Data Value Management – Prediction and Reduction of Micro-Stops Data Value Management  Sector: Industry Business Case The challenge is to develop a system capable of detecting the primary causes that provoke a large number of micro-stops in the different production lines of a company, in order to reduce their occurrence. Additionally, a secondary system is

HUPI – Energy Consumption Prediction and Behavioural Modelling of an Entity HUPI  Sector: Industry Business Case Automatic energy demand prediction for the next period of time (12 months?), with a precise level of granularity: it predicts the level of energy consumption that each specific customer or building will need in the next day/week/month. Objectives Estimate

Inzu Group – Federated Artificial Intelligence for Predictive Maintenance on Bridges (FAI4CIM) Inzu Group  Sector: Industry Business Case Currently, there is no cost-effective method for automatically detecting structural issues in bridges (10% in Europe, 30% in the USA). Inspection (procedure for assessing the condition of an infrastructure in use) was based on subjective criteria. The

ITP Aero – ML-Based Turning Process Capability Improvement ITP Aero  Sector: Industry Business Case The goal is to enhance the capability indices of the turning process (Cp, Cpk) through the application of ML techniques. Models based on data from the process itself will be used to make the process self-adaptive. Objectives Improve process capability (reduction

ITP Aero – Improving Melting Curves for Lost Wax Processes ITP Aero  Sector: Industry Business Case The goal is to reduce defects in the final product by modifying the melting curves of the material ingots using data-driven models. Objectives Improve product quality. Use case Identify all parameters of the melting curves relevant to product quality.

ITP Aero – Improving the Broaching Process Using ML ITP Aero  Sector: Industry Business Case It seeks to improve both the capacity (variability reduction) and quality of broached products at ITP Aero through data-driven modelling. Objectives Process capability improvement (reduction of dimensional variability) and quality improvement (reduction of allowances) through the use of ML-based correctors

Lantek – Forescrap: Prediction Service for Scrap Generated in Sheet Metal Cutting Processes Lantek  Sector: Industry Business Case In metal part manufacturing processes involving cutting, the generation of scrap or unused material is closely tied to how efficiently the parts are arranged on the sheet metal. In order to address this challenge, the Forescrap system

Mondragon Innovation | Humanity at work – Prediction of Polymer Creep Moduli using Machine Learning Mondragon Innovation | Humanity at work  Sector: Industry Business Case Polymers gradually lose their stiffness over time when subjected to a constant load, a phenomenon known as creep. Tests to measure this phenomenon are very time-consuming and expensive, meaning the