An Estimation of Supporting Hand Forces for Common Automotive Assembly Tasks

Quite often people are faced with one handed tasks in which the other hand is needed for support. Without these supporting external forces, postures may be unstable, rendering the task impossible. Automotive assembly line operators are confronted with these types of tasks every day, such as hose installations and the connection of electrical components. Determining the optimal location and forces for the supporting hand is important to minimize potential injuries of operators. Traditionally, these supporting hand forces are measured by experiments. This work attempts to provide an important predictive tool that promises to be of considerable value to companies in predicting leaning forces in work simulation for the proactive ergonomic assessment of work tasks. It presents a method using optimization and stability analysis techniques. Stability is based on the calculation of a three dimensional zero moment point (3D-ZMP) and the resultant reaction loads, calculated from the joint torque. The formulation of the optimization problem used to predict the supporting hand forces is presented and tested using tasks commonly encountered by automotive assembly workers. The results are compared to that in literature, providing an initial validation of the methods. The predicted external forces fell within the 95% confidence intervals calculated from the literature for all tasks.

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Simulating Complex Automotive Assembly Tasks using the HUMOSIM Framework

10.4271/2009-01-2279 ◽

2009 ◽

Author(s):

Wei Zhou ◽

Thomas J. Armstrong ◽

Matthew P. Reed ◽

Suzanne G. Hoffman ◽

Diana M. Wegner

Keyword(s):

Automotive Assembly ◽

Assembly Tasks

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Ergonomic assessment of automotive assembly tasks with digital human modelling and the 'ergonomics assessment worksheet' (EAWS)

International Journal of Human Factors Modelling and Simulation ◽

10.1504/ijhfms.2012.051581 ◽

2012 ◽

Vol 3 (3/4) ◽

pp. 398 ◽

Cited By ~ 24

Author(s):

Karlheinz G. Schaub ◽

Jens Mühlstedt ◽

Benjamin Illmann ◽

Sebastian Bauer ◽

Lars Fritzsche ◽

...

Keyword(s):

Human Modelling ◽

Automotive Assembly ◽

Digital Human ◽

Assembly Tasks

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Investigation of common insertion hand postures and directions and determination of the voluntarily maximal and preferred insertion forces in automotive assembly tasks

Human Factors and Ergonomics in Manufacturing & Service Industries ◽

10.1002/hfm.20825 ◽

2019 ◽

Vol 30 (2) ◽

pp. 93-102

Author(s):

Kyung‐Sun Lee ◽

Myung‐Chul Jung

Keyword(s):

Automotive Assembly ◽

Assembly Tasks

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Optimal Posture and Supporting Hand Force Prediction for Common Automotive Assembly One-Handed Tasks

Journal of Mechanisms and Robotics ◽

10.1115/1.4025749 ◽

2014 ◽

Vol 6 (2) ◽

Cited By ~ 2

Author(s):

Bradley Howard ◽

James Yang ◽

Burak Ozsoy

Keyword(s):

Stability Analysis ◽

Degrees Of Freedom ◽

Human Performance ◽

Performance Measure ◽

Joint Torque ◽

External Support ◽

Human Model ◽

Automotive Assembly ◽

External Forces ◽

Hand Forces

People often complete tasks using one hand for the task and one hand for support. These one-handed support tasks can be found in many different types of jobs, such as automotive assembly jobs. Optimization-based posture prediction has proven to be a valid tool in predicting the postures necessary to complete the tasks, but the related external support forces have been prescribed and not predicted. This paper presents a method in which the optimal posture and related supporting hand forces can be predicted simultaneously using optimization and stability analysis techniques. Postures are evaluated using a physics-based human performance measure (HPM) while external forces are assessed using stability analysis. The physics-based performance measures are based on joint torque. Stability is analyzed using criteria based on a 3D zero moment point (ZMP). The human model used in the prediction contains 56 degrees of freedom and is based on a 50th percentile female in stature. Tasks based on common automotive assembly one-handed tasks found in literature are considered as examples to test the proposed method. Overall, the predicted supporting hand forces have good correlation with experimentally measured forces.

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