This study presents the iterative design, development, and evaluation of a Virtual Reality (VR)-based training system for industrial production, addressing high employee turnover, training inefficiencies, and operational errors. The system was developed using the Design Science Research Methodology (DSRM) to integrate real-time feedback, interactive learning paths, and adaptive training. The evaluation with industry experts and production staff demonstrated high user engagement, improved knowledge retention, and practical applicability. However, challenges remain regarding interface intuitiveness and spatial presence. Unlike prior studies focusing on general VR training, this research proposes a structured approach for industrial environments, prioritizing usability, cognitive load management, and scalability. Future research should explore Artificial Intelligence (AI)-driven personalization, multi-user collaboration, and enhanced haptic feedback to optimize adaptability. This work contributes to VR training design theory and offers structured guidelines for industry adoption.