Abstract
The transformation process of manufacturing industry into a more digitalized world is a key challenge of the fourth industrial revolution. Advantages of new technologies must be used effectively, and therefore employees need to be prepared to deal with these new technologies and the complexity and speed that today's production entails. Worker assistance systems offer the possibility to simplify the interaction between humans and complex machines and to reinforce physical and cognitive skills of employees. Although worker assistance systems are available on the market, methods focusing on the systematic selection and associated classification of appropriate worker assistance systems for specific work tasks and worker types are missing. This work starts from a state of the art analysis of worker assistance systems in manufacturing and a review on existing selection and classification methodologies. Based on these results, the general worker in manufacturing, who can be seen as an indispensable resource, is analyzed and grouped in different operator types. Furthermore, their strengths and weaknesses are discussed. Subsequently, based on previously defined parameters, a novel and systematic selection methodology is introduced to analyze and evaluate the workplace, the employee, and the respective work task. An innovative algorithm enables a selection and ranking of potential useful worker assistance systems. Finally, some application examples of worker assistance systems are given to contribute to the existing body of knowledge and an applied case study gives further insights addressing the potential of worker assistance systems for a more inclusive manufacturing.