Manufacturing Operator Ergonomics: A Conceptual Digital Twin Approach to Detect Biomechanical Fatigue

Abhimanyu Sharotry,Rachel M Koldenhoven,Francis A Mendez Mediavilla,Jesus A Jimenez,David Wierschem,Damian Valles

doi:10.1109/access.2022.3145984

Abhimanyu Sharotry, Rachel M Koldenhoven + Show 4 more

Open Access

https://doi.org/10.1109/access.2022.3145984

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Journal: IEEE Access	Publication Date: Jan 1, 2022
Citations: 8	License type: CC BY 4.0

Affiliation: Texas State University

Abstract

The primary sources of injuries in the workplace are improper manual material handling (MMH) motions, forklift collisions, slip, and fall. This research presents a Digital Twin (DT) framework to analyze fatigue in humans while performing lifting MMH activity in a laboratory environment for the purpose of reducing these types of injuries. The proposed methodology analyzes the worker’s body joints to detect biomechanical fatigue as a factor of change in back, elbow, and knee joint angles. Using the dynamic time warping (DTW) algorithm, the change in joint angles with time was analyzed. The variation in DTW parameters was evaluated using exponentially weighted moving average (EWMA) control charts for further analysis. A preliminary study considering two healthy male subjects performing seven experiments, each under an optical motion capture system was performed to test the model’s efficiency. Our contributions are twofold. First, we propose a model to detect biomechanical fatigue in the subjects performing MMH lifting activity as a change in joint angles. Secondly, the research also shows evidence that different individuals show signs of body fatigue via different body joints and showcases the need for a true personalized DT for an operator for fatigue assessment in an MMH environment.

Highlights

Industry 4.0 (I4.0) is the era of digitization and is evolving exponentially
A True Positive (TP) detection is defined as the exponentially weighted moving average (EWMA) point in the control chart, which lies in RPE 15 to RPE 17 range and beyond the upper control limit (UCL)
False Negative (FN) is the point that lies in the same range (RPE 15 to RPE 17) but below the UCL

Summary

Introduction

Industry 4.0 (I4.0) is the era of digitization and is evolving exponentially Technologies such as the Internet of Things, cyber-physical systems, enterprise architecture, artificial intelligence, robotics, autonomous vehicles, and 3-D printing have been vital components in the development of I4.0 [1]. Romero et al [5] has defined this innovative generation of operators as Operator 4.0, i.e., humans assisted by machines and technology to enhance their physical, cognitive and sensorial capabilities to perform their manufacturing tasks. Material handling is one of the most physically demanding tasks, and can quickly become a leading factor contributing to operators' accumulation of mental and physical fatigue [6]. According to the Bureau of Labor Statistics, 114 million people were employed in the Warehousing and Storage Industry Group in 2018 [7]. These statistics show that 22% of the workforce are VOLUME XX, 2017

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