Elsevier

Applied Ergonomics

Volume 83, February 2020, 102985
Applied Ergonomics

Workers’ biomechanical loads and kinematics during multiple-task manual material handling

https://doi.org/10.1016/j.apergo.2019.102985Get rights and content

Highlights

  • 20 subjects performed 3780 repetitions of continuous sequential box conveying task.

  • Handled boxes weighted from 2 to 12 kg and shelves heights from 20 to 170 cm above floor.

  • Prediction models were developed for spinal and shoulder moments and joint angles.

  • Shelf height was main predictor of moments and angles with a nonlinear relationship.

  • Changes in shelf height resulted in a tradeoff between spinal and shoulder moments.

Abstract

This study investigated the biomechanical loads and kinematics of workers during multiple-task manual material handling (MMH) jobs, and developed prediction models for the moments acting on a worker's body and their peak joint angles. An experiment was conducted in which 20 subjects performed a total of 3780 repetitions of a box-conveying task. This task included continuous sequential removing, carrying and depositing of boxes weighing 2–12 kg. The subjects' motion was captured using motion-capture technology. The origin/destination height was the most influencing predictor of the spinal and shoulder moments and the peak trunk, shoulder and knee angles. The relationship between the origin/destination heights and the above parameters was nonlinear. The mass of the box, and the subject's height and mass, also influenced the spinal and shoulder moments. A tradeoff between the moments acting on the L5/S1 vertebrae and on the shoulder joint was found. Compared to the models developed in similar studies that focused on manual material handling (albeit under different conditions), the high-order prediction equation for peak spinal moment formulated in the present study was found to explain between 10% and 48% more variability in the moments. This suggests that using a high-order equation in future studies might improve the prediction.

Introduction

Manual material handling (MMH) tasks, such as lifting, carrying and lowering objects, are still common in various industries, and contribute substantially to both the number of claims for musculoskeletal disorders (MSDs) and their resulting costs (Murphy et al., 1996; National Academy of Sciences, 2001; Bureau of Labor Statistics, 2015). In order to reduce the number and severity of MMH injuries, many studies have investigated worker motion and biomechanical loads during MMH tasks (e.g., Lavender et al., 2003; Hoozemans et al., 2008; Qu and Nussbaum, 2009; Gallagher et al., 1988; Karwowski and Yates, 1986; Rose et al., 2013). However, these studies investigated cases in which workers conducted only a single MMH task (e.g., only lifting, only carrying), while in industry, workers often carry out multiple-task MMH jobs, which combine several sequential tasks (e.g., lifting a box from a shelf and turning simultaneously, or carrying a box and lowering it toward a platform).

For this reason, Plamondon and colleagues investigated workers’ biomechanics during a multiple-task palletizing job (Plamondon et al., 2010, 2012, 2014, 2017). The mass of the box being handled was either 15 or 23 kg, and the origin and destination heights were less than 96 cm. The body of work produced by these authors constitutes an important step in understanding the biomechanics of workers during multiple-task MMH; however, in many industrial cases the workers handle lighter objects and the platform heights are greater than 96 cm (Harari et al., 2018). Furthermore, these studies focused on the spinal load, while other joints that are positively correlated with MSDs during MMH tasks (Bureau of Labor Statistics, 2015), such as the shoulder, were not investigated.

Other studies focused on differences in biomechanics and physiological parameters between single-task and multiple-task MMH, and found differences in the subjects’ kinematics (Harari et al., 2019, Harari et al., 2019b), lower back moments, compression and shear forces (Harari et al., 2019, Harari et al., 2019b; Straker et al., 1997b), perceived rate of exertion (Straker et al., 1997a), and maximum acceptable weight limit (Straker et al., 1996). These studies and others (e.g., Garg and Kapellusch, 2009; Dempsey, 1999) suggested that worker physiology and biomechanics during multiple-task MMH jobs should be investigated separately, and that the analysis of multiple-task jobs in industry should be conducted using tools developed specifically for them.

When designing a new work process, it is important to be able to predict ergonomic measures as a function of the workplace parameters (e.g., origin height, box mass). Worker physiology during multiple-task MMH has been investigated, and prediction models for workers' oxygen consumption have been developed (Dempsey et al., 2008). A recent study investigated workers' pace during multiple-task MMH, and developed models predicting the time required to complete multiple-task MMH jobs (Harari et al., 2018). Yet, to the best of our knowledge, no models have been developed for predicting worker kinetics and kinematics during multiple-task MMH that occurs in 3D space. Thus, the objective of this study is to investigate worker biomechanics during multiple-task MMH, and to develop a prediction model for both the moments acting on the worker's spine and shoulders, and the worker's kinematics, during multiple-task MMH jobs.

Section snippets

Methods

An experiment in which subjects performed a continuous box-conveying work process was conducted. Each subject's motion was recorded using a motion-capture system, and biomechanical parameters were calculated (see Section 2.1). In order to analyze each of the tasks individually during the box-conveying work process, we developed a program that automatically identified and classified each of the tasks using the motion data (Section 2.2). Statistical analyses were conducted and prediction models

Significant main effects and interactions

The box mass, origin height (for the removing task) and destination height (for the depositing task) affected the peak and cumulative moments acting on the L5/S1 vertebrae and on the shoulder joints. These three variables also affected the kinematics (i.e., the peak trunk, shoulder and knee angles). For all of these main effects, p < 0.05. Subject height, interacting with the origin/destination height, affected both the moments acting on the L5/S1 and shoulder joints and the peak joint angles

Discussion

This study investigated worker biomechanics during multiple-task MMH with 3D motion components. We developed prediction models for the workers’ peak joint angles, and for the moments acting on the spine and shoulder.

Limitations

The subjects in this experiment were young and healthy university students. While this is a good representation of workers in some industries, other fields may include less fit or older populations, which will affect the weight distribution and the workers’ movements.

The design of the shelf stations (i.e., three shelves, one above the other) might have affected the subject's kinematics during the removing and depositing tasks. Specifically, the shelves could have obstructed the inclination of

Conclusion

During multiple-task removing and depositing of boxes weighing 2–12 kg, the platform's height was found to be the most important predictor of both the spinal and shoulder moments and the subject's kinematics (explaining between 36% and 81% of the variation). The relationship between the platform height and the spinal moment was nonlinear, with the moment being highest at 0.2 m, decreasing to a minimum at 1.1 m, and then slowly increasing as the origin height increased to 1.7 m. For the shoulder

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

The authors would like to thank Alan De Asha from C-Motion for his support in the development of the automated program, and Mor Topaz and Yarden Avrahami for their assistance in the data collection. This research was supported by the Israel Science Foundation (grant no. 8/998).

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