Development of an Adaptive Human-centered Work Station for Fuel Cell Stack Assembly

Abstract

Facing the challenges of modern production, such as increased product variability and individuality, assembly systems must strive for maximum flexibility. Consequently, despite the continuous advancements in automation, the human workforce retains its crucial role in industrial assembly due to its exceptional adaptability and learning capabilities. However, the industry is confronted with the additional challenge of addressing a shortage of skilled workers, managing ongoing demographic changes, and handling an increasingly heterogenous workforce in terms of age, skills, and experience. As a result, there is a growing emphasis on the efficient and ergonomic use of the human workforce. In this context, the concept of human-centered production systems has emerged as an important approach.The objective of this paper is to propose a general concept for the implementation of a human-centered assembly system that can adapt to different human characteristics in terms of anthropometry, functional capabilities, knowledge, and personal needs during the assembly process. This in-process adaptation is based on the tracking of human movements and actions during the assembly process using LiDAR and camera technology. The collected data is utilized to feed a recommender system that serves to suggest possible configuration optimizations in the assembly system dimensions of Working height, Range of vision, gripping area, and handedness, Lighting and Use of information and assistance systems, encompassing a laser projector, spatial augmented reality facilitated by a dynamic beamer, and intelligent tools.Subsequently this general approach is applied to the development of a work station designed for the assembly of fuel cell stack components.