基于改进DMAIC的打磨工人工效学模型与作业姿势改善

doi:10.3969/j.issn.1007-7375.230195

工业工程 ›› 2024, Vol. 27 ›› Issue (5): 53-63.doi: 10.3969/j.issn.1007-7375.230195

• 人因工程 • 上一篇

基于改进DMAIC的打磨工人工效学模型与作业姿势改善

郭春东¹, 李云浩¹, 颜硕¹, 沈琳²

1. 河北科技大学经济管理学院河北石家庄 050091;
2. 北京津发科技股份有限公司北京 100080

收稿日期:2024-03-11 发布日期:2024-11-05
作者简介:郭春东 (1974—)，男，河北省人，副教授，博士，主要研究方向为创新管理、数据挖掘、系统仿真。Email: guochundong@hebust.edu.cn
基金资助:
国家自然科学基金资助项目 (61440012)；河北省软科学基金资助项目 (174576236D)；石家庄市软科学资助项目 (215790165A)

An Ergonomics Model and Posture Improvement for Grinding Workers Based on an Improved DMAIC Approach

GUO Chundong¹, LI Yunhao¹, YAN Shuo¹, SHEN Lin²

1. School of Economic and Management, Hebei University of Science and Technology, Shijiazhuang 050091, China;
2. Kingfar International Inc., Beijing 100080, China

Received:2024-03-11 Published:2024-11-05

摘要/Abstract

摘要： 为改进打磨工人作业姿势、减少罹患工作相关肌肉骨骼疾患 (WMSDs) 风险，对某制药设备企业压力容器车间打磨工人的作业姿势开展实验研究。在DMAIC模型基础上，提出在改进 (I) 阶段增加仿真验证分析 (S) 、在控制 (C) 阶段增加执行 (E) 分析的DMASIEC工作改善模型；采用Xsens MVN动作捕捉系统与Jack TAT工具同步联合分析的方法，设计、开展基于生理信号和主观评价的测度指标的作业姿势改善沉浸式实景实验；结合Jack对打磨工作业姿势的仿真验证，提出能够减少作业疲劳的打磨工作台和作业改善指导方法。结果表明，开展相同的作业任务时，打磨工L4/L5脊椎处压力约为原有压力的1/4，工作姿势评级均为AC1；3名打磨工表征作业疲劳的sEMG和HRV指标由蹲姿作业转为坐姿作业后发生了显著变化 (P＜0.05)；改善后的工作台和操作方法有助于改善作业姿势对肌肉骨骼系统的不良影响。

关键词: 工效学, DMAIC模型, 表面肌电, 心率变异性, Jack仿真

Abstract: In order to improve the working posture of grinding workers and reduce the risk of developing work-related musculoskeletal disorders (WMSDs), an experimental study is carried out on the working postures of grinding workers in the pressure vessel workshop of a pharmaceutical equipment company. Based on the DMAIC model, a DMASIEC work improvement model is proposed which adds simulation (S) verification analysis in the improvement (I) stage and execution (E) analysis in the control (C) stage. Using the Xsens MVN motion capture system and the Jack TAT tool in a synchronized joint analysis method, an immersive real-world experiment for job posture improvement based on physiological signals and subjective evaluation indicators is designed and carried out. Through the simulation verification of grinding postures using Jack, a guideline for improving grinding worktable and operations is proposed to reduce work fatigue. Results show that the pressure on the L4/L5 spines of grinding workers is about 1/4 of the original pressure when performing the same task, and all working posture ratings are AC1; significant changes (P ＜ 0.05) in sEMG and HRV fatigue indicators are observed in three workers after transitioning from a squatting to a sitting posture; the improved worktable and operational guidance contribute to mitigating the adverse effects of working posture on the musculoskeletal system.

Key words: ergonomics, DMAIC model, surface elecromyography, heart rate variability, Jack simulation

中图分类号:

TB18
F428

郭春东, 李云浩, 颜硕, 沈琳. 基于改进DMAIC的打磨工人工效学模型与作业姿势改善[J]. 工业工程, 2024, 27(5): 53-63.

GUO Chundong, LI Yunhao, YAN Shuo, SHEN Lin. An Ergonomics Model and Posture Improvement for Grinding Workers Based on an Improved DMAIC Approach[J]. Industrial Engineering Journal, 2024, 27(5): 53-63.

参考文献

[1] 江南宇, 董一丹, 秦东亮, 等. 装配制造企业作业人员工效学负荷与工作相关肌肉骨骼疾患的关系[J]. 环境与职业医学, 2022, 39(6): 600-608.
JlANG Nanyu, DONG Yidan, QlN Dongliang. et al. Relationship between ergonomic exposures and work-related musculoskeletaldisorders of assembly workers in assembly manufacturing enterprises[J]. Journal of Environmental and Occupational Medicine, 2022, 39(6): 600-608.
[2] 徐胜, 金龙哲, 徐明伟. 受限空间钻孔工人的肌肉疲劳特性研究[J]. 中国安全科学学报, 2019, 29(3): 76-81.
XU Sheng, JIN Longzhe, XU Mingwei. Study on muscle fatigue characteristics of drilled workers in confined space[J]. China Safety Science Journal, 2019, 29(3): 76-81.
[3] 李良, 肖军, 刘芷言, 等. 铸件打磨工人姿势分析及改善研究[J]. 工业工程, 2020, 23(4): 167-173.
LI Liang, XIAO Jun, LIU Zhiyan, et al. Posture analysis and improvement research of casting grinding workers[J]. Industrial Engineering Journal, 2020, 23(4): 167-173.
[4] 朱守林, 严杰, 李航天, 等. 基于心率变异性的草原公路驾驶疲劳恢复调节方式[J]. 科学技术与工程, 2022, 22(15): 6362-6368.
ZHU Shoulin, YAN Jie, LI Hangtian, et al. Driving fatigue recovery and regulation on grassland highway based on heart rate variability[J]. Science Technology and Engineering, 2022, 22(15): 6362-6368.
[5] 赵小平, 龚俊, 万平, 等. 基于生理信号分析的不同风格驾驶人疲劳特性[J]. 中国科技论文, 2022, 17(10): 1111-1119.
ZHAO Xiaoping, GONG Jun, WAN Ping, et al. Fatigue characteristic of drivers with different styles based on physiological signal analysis[J]. China Science Paper, 2022, 17(10): 1111-1119.
[6] 祝荣欣. 基于生理信号的驾驶疲劳检测研究综述[J]. 人类工效学, 2020, 26(4): 82-86.
ZHU Rongxin. Research review of driver fatigue detection based on physiological signals[J]. Chinese Journal of Ergonomics, 2020, 26(4): 82-86.
[7] 许全盛, 白茹雪, 李世明. 力量训练负荷和肌肉疲劳对表面肌电非线性参数的双重调节[J]. 中国体育科技, 2022, 58(8): 83-90.
XU Quansheng, BAI Ruxue, LI Shiming. Strength training load and muscle fatigue cooperatively modulates the nonlinear parameters of surface electromyography[J]. China Sport Science and Technology, 2022, 58(8): 83-90.
[8] 陈晓琳, 陈立, 郭鑫禾, 等. 井下支护作业人员颈部肌肉疲劳特性研究[J]. 中国安全生产科学技术, 2022, 18(6): 92-97.
CHEN Xiaolin, CHEN Li, GUO Xinhe, et al. Study on fatigue characteristics of neck muscles of underground supporting operators[J]. Journal of Safety Science and Technology, 2022, 18(6): 92-97.
[9] HASSAN A, YAHYA S. A case study on implementing lean six Sigma: DMAIC methodology in aluminum profiles extrusion process[J]. The TQM Journal, 2023, 35(2): 337-365.
[10] KUVVETLI Ü, FIRUZAN A R. Applying six sigma in urban public transportation to reduce traffic accidents involving municipality buses[J]. Total Quality Management, 2019, 30(1-2): 82-107.
[11] 王晨霖, 鲁建厦, 李嘉丰. 基于DMAIC与仿真的地铁乘坐流程改进[J]. 工业工程, 2017, 20(5): 94-102.
WANG Chenlin LU Jiansha, LI Jiafeng. Process improvement of metro system based on DMAIC and simulation[J]. Industrial Engineering Journal, 2017, 20(5): 94-102.
[12] GOMATHI PRABHA M, YUVARAJA M. Development of an IoT integrated DMAIC model for process improvement in Indian SMEs: an empirical study[J]. Proceedings of the Institution of Mechanical Engineers, Part E: Journal of Process Mechanical Engineering, 2023, 237(2): 589-601.
[13] 祝荣欣. 基于sEMG的联合收获机驾驶人腰部肌肉疲劳研究[J]. 工业工程, 2020, 23(1): 119-125.
ZHU Rongxin. A study of lumbar muscle fatigue of combine harvester drivers based on sEMG[J]. Industrial Engineering Journal, 2020, 23(1): 119-125.
[14] 吴旭东, 马佩, 王乐军, 等. 重复性同侧搬举负荷对竖脊肌疲劳的影响[J]. 中国安全科学学报, 2018, 28(6): 31-36.
WU Xudong, MA Pei, WANG Lejun, et al. Influence of repeated ipsilateral labor load on erector spinal muscle fatigue[J]. China Safety Science Journal, 2018, 28(6): 31-36.
[15] 龚淑娟, 赵永翔, 黄德明. 基于多生理信号融合的疲劳驾驶检测研究[J]. 安全与环境学报, 2023, 23(11): 4002-4012.
GONG Shujuan, ZHAO Yongxiang, HUANG Deming. Research on fatigue driving detection based on multi-physiological signal fusion[J]. Journal of Safety and Environment, 2023, 23(11): 4002-4012.
[16] 蔡启明. 以动态心率为指标的体力疲劳的评价方法研究[J]. 人类工效学, 1999(1): 28-30.
CAI Qiming. Study on methods of evaluating physical fatigue according to dynamic heart rate[J]. Chinese Journal of Ergonomics, 1999(1): 28-30.
[17] 徐明伟, 金龙哲, 张驎, 等. 基于心率监测的建筑工人生理疲劳分析[J]. 工程科学学报, 2018, 40(6): 760-765.
XU Mingwei, JIN Longzhe, ZHANG Lin, et al. Research on the fatigue of construction workers by heart rate monitoring[J]. Chinese Journal of Engineering, 2018, 40(6): 760-765.

基于改进DMAIC的打磨工人工效学模型与作业姿势改善

An Ergonomics Model and Posture Improvement for Grinding Workers Based on an Improved DMAIC Approach

PDF

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 5

编辑推荐

Metrics

本文评价

[1]	苏晨, 张浩然, 程帅. 基于CATIA的可穿戴下肢康复外骨骼人类工效学研究[J]. 工业工程, 2022, 25(1): 160-165.
[2]	祝荣欣. 基于sEMG的联合收获机驾驶人腰部肌肉疲劳研究[J]. 工业工程, 2020, 23(1): 119-125.
[3]	刘力卓, 赵义格, 韩玉琪, 何明. 基于Jack远程监控操作台人机工效评价[J]. 工业工程, 2019, 22(5): 25-31.
[4]	李霞霞, 申黎明, 方菲. 基于模糊综合评判的职员办公椅工效学[J]. 工业工程, 2018, 21(2): 81-86.
[5]	段斌, 雷永杰, 刘蓉, 张立松. 基于DMAIC模型的起锚机离合器故障问题研究[J]. 工业工程, 2017, 20(3): 75-81.