Age management in the context of Industry 4.0 and beyond

Abstract

Abstract Keeping workers active and productive for a longer time is one of the key societal challenges of developed economies. Older workers have accumulated experiences and knowledge during their working lifetime, but due to declining functional capacities, many of them will not be able to work until the increased retirement age. Contemporary technological solutions supporting human-machine interactions such as smart working environment, production cells, exoskeletons, and others, in the context of Industry 4.0 technologies enable workers to stay productive longer. In the present study, we use a multiple decrement model. In the numerical example, we apply the model to the European industrial workforce. We modeled transitions among different productivity states of industrial workers, ranging from a potential employee to workforce exit, through retirement or death. The presented study shows the importance of appropriate age management practice applications that have the potential to substantially prolong the work-life of industrial workers in the European Union. The demographic model presented, allows measuring the influence that technological solutions in the context of Industry 4.0 have on the workers’ entrance and exits. The model shows how leveraging the accumulated workers’ knowledge and experience of older workers and automation of physically demanding tasks can not only improve the productivity of industrial systems but also decrease the costs of ill-health related expenditures.