Predictive Service and Maintenance

The PRE-SEMA (Predictive Service and Maintenance) project harnesses advanced analytics and machine learning to improve the forecasting and scheduling of service appointments within the technical home appliances sector. By analyzing several years of historical data on installation, service, and maintenance appointments, PRE-SEMA identifies critical patterns that enable precise predictions for both planned and unplanned service needs. The project’s objective is to enhance operational efficiency by forecasting unexpected service requirements, such as appliance malfunctions and new installations, while simultaneously improving adherence to scheduled maintenance. Through sophisticated machine learning techniques, PRE-SEMA extracts key data features to develop predictive models, supporting proactive resource allocation. This approach addresses the challenges of high service demand and limited technician availability, reducing customer dissatisfaction from rescheduled appointments and minimizing appliance downtime. Ultimately, the project aims to provide an innovative decision-support tool that integrates smoothly with existing scheduling processes, ensuring consistent service quality across regions and elevating customer satisfaction.