Automatic assessment of the ergonomic risk for manual manufacturing and assembly activities through optical motion capture technology

被引:45
作者
Bortolini, Marco [1 ]
Gamberi, Mauro [1 ]
Pilati, Francesco [1 ]
Regattieri, Alberto [1 ]
机构
[1] Univ Bologna, Dept Ind Engn, Viale Risorgimento 2, I-40136 Bologna, Italy
来源
51ST CIRP CONFERENCE ON MANUFACTURING SYSTEMS | 2018年 / 72卷
关键词
Motion capture; depth camera; markerless; assembly; manufacturing; EAWS; ergonomic; muscoloskeletal disorder; automotive; REAL-TIME; DESIGN; SYSTEM;
D O I
10.1016/j.procir.2018.03.198
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Safeguard the operator health is nowadays a hot topic for most of the companies whose production process relies on manual manufacturing and assembly activities. European legislations, national regulations and international standards force the companies to assess the risk of musculoskeletal disorders of operators while they are performing manual tasks. Furthermore, international corporates typically require their partners to adopt and implement particular indices and procedures to assess the ergonomic risks specific of their industrial sector. The expertise and time required by the ergonomic assessment activity compels the companies to huge financial, human and technological investments. An original Motion Analysis System (MAS) is developed to facilitate the evaluation of most of the ergonomic indices traditionally adopted by manufacturing firms. The MAS exploits a network of marker-less depth cameras to track and record the operator movements and postures during the performed tasks. The big volume of data provided by this motion capture technology is employed by the MAS to automatically and quantitatively assesses the risk of musculoskeletal disorders over the entire task duration and for each body part. The developed hardware/software architecture is tested and validated with a real industrial case study of a car manufacturer which adopts the European Assembly Worksheet (EAWS) to assess the ergonomic risk of its assembly line operators. The results suggest how the MAS is a powerful architecture compared to other motion capture solutions. Indeed, this technology accurately assesses the operator movements and his joint absolute position in the assembly station 3D layout. Finally, the MAS automatically and quantitatively fill out the different EAWS sections, traditionally evaluated through timeand resource-consuming activities. (C) 2018 The Authors. Published by Elsevier B.V. Peer-review under responsibility of the scientific committee of the 51st CIRP Conference on Manufacturing Systems.
引用
收藏
页码:81 / 86
页数:6
相关论文
共 15 条
[1]   Multi-objective warehouse building design to optimize the cycle time, total cost, and carbon footprint [J].
Accorsi, Riccardo ;
Bortolini, Marco ;
Gamberi, Mauro ;
Manzini, Riccardo ;
Pilati, Francesco .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2017, 92 (1-4) :839-854
[2]   Including Material Exposure and Part Attributes in the Manual Assembly Line Balancing Problem [J].
Bortolini, M. ;
Faccio, M. ;
Gamberi, M. ;
Pilati, F. .
IFAC PAPERSONLINE, 2016, 49 (12) :926-931
[3]  
Bortolini Marco, 2016, International Journal of Logistics Systems and Management, V24, P155
[4]   Assembly system design in the Industry 4.0 era: a general framework [J].
Bortolini, Marco ;
Ferrari, Emilio ;
Gamberi, Mauro ;
Pilati, Francesco ;
Faccio, Maurizio .
IFAC PAPERSONLINE, 2017, 50 (01) :5700-5705
[5]   Multi-objective assembly line balancing considering component picking and ergonomic risk [J].
Bortolini, Marco ;
Faccio, Maurizio ;
Gamberi, Mauro ;
Pilati, Francesco .
COMPUTERS & INDUSTRIAL ENGINEERING, 2017, 112 :348-367
[6]   The identification of vertical velocity profiles using an inertial sensor to investigate pre-impact detection of falls [J].
Bourke, A. K. ;
O'Donovan, K. J. ;
OLaighin, G. .
MEDICAL ENGINEERING & PHYSICS, 2008, 30 (07) :937-946
[7]   On the use of Multi-Depth-Camera based Motion Tracking Systems in Production Planning Environments [J].
Geiselhart, Florian ;
Otto, Michael ;
Rukzio, Enrico .
RESEARCH AND INNOVATION IN MANUFACTURING: KEY ENABLING TECHNOLOGIES FOR THE FACTORIES OF THE FUTURE - PROCEEDINGS OF THE 48TH CIRP CONFERENCE ON MANUFACTURING SYSTEMS, 2016, 41 :759-764
[8]   Introducing quantitative analysis methods into virtual environments for real-time and continuous ergonomic evaluations [J].
Jayaram, U ;
Jayaram, S ;
Shaikh, I ;
Kim, YJ ;
Palmer, C .
COMPUTERS IN INDUSTRY, 2006, 57 (03) :283-296
[9]  
Li G., 2017, ERGONOMICS, V42, P674
[10]  
Paoli Pascal., 2001, 3 EUROPEAN SURVEY WO