Predictive Maintenance via Deep Tech Solutions for Environmental and Social Impacts in Manufacturing

The PreVEnT project addresses specific skill gaps in Predictive Maintenance (PM) using deep tech solutions. It aims to develop innovative, market-oriented educational resources for VET learners and trainers, who currently lack access to emerging PM curricula. The project supports the growing demand for PM professionals to improve infrastructure resilience, reduce resource use, and mitigate environmental and social impacts. The project targets key needs: - VET learners and employees require skills in advanced technologies like AI, machine learning, collaborative robotics and lifecycle analysis to enhance employability and job performance; - VET trainers need modern pedagogical strategies, digital tools and methods to reduce dropout rates, promote inclusion and deliver effective PM training; - Industries and VET providers seek micro-credential systems and dual education frameworks to better align training with labour market needs, while fostering sustainability.

The PreVEnT project aims to achieve the following objectives: O1: Develop a market-oriented PM education toolkit using deep tech solutions (e.g., AI, machine learning, collaborative robotics) to train over 200 VET learners and employees, improving their job performance and employability. O2: Create an innovative toolkit for VET trainers to enhance their capacity to deliver inclusive and effective PM education, reduce dropout rates, and empower learners to take ownership of their learning path. O3: Establish a micro-credential certification framework to provide formal recognition for PM-related skills, awarding at least 200 certifications and increasing employability by addressing workforce skill gaps. These objectives aim to improve VET education, align training with labour market demands, and promote sustainability through environmentally and socially impactful PM practices.

The PreVEnT project implemented the following key activities: - Project Management (WP1): Ensured coordination, monitoring and quality assurance across all activities; - Development of the Deep Tech in Predictive Maintenance Toolkit for VET Learners (WP2): Created a comprehensive toolkit with 4 modules (covering AI, machine learning, collaborative robotics, lifecycle analysis and sustainability), a resource hub with over 100 curated learning materials and a micro-credential certification framework. A total of 280 participants (target: 200) were trained through virtual pilots; - Trainer Toolkit for VET Educators (WP3): Developed 5 modules addressing digital skills, neuroscience strategies, inclusion and micro-credentials. A total of 115 (target: 100) VET trainers were trained through virtual pilots; - Work-Based Learning Pilots (WP4): Conducted 3 hybrid teaching factories where total of 195 participants (target: 150) solved industry-driven PM challenges using sustainable solutions; - Dissemination and Outreach (WP5): Organized 4 open days / workshops, created a project website, social media campaigns and policy recommendations to share results and engage stakeholders. These activities were designed to align VET education program.

The PreVEnT project delivered the following concrete outputs and results: 1. Deep Tech in Predictive Maintenance Toolkit for VET Learners: A comprehensive toolkit with 4 modules (EQF Level 5), including more than 200 slides, a 100-page booklet, 4 concept maps, 4 WebQuests, 4 videos, and a resource hub integrating 140 curated learning materials. 280 VET learners were trained, with 205 micro-credential certificates awarded. 2. Trainer Toolkit for VET Educators: 5 modules focusing on neuroscience strategies, inclusion, digital skills, and micro-credentials were developed. 115 VET trainers were trained, receiving 139 certifications (for various CU). 3. Work-Based Learning Pilots: Three hybrid teaching factories were conducted with 195 participants solving more than 15 industry-driven PM challenges using deep tech solutions, resulting in environmental and social improvements. 4. Dissemination and Outreach: A project website, 4 open-day /workshop events, newsletters, social media campaigns, and more than 7 policy recommendations (target: 4) ensured broad dissemination and stakeholder engagement. These outputs strengthened VET education, improved employability, and promoted sustainable and innovative practices in predictive maintenance.