Design of an integrated manufacturing system for CNC machine availability, energy measurement, and maintenance alerts through digital monitoring and operational management

This thesis presents the design and pilot deployment of an integrated digital system for a university CNC workshop, aimed at improving machine availability visibility, standardizing maintenance-related communication, and enabling structured data collection for performance analysis. The system combines three modules: the MA Dashboard for ON/OFF status management, QR Check & Alert (QR C&A) for guided pre-use checks and maintenance alerting, and an Energy Monitoring module for the acquisition and interpretation of machining energy signals. The core contribution is the creation of a shared information infrastructure where operational data are collected in consistent formats and stored in a unified repository, transforming day-to-day workshop activities into measurable evidence. This enables short-to-medium term improvements in laboratory efficiency and supports the setup of a framework to compute integrated KPIs, including cost visibility and sustainability indicators, with the student as the unit of analysis in a teaching environment. By making availability, maintenance events, and energy-related information comparable over time, the proposed approach provides a basis for better decisions on resource allocation, supervision effort, and learning-support activities, ultimately improving the quality and impact of hands-on training. Finally, the same architecture is designed to be extensible: with larger datasets and further integration, it can be adapted to an industrial setting to support company-level monitoring and decision-making.