Abstract
Ergonomics of human workers is one of the key elements in design and evaluation of production processes. Human ergonomics have a major impact on productivity as well as chronic health risks incurred by inappropriate working postures and conditions. In this paper we propose a novel method for estimating and communicating the ergonomic work condition called Binary Work-Condition Map, which provides a visualized feedback about work conditions of different configurations of an arm. The map is of binary nature and is derived by imposing the desired thresholds on considered ergonomic and safety related criteria. Therefore, the suggested arm postures in the map guarantee that all considered criteria are satisfied. This eliminates the ambiguity compared to state-of-the-art maps that uses continuous scales derived from weighted sum of multiple ergonomics criteria. In addition, to combine the advantages of both the binary map and the continuous map, we additionally propose a Hybrid Work-Condition Map that rules out unsuitable workspace with the binary map approach and renders the suitable workspace with the continuous map approach. The proposed approach was tested in simulation for various tasks and conditions. In addition, we conducted subjective evaluation experiments to compare the proposed methods with the state-of-the art method regarding the usability. The results indicated that the binary map is simpler to use, while the hybrid map is a good tradeoff between the binary and the continuous map. In selecting the map, strong points of each map should be considered with respect to the requirements of a specific application and task.
Highlights
Robots have successfully supplemented human workers in modern manufacturing processes
Earlier methods of evaluating ergonomics of working postures, like Rapid Upper Limb Assessment (RULA) (McAtamney and Corlett, 1993) and rapid entire body assessment (REBA) (Hignett and McAtamney, 2000), used predefined heuristic tables that indicate a score of particular joint configuration
An interactive Binary Work-Condition Map guides human workers to place their arms in appropriate postures for performing quasi-static manipulation tasks in an ergonomic and safe way
Summary
Robots have successfully supplemented human workers in modern manufacturing processes. While robots can work safely and efficiently without getting tired for extended periods of time, human workers are prone to productivity degradation when ergonomics is not taken into account. This is true both when the humans work on their own and when they work with machines, such as collaborative robots. Earlier methods of evaluating ergonomics of working postures, like Rapid Upper Limb Assessment (RULA) (McAtamney and Corlett, 1993) and rapid entire body assessment (REBA) (Hignett and McAtamney, 2000), used predefined heuristic tables that indicate a score of particular joint configuration. There are other important underlying indicators that affect the human ergonomics beyond kinematic posture and lifting load
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