Grupo Lanit – Customer churn prediction Grupo Lanit Sector: Mobility Business Case The company needs to anticipate behaviours likely to be abandoned by its customers. Objectives Anticipate the risk of customer leakage or loss and take preventive measures to retain customers, such as offering them personalised offerings Optimise the resources and budget allocated to marketing […]
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Ayesa – Cardiac risk prediction Ayesa Sector: Health Business Case Improve the triage of patients with non-traumatic pain in the A&E department (ischemic heart disease) to reduce the number of false positives without increasing false negatives. Objectives Correctly classify ischemic heart disease in A&E with emphasis on minimising false negatives that mean that someone may
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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
BCAM – Probabilistic Predictions for Energy Management Based on Continuous Learning BCAM Sector: Energy Business Case Obtaining accurate energy demand predictions is difficult due to the continuous changes in consumption patterns (concept drift). Accurate forecasts can optimise the planning of energy production as well as its distribution, resulting in efficient generation and minimising the risk
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LIS Data Solutions – Demand forecasting and suggestion for procurement LIS Data Solutions Sector: Generalist Business Case Warehouse inventory management based on sales forecasting. Once the forecast is done, knowing the supplier’s LTsr, the level of service we want to deliver to the customer and the pending orders to be received, we come up with
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Ayesa – Anomaly detection in cybersecurity attacks in industrial environments using quantum algorithms. Ayesa Sector: ICT Business Case Detection of anomalous behaviour in industrial safety systems as critical systems. How can we reduce training times and volumes of current unsupervised systems? How can we reduce the detection latency of possible attacks by improving the sensitivity
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
Ceit – Automated disassembly system for recovery of critical materials Ceit Sector: Industry Business Case Robotic assembly tasks are well established in industry, but automated disassembly is not. There is a lack of automation in this process and it has been identified as one of the great environmental and technological challenges of the next decade.
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Mondragon Innovation | Humanity at work – Prediction of Home Delivery Activity (Last Mile Logistics) Mondragon Innovation | Humanity at work Sector: Commercial sector Business Case The number of orders to be delivered to customers’ homes is not homogeneous and fluctuates due to internal and external variables. Tailoring the sizing to the unique requirements of
Multiverse Computing – Hospital Clinic: q-VIGILANCE Multiverse Computing Sector: Energy Business Case The q-Vigilance project addresses the need to improve the prediction of symptom severity in patients using a quantum machine learning algorithm to overcome the limitations of the NEWS 2 model. This approach aims to provide faster and more accurate responses at Hospital Clinic
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