Manufacturing Process Design Based on Mental and Physical Workload Analysis

被引：5

作者：

Ma, QingGuo ^{[1
]}

Sun, XiaoLi ^{[1
]}

Fu, HuiJian ^{[1
]}

Zhao, DaChun ^{[2
]}

Guo, JunFeng ^{[3
]}

机构：

[1] Zhejiang Univ, Dept Management Sci & Engn, Hangzhou 310003, Zhejiang, Peoples R China

[2] Hangzhou Zhengheng Elect Co Ltd, Hangzhou, Peoples R China

[3] Hangzhou Huali Measuring Appliance Co Ltd, Hangzhou, Peoples R China

来源：

ADVANCED RESEARCH ON MECHANICAL ENGINEERING, INDUSTRY AND MANUFACTURING ENGINEERING III | 2013年 / 345卷

关键词：

Neuro-Industrial Engineering (Neuro-IE); Industrial Engineering; mental workload; physical workload; electroencephalography; electromyography; EEG;

D O I：

10.4028/www.scientific.net/AMM.345.482

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

Human factor is an important issue in industrial engineering system. Mental and physical states in the manufacturing process greatly influence worker's performance. In this study, EEG data were recorded to analyze mental workload and EMG data to analyze physical workload when a worker was tasks in the production line. Video camera was used to record the manufacturing process simultaneously. We could detect the time periods within which the worker's mental workload or physical workload was at a high level. By tracking the operating process through the video, we were able to find the potential problems leading to high workload, and thus optimize the design of manufacturing process or machine in order to decrease mental and physical workload and improve production efficiency.

引用

页码：482 / +

页数：2

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