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

Sharotry, Abhimanyu; Jimenez, Jesús A.; Mediavilla, Francis A. Méndez; Wierschem, David; Koldenhoven, Rachel M.; Valles, Damian

doi:10.1109/access.2022.3145984

Cited by 10 publications

(2 citation statements)

References 59 publications

(93 reference statements)

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“…Through digital human modeling (Paul et al, 2021 ), DTs can contribute to monitoring, assessing, and designing different human-system interactions (Caputo et al, 2019 ; Greco et al, 2020 ; Sharotry et al, 2022 ; Wang B. et al, 2022 ) according to the perspective of human factors. In particular, neuroergonomics (Mehta and Parasuraman, 2013 )—especially computational neuroergonomics (Farahani et al, 2019 )—can advantageously exploit twinning for understanding how the human nervous system works in real contexts (Cheng et al, 2022 ), and improving the design of any item interacting with it.…”

Section: Neuroergonomic Twinning Of Hri Systemsmentioning

confidence: 99%

Beyond Digital Twins: Phygital Twins for Neuroergonomics in Human-Robot Interaction

et al. 2022

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Section: Neuroergonomic Twinning Of Hri Systemsmentioning

confidence: 99%

Beyond Digital Twins: Phygital Twins for Neuroergonomics in Human-Robot Interaction

et al. 2022

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“…As drivers are forced to adapt to these vehicles, they face an increased risk of various occupational hazards, including Lower Back Pain (LBP), whole-body vibration, fatigue, and musculoskeletal disorders. The constrained work postures and vibration-induced fatigue on muscles and tendons are known to contribute to problems such as back pain while driving (Sharotry et al, 2022) Anthropometry is the art and science of measuring the physical geometry, mass properties, and strength capabilities of the human body (Hassanain et al, 2023). It is concerned with the scientific study of human subjects for the development of standards and evolving of specific demands associated particularly with manufactured goods and services to enhance product usability and ergonomics suitability for the user population (Halek, 2023).…”

Section: Introductionmentioning

confidence: 99%

Mismatch Between Anthropometric Measurements of Occupational Drivers in Southwest Nigeria and Vehicle Seat Design Parameters

Onawumi,

Akinrinade,

Abisoye

et al. 2023

int.jour.sci.res.mana

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Most commercial vehicles used for transportation are not manufactured in Nigeria. As a result, the design of these vehicles, which relies on anthropometric measurements from the manufacturing countries, does not adequately accommodate the variations in anthropometric measurements of Nigerian drivers. This mismatch can lead to ergonomic risk and musculoskeletal disorders. Therefore, this study investigated the level of mismatch between drivers’ anthropometric characteristics and seat design variables of selected commercial vehicles. A total of 161 male drivers were randomly selected, and data was collected using standard Nordic questionnaires. The anthropometric characteristics of the drivers were measured using a stadiometer and measuring tape. Seat design variables were also measured using a tape rule and steel rule. The collected data were subjected to statistical analysis, including the calculation of means, standard deviations, and 5th, 50th, and 95th percentiles of the anthropometric measurements. The results revealed the average anthropometric measurements for sitting height (erect), sitting height (normal), shoulder height, buttock-knee length, and buttock-popliteal length to be 83.01, 77.86, 52.71, 57.07, and 50.20 cm, respectively. Comparing the results of the seat variables with the relevant anthropometric characteristics, a mismatch in the measurements was observed. This led to the conclusion that the existing commercial vehicle seats in the Southwest region are not compatible with the anthropometric dimensions of the drivers.

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Visual analysis of fatigue in Industry 4.0

Alfavo-Viquez,

Zamora-Hernandez,

Azorín-López

et al. 2023

Int J Adv Manuf Technol

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The performance of manufacturing operations relies heavily on the operators’ performance. When operators begin to exhibit signs of fatigue, both their individual performance and the overall performance of the manufacturing plant tend to decline. This research presents a methodology for analyzing fatigue in assembly operations, considering indicators such as the EAR (Eye Aspect Ratio) indicator, operator pose, and elapsed operating time. To facilitate the analysis, a dataset of assembly operations was generated and recorded from three different perspectives: frontal, lateral, and top views. The top view enables the analysis of the operator’s face and posture to identify hand positions. By labeling the actions in our dataset, we train a deep learning system to recognize the sequence of operator actions required to complete the operation. Additionally, we propose a model for determining the level of fatigue by processing multimodal information acquired from various sources, including eye blink rate, operator pose, and task duration during assembly operations.

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

Abstract: Date of publication xxxx 00, 0000, date of current version xxxx 00, 0000.

Cited by 10 publications

References 59 publications

Beyond Digital Twins: Phygital Twins for Neuroergonomics in Human-Robot Interaction

Beyond Digital Twins: Phygital Twins for Neuroergonomics in Human-Robot Interaction

Mismatch Between Anthropometric Measurements of Occupational Drivers in Southwest Nigeria and Vehicle Seat Design Parameters

Visual analysis of fatigue in Industry 4.0

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