensor data, AI‑based predictions, and dynamic risk management. The solution monitors variables like temperature, conductivity and humidity, and uses predictive models to anticipate when the electrolyte condition may compromise the process. These predictions are mapped onto a digital Bowtie risk diagram that enables automated actions, such as alerts, fluid renewal recommendations, or system interventions—reducing downtime and ensuring consistent quality.

Impact
- Up to 20 % reduction in CO₂ emissions, equivalent to ~27 tonnes/year.
- Extension of electrolyte life by up to 30–40 %, reducing energy and material consumption.
- Reduction in incinerated waste due to optimised use of polishing fluids.

Scalable to multiple models of polishing equipment and adaptable across sectors with similar surface treatment needs.

Supported by ACCIÓ - Generalitat de Catalunya (project id ACE105/23/000157), EcoPrism helps shift polishing operations from routine-based maintenance to smart, evidence-driven decision making. This approach not only supports more sustainable industrial practices, but also improves process reliability and traceability—laying the foundation for greener, more efficient production in high-value sectors.