Predictive Maintenance Education & Training System: An alliance for boosting the European Innovation in Predictive Maintenance through entrepreneurial cooperation, education, and training

ongoing

Predictive Maintenance (PM) is a critical element for the optimization of primary resources used in the economy and on fundamental infrastructure systems (while mitigating climate change also). Currently, both industry, academia and VET trainings lack coprehensive PM curricula. The objectives of PreMETS are to introduce an alliance for boosting the European Innovation in Predictive Maintenance through entrepreneurial cooperation, education, and training for the development of a coherent digital platform that covers all aspects of the PM process. In this context, the general objectives of PreMETS (linked to the goals of the call) are: OBJ1: Develop an innovative cross-disciplinary and cross-sectoral PM education toolkit (ECTS and ECVET compliant) hat will be used to train 1000+ PM learners (students, VET learners) and workforce during the project implementation. OBJ2: Develop a cutting edge toolkit for trainers in the field of PM (higher education, vocational education, corporate) that would be uptaken by 250+ trainers during the project implementation. OBJ3: Develop a micro-credential certification framework for PM-related micro-courses that would enable at least 500 learners (students, VET learners, workforce) to receive certification for skill-recognition OBJ4: Develop a cross-disciplinary platform that would include the PM education toolkit, the package for PM trainers, the micro-credential certification system, an embedded lifecycle analysis process calculation service (that can be used by learners to test various resilient PM strategies and assess their environmental, social and economic impacts) and a virtual space for blended Teaching Factories deployment. OBJ5: Pilot the training courses and the platform via innovative work-based learning blended apprenticeship secondments where mixed learners from academia, VET and industry (under the moderation of trainers and experts) will experiment the gained know-how in cyber-physical industrial settings.