Adapting Virtual Training Systems for Industrial Procedures to the Needs of Older People Integration of older employees into the workforce is critical for a successful manufacturing industry due to demographic change. However, technological developments to create more flexible manufacturing environments are leading to increasingly complex machinery that has to be operated by an aging workforce. Virtual training systems prepare operators for the interaction with industrial machines. Current virtual training systems do not address the perceptive and cognitive abilities of older users to enable a satisfying and efficient training. This article develops adaptations of the visualization and the interaction techniques of a virtual training system to address the abilities of older operators. The results of a betweensubjects study indicate that the adaptations improve the subjective perception of the training system and decrease the training time. The paper concludes that adaptive training systems can support the participation of diverse user groups in the manufacturing industry by providing more effective and satisfying training.

Online Training and Monitoring of Robot Tasks through Virtual Reality Currently, the implementation of virtual, augmented and mixed realitiesbased solutions is one of the megatrends in the Industrial Automation domain. In this context, Virtual Reality (VR) permits the development of virtual environments that can be used for different purposes, such as designing, monitoring andor training industrial machinery. Moreover, the access to such environments can be remote, facilitating the interaction of humans with cyber models of realworld systems without the need of being at the system facilities. This article presents a virtual environment that has been developed within VR technologies not only for training and monitoring robot tasks but also to be done at robot operation runtime within an online mode. In this manner, the user of the presented environment is able to train and monitor de tasks at the same time that the robot is operating. The research work is validated within the online training and monitoring tasks of an ABB IRB 14000 industrial robot.