基于EEG和动作分析的手工装配线易疲劳工序  

Research on Manual Assembly Processes Fatigue Optimization Based on EEG and Motion Analysis

作　　者：蔡敏[1] 商滔[1] 付辉建[2] 李晓[1] 汪挺[1] 陈芸[1] 

机构地区：[1]杭州电子科技大学工业工程与管理研究所,浙江杭州310018 [2]浙江大学,管理学院神经管理学实验室,浙江杭州310027

出　　处：《工业工程与管理》2016年第2期68-72,80,共6页Industrial Engineering and Management

基　　金：国家自然科学基金资助项目(71171070);国家社会科学基金青年项目(14CTQ024);教育部人文社会科学研究青年基金项目(12YJC630095)

摘　　要：一些容易产生疲劳的工序广泛存在于手工装配线中,传统方法难以发觉,脑电分析根据大脑活动特征,将各类信号以数据的形式反映出来,帮助人们找到易产生疲劳的工序,成为人因领域研究的新热点。以BOSCH公司的电动螺丝刀手工装配线为例设计实验,选取16名年龄基本相同的被试者,经过相同的作业时间分别记录每个人的脑电数据,通过分析对比,发现装配工序中的易疲劳工序,根据动作分析提出优化和改进建议,证明了EEG和动作分析相结合的有效性。Some processes prone to fatigue widespread in manual assembly line, traditional methods were difficult to find, EEG analysis based on characteristics of brain activity, reflected various types of signals by data,became the new hot research field in human factors. As BOSCH Company＇s electric screwdriver manual assembly line designed an experiment for example. Selecting 16 subjects in substantially the same age, through the same operation time, recorded each person^s EEG data and found the fatigue process in the assembly process by analysis and comparison. Finally, proposing optimization and improvement recommendations for fatigue process based on motion analysis. It demonstrates the effectiveness of combining EEG and motion analysis.

关 键 词：脑电分析 手工装配线 疲劳 人因 动作分析 

分 类 号：TP206.1[自动化与计算机技术—检测技术与自动化装置]