Systematic selection methodology for worker assistance systems in manufacturing. (April 2022)

• Record Type: Journal Article
• Authors: Mark, Benedikt G.; Rauch, Erwin; Matt, Dominik T.
• Is Part Of: Computers & industrial engineering. Volume 166(2022)
• Publication Date: 2022-04
• Subjects: Industry 4.0 -- Smart manufacturing -- Assistance systems -- Methodology -- Operator 4.0 -- Systematic selection; Engineering -- Data processing -- Periodicals; Industrial engineering -- Periodicals; 620.00285
• DOI: 10.1016/j.cie.2022.107982
• Languages: English
• ISSNs: 0360-8352

Abstract

Highlights: Systematic literature review on existing selection methodologies. Novel and systematic selection methodology for worker assistance systems. Definition of evaluation parameters for workplace, worker and work task. Ranking methodology of potentially useful worker assistance systems. Application and validation in a real use case. Abstract: The transformation process of the industry into a more digitized world is a key challenge of the Fourth Industrial Revolution. On the one hand, the advantages of new technologies must be used profitably, on the other hand, the workforce needs to be prepared to deal with new technologies and the complexity and speed that the 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 of appropriate worker assistance systems for specific work tasks and worker types are missing. This paper presents a novel and systematic selection methodology, to analyze and evaluate the workplace, the employee, and the respective work task, based on previously defined parameters. An innovative selection algorithm enables a ranking of potential useful worker assistance systems. Therefore, the proposed novel selection methodology not only contributes to the existing body of knowledge, but also proves to be a helpful tool for practitioners in selecting the right assistance system for both, human workers, and manufacturing operations.