Physiological Data Measurement in Digital Manufacturing

2021 24th International Conference on Mechatronics Technology (ICMT) Pub Date : 2021-12-18 DOI:10.1109/ICMT53429.2021.9687200

Subham Agrawal, J. Chong, Ali A. Yacoub, M. Giuliani, A. Jafari, Appolinaire C. Etoundi

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Abstract

As industry is moving towards a new digital rev-olution, identifying workers' mental and physical status is key to improved productivity in a digital manufacturing scenario. The main objective here is to provide an overview of sensing technologies in digital manufacturing and discuss suitability for taking physiological measurements of workers collaborating with robots. A method for rating physiological sensors in digital manufacturing application areas has been discussed which takes into account expert reviews. Selected commercially-available sensors are rated based on 9 evaluation keys (wearability, form-factor, mobility, pre-training, data-exchange capability, on-board filtering, ease-of-use, cost, and calibration) for digital manufacturing. The result is a scorecard of available sensors with feasibility to be used in digital manufacturing. In a given category, this data allows the selection of the best available sensors for certain use cases. The method to score the sensors has been explicitly explained to allow readers to expand on and contribute towards the data.

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数字化制造中的生理数据测量

随着工业向新的数字革命迈进，在数字化制造场景中，识别工人的精神和身体状态是提高生产力的关键。本文的主要目的是概述数字制造中的传感技术，并讨论对与机器人合作的工人进行生理测量的适用性。讨论了一种考虑专家评价的数字制造应用领域生理传感器的评定方法。选定的商用传感器基于9个评估关键(可穿戴性，外形因素，移动性，预训练，数据交换能力，机载滤波，易用性，成本和校准)进行数字制造评级。结果是可用传感器的记分卡，具有在数字化制造中使用的可行性。在给定的类别中，此数据允许为某些用例选择最佳可用传感器。为传感器评分的方法已明确解释，以允许读者对数据进行扩展和贡献。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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2021 24th International Conference on Mechatronics Technology (ICMT)

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