Manual Material Research Articles

Reviewing interventions to enhance comfort and productivity of workers in Enterprises

The following study deals with the detailed reviews regarding the interventions that have been done globally in the sector of entrepreneurial interventions in aspect of work simplification. Various standards hence can be considered while referring to different designs for enterprises, especially small scale enterprises. The studies have revealed the musculoskeletal disorders from manual material handling (MMH) works often involving strains and sprains to the lower back, shoulders, and upper limbs. The ergonomic interventions are found to give comfort to the workers in various postures. It is concluded that the design of the system must be incorporating to the worker, equipment, and environment as a whole.

Evaluating Different Measures of Low Back Pain Among U.S. Manual Materials Handling Workers: Comparisons of Demographic, Psychosocial, and Job Physical Exposure.

To examine differences in demographic, psychosocial, and job physical exposure risk factors between multiple low back pain (LBP) outcomes in a prospective cohort of industrial workers. LBP remains a leading cause of lost industrial productivity. Different case definitions involving pain (general LBP), medication use (M-LBP), seeking healthcare (H-LBP), and lost time (L-LBP) are often used to study LBP outcomes. However, the relationship between these outcomes remains unclear. Demographic, health status, psychosocial, and job physical exposure risk factors were quantified for 635 incident-eligible industrial workers. Incident cases of LBP outcomes and pain symptoms were quantified and compared across the four outcomes. Differences in age, gender, medical history, and LBP history were found between the four outcomes. Most incident-eligible workers (67%) suffered an LBP outcome during follow-up. Cases decreased from 420 for LBP (25.4 cases/100 person-years) to 303 for M-LBP (22.0 cases/100 person-years), to 151 for H-LBP (15.6 cases/100 person-years), and finally to 56 for L-LBP (8.7 cases/100 person-years). Conversely, pain intensity and duration increased from LBP to H-LBP. However, pain duration was relatively lower for L-LBP than for H-LBP. Patterns of cases, pain intensity, and pain duration suggest the influence of the four outcomes. However, few differences in apparent risk factors were observed between the outcomes. Further research is needed to establish consistent case definitions. Knowledge of patterns between different LBP outcomes can improve interpretation of research and guide future research and intervention studies in industry.

Two-Dimensional Symmetric Box Delivery Motion Prediction and Validation: Subtask-Based Optimization Method

Box delivery is a complicated manual material handling task which needs to consider the box weight, delivering speed, stability, and location. This paper presents a subtask-based inverse dynamic optimization formulation for determining the two-dimensional (2D) symmetric optimal box delivery motion. For the subtask-based formulation, the delivery task is divided into five subtasks: lifting, the first transition step, carrying, the second transition step, and unloading. To render a complete delivering task, each subtask is formulated as a separate optimization problem with appropriate boundary conditions. For carrying and lifting subtasks, the cost function is the sum of joint torque squared. In contrast, for transition subtasks, the cost function is the combination of joint discomfort and joint torque squared. Joint angle profiles are validated through experimental results using Pearson’s correlation coefficient (r) and root-mean-square-error (RMSE). Results show that the subtask-based approach is computationally efficient for complex box delivery motion simulation. This research outcome provides a practical guidance to prevent injury risks in joint torque space for workers who deliver heavy objects in their daily jobs.

Reports from the field: current challenges is assessing risk from push pull tasks and gaps in the research base

In this session, we continue our discussion of push and pull manual materials handling tasks, especially issues related to the use of manual carts. We will describe some current issues in the evaluation of cart-handling tasks from aspects of both risk and performance, describe some practices currently employed to address these issues and will conclude with some thoughts about a program of research to enhance our understanding of how these tasks can be performed safely and efficiently.

Prediction of Occupational Physical Activities using Inertial Measurement Units and Deep Learning Models

Many workers engaged in manual material handling (MMH) jobs experience high physical demands that are associated with work-related musculoskeletal disorders (WMSD). Quantifying the physical demands of a job is an important legal requirement in the US that is used by human resources in the job hiring process. Most physical demands analysis (PDA) are performed using observational and semi-quantitative methods. The lack of accuracy and reliability of these methods can create problems when assigning acceptable tasks to an injured worker. In this study, various deep learning models were applied to data from eight inertial measurement units (IMUs) to predict 15 occupational physical activities (OPA). Overall, a 95% accuracy was reached by convolutional neural network (CNN) for predicting occupational physical activities when performed in isolation. More work is needed to estimate the accuracy of the model when OPA elements are combined into a more complex task.

Survey of One-handed Lifting in Manufacturing Industry: A Cross-sectional Study of the BackWorks Study Cohort

Low back pain (LBP) is a common health problem and a major cause of lost productivity in workplaces. Manual materials handling (MMH) jobs have traditionally been regarded as risk factor for LBP. Compared to two-handed lifting, one-handed lifting has received little attention in both epidemiological and biomechanical research. In addition, one frequent complaint of the revised NIOSH lifting equation (RNLE) has been the lack of capability to directly evaluate one-handed lifting. Modifications have been proposed by the European Union, however their efficacy and influence have not yet been evaluated. This cross-sectional study provided objective survey of the MMH jobs, especially the one-handed lifting performed in manufacturing industry and investigated the outcomes of three proposed methods to address one-handed lifting using RNLE approach. Preliminary results suggest that workers with some one-handed lifting are associated with higher physical exposure. However, the increase was more significant among those who perform primarily one-handed lifting.

Ergonomics Evaluation of Manual Material Handling Activities in the Section of Feeding Laying Hens at Poultry Farm

This study aimed to evaluate the activity of feeding laying hens at poultry farm. Observations were made of all workers in charge of providing animal feed totaling 13 workers. The work observed was the process of loading animal feed on baskets until the final distribution. The evaluation was based on the results of the Nordic Body Map questionnaire, physiological workload measurements, National Institute for Occupational Safety and Health (NIOSH) lifting calculations. The worker’s physiological workload was taken into account, and it revealed that there has been an increase in work pulse rate obtained Cardiovascular Load (%CVL) is in the range of 58%-72% and the energy consumption of workers ranges from 4.10-6.59 Kcal/minute. Thus, physiologically the work activities carried out by the feeding workers are categorized as moderate work, and it is necessary to improve the work activities. Meanwhile, evaluation using the Recommended Weight Limit (RWL) and Lifting Index (LI) in the process of animal feed showed RWL values ranged from 8.61 kg-10.19 kg, and LI values ranged from 1.87 to 2.50. This number is beyond the limit for manual lifting.

Spinal Compression Force During Manual Material Handling - Calculated in JackTM Software Using Real Vs Predicted Human Motion

Spinal Compression Force During Manual Material Handling - Calculated in Jack^TM Software Using Real Vs Predicted Human Motion

Development of an observation-based tool for ergonomic exposure assessment in informal electronic waste recycling and other unregulated non-repetitive work.

Most existing ergonomic assessment tools are intended for routine work. Time- and cost-efficient observational tools for ergonomic assessment of unregulated work are lacking. This paper presents the development of an observation-based tool designed to investigate ergonomic exposures among informal electronic waste workers that could be applied to other unregulated jobs/tasks. Real time coding of observation is used to estimate the relative duration, intensity, and frequency of exposure to key work postures, forceful exertions, movements, contact stress and vibration. Time spent in manual material handling activities such as carrying, lifting and pushing/pulling of working carts are also estimated. A preliminary study conducted with 6 e-waste workers showed that the tool can easily be used with minimal training and good inter-observer agreement (i.e., 89% to 100%) for most risk factors assessed. This new assessment tool provides effective and flexible options for quantifying ergonomic exposures among workers engaged in unregulated, highly variable work.

Investigation of 3D dynamic and quasistatic models for spinal moments during combined manual material handling tasks

Digital human modeling software uses biomechanical models to compute workers' risk of injury during industrial work processes. In many cases, the biomechanics are calculated using quasistatic models, which neglect the body's dynamics and therefore might be erroneous. This study investigated the differential effect of using a dynamic vs. a quasistatic model on spinal loading during combined manual material handling tasks that are prevalent in industry. An experiment was conducted involving nine male and nine female participants performing a total of 3402 cycles of a box-conveying task (removing, carrying and depositing) for different box masses and shelf heights. Using motion capture data, the peak and cumulative moments acting on the L5/S1 joint were calculated using 3D dynamic and quasistatic models. This revealed that neglecting the dynamic movements (i.e., using a quasistatic model) results in an on average underestimation of 19.7% in the peak spinal moment and 3.6% in the cumulative moment that in some cases exceeds the maximal limit for the compression forces acting on the lower back.

Motor performance patterns between unilateral mechanical assistance and bilateral muscle contraction

Motor performance patterns for mechanical assistance on unilateral force control can be affected by simultaneous muscle contraction. This study investigated how muscle activity and motor performance during the cooperation between dominant-arm force control and assistive force are affected by simultaneous non-dominant arm muscle contraction with inertial loading. Eleven participants (age: 24.1 ± 1.7 years) performed trajectory-tracking task based on visual feedback of real-time isometric force control. Their force for dominant-arm elbow flexion was released from reference magnitude of 47 N to magnitude of 23.5 N by providing mechanical assistance of a linear actuator. A 47 N of inertial loading on non-dominant arm elbow flexion was conditionally provided. For four time epochs of the experimental task, we measured responses of the assisted arm in terms of: (1) surface electromyography (EMG) amplitudes of biceps brachii and triceps brachii muscles, (2) peak perturbation, and (3) motor performance of force variability and target overshoot during manual force output. Simultaneous loading on unassisted arm did not affect peak perturbation of assisted arm. However, it caused lower force variability and overshoot ratio during the time epoch of force release and higher EMG amplitudes of biceps brachii muscle during the time epochs after mechanical assistance is provided, compared to the non-loaded condition. Our results indicate that simultaneous muscle contraction affects unilateral force control with mechanical assistance aimed at enhancing motor performance by creating extra agonist muscle activity. These findings can be utilized for improving the performance of human-robot cooperation during manual material handling in many industrial sites.

Manual Material Handling Training: The Effect of Self-Observation, Hetero-Observational and Intrinsic Feedback on Workers' Knowledge and Behaviour.

This study aimed to assess the effect of systematic self-observation, hetero-observational feedback, and feedforward and intrinsic feedback (SsObserWork components) on workers’ knowledge and behaviour of a manual material handling (MMH) technique in the industrial sector. Blue-collar workers recruited from a food processing company in Catalonia (Spain) were randomized into SsObserWork (N = 31) and control (N = 30) groups. SsObserWork group members participated individually in two sessions and a three-week follow-up between sessions where they received the SsObserWork components. The control group participated individually in two sessions where they received a standard MMH training. An ad hoc instrumentcalled the MMH-SsObserWork instrument was used to assess the MMH behaviour, and an adaption of the instrument was done to assess the workers’ knowledge. Significant differences were found between groups for the identification of recommended back positions in the first session and also on comparing both sessions. However, no differences were found for the rest of the criteria. There also were significant differences between groups in the score changes of the back, knee joints, elbow joints, and interaction criterion, indicating that the SsObserWork group improved the MMH performance in these criteria (behaviour). SsObserWork intervention showed a positive effect on improving the knowledge and behaviour of the MMH technique, specifically on back posture.

중량물 취급 시 어깨 부하 평가에 대한 연구

Objective: The purpose of this study is to analyze the load on the shoulder in Manual Materials Handling (MMH).Background: According to the Korea Occupational Safety and Health Agency"s statistics on industrial injuries, Among the musculoskeletal patients in 2019, about 73.1% of patients were found to have physical pain due to the Manual Materials Handling (MMH) work process. In Korea, foreign evaluation criteria of materials handling have been employed without modification. Although a number of studies have been conducted on the degree of load on the lumbar spine (L5/S1) in materials handling, the research on the shoulder load is insufficient.Method: This study used the anthropometry data in the 1st, 50th and, 99th percentiles of Korean males aged 20 to 45. Also, 3D Static Strength Prediction Program (3DSSPP) software was used to analyze the load on the shoulder in materials handling.Results: The results of this study showed that as the horizontal distance between the worker and the center of the material increases, the load on the shoulder increases. Also, as the vertical distance increases, the load on the shoulder increases.Conclusion: The loads on the shoulder for 99th percentile male was relatively greater than those for 1st and 50th percentile male in the outstretched arm posture.Application: These results can be used as the basic data for the research of materials handling guidelines of the shoulder that considers physical characteristics for Koreans.

The effects of handle height, load's CoG height and load on lifting tasks

The effect of the load's center of gravity (CoG) on manual materials handling tasks received little attention in literature. The motivation of this study was to examine the effects of handle height, load's CoG height and load on lifting tasks. Eighteen participants performed 27 lifting tasks, including 3 handle heights (10, 30, 50 cm) by 3 load's CoG heights (10, 30, 50 cm) by 3 loads (7, 14, 21 kg). The lifting time, maximum box tilt angle, muscular activity (brachioradialis, biceps brachii, deltoid, and erector spinae), maximum CoP velocity, and lifting difficulty were measured. The results showed that lifting time and maximum box tilt angle decreased with increasing handle height. Middle handle height (30 cm) resulted in the lowest muscular activity, maximum CoP velocity, and lifting difficulty. Low load's CoG height decreased lifting time, maximum box tilt angle, muscular activity, and lifting difficulty, however, it also increased maximum CoP velocity. In addition, high load increased lifting time, maximum box tilt angle, muscular activity, maximum CoP velocity, and lifting difficulty.

The influence of age on spinal and lower limb muscle activity during repetitive lifting

This study investigated the effects of age on upper erector spinae (UES), lower erector spinae (LES) and lower body (gluteus maximus; biceps femoris; and vastus lateralis) muscle activity during a repetitive lifting task. Twenty-four participants were assigned to two age groups: ‘younger’ (n = 12; mean age ± SD = 24.6 ± 3.6 yrs) and ‘older’ (n = 12; mean age = 46.5 ± 3.0 yrs). Participants lifted and lowered a box (13 kg) repetitively at a frequency of 10 lifts per minute for a maximum of 20 min. EMG signals were collected every minute and normalised to a maximum voluntary isometric contraction. A submaximal endurance test of UES and LES was used to assess fatigue. Older participants showed higher levels of UES and LES muscle activity (approximately 12–13%) throughout the task, but less fatigue compared to the younger group post-task completion. When lifting, lower-limb muscle activity was generally higher in older adults, although temporal changes were similar. While increased paraspinal muscle activity may increase the risk of back injury in older workers when repetitive lifting, younger workers may be more susceptible to fatigue-related effects. Education and training in manual materials handling should consider age-related differences when developing training programmes.

A cross-sectional survey of musculoskeletal disorder hazard exposures and self-reported discomfort among on-shore wind turbine service technicians

Background Servicing and maintaining wind turbines may expose wind turbine technicians (wind techs) to musculoskeletal disorder (MSD) hazards. We aimed to characterise MSD hazard exposures and identify work elements that should be prioritised for MSD prevention efforts. Methods A cross-sectional online survey methodology gathered data from 144 wind techs based on a convenience, non-probability sampling approach. The survey was developed using resources from the Ontario MSD Prevention Guideline, where cognitive interviewing yielded wind tech specific modifications. Results Climbing was the most physically demanding task, followed by torqueing/tensioning and manual materials handling (MMH). However, working in awkward and constrained postures emerged as the task most likely to cause or aggravate discomfort. Conclusions Injecting ergonomic and human factors principles into wind turbine design should be a high priority. Re-engineering tools like torque tensioning devices may reduce MSD hazard exposures associated with tasks including torqueing/tensioning and MMH. Practitioner Summary We know little about musculoskeletal disorder (MSD) hazards associated with green jobs. By surveying wind turbine technicians, we learned that MSD hazards exists, and can be addressed by better considering human factors/ergonomics principles in the design of wind turbines and the tools required for service and maintenance operations. Abbreviations: MSD: musculoskeletal disorder; MMH: manual materials handling; Wind techs: wind turbine technicians; CRE-MSD: centre of research expertise for the prevention of musculoskeletal disorders; CanWEA: Canadiarn wind energy association; HFE: human factors/ergonomics; ASME: American Society of Mechanical Engineers; CSA: Canadian Standards Association

Working and Resting Period based on Inclination, Loads, and Lift Methods on Manual Material Handling in Mining Environment

Working and Resting Period based on Inclination, Loads, and Lift Methods on Manual Material Handling in Mining Environment

A forecasting framework for predicting perceived fatigue: Using time series methods to forecast ratings of perceived exertion with features from wearable sensors

Advancements in sensing and network technologies have increased the amount of data being collected to monitor the worker conditions. In this study, we consider the use of time series methods to forecast physical fatigue using subjective ratings of perceived exertion (RPE) and gait data from wearable sensors captured during a simulated in-lab manual material handling task (Lab Study 1) and a fatiguing squatting with intermittent walking cycle (Lab Study 2). To determine whether time series models can accurately forecast individual response and for how many time periods ahead, five models were compared: naïve method, autoregression (AR), autoregressive integrated moving average (ARIMA), vector autoregression (VAR), and the vector error correction model (VECM). For forecasts of three or more time periods ahead, the VECM model that incorporates historical RPE and wearable sensor data outperformed the other models with median mean absolute error (MAE) <1.24 and median MAE <1.22 across all participants for Lab Study 1 and Lab Study 2, respectively. These results suggest that wearable sensor data can support forecasting a worker’s condition and the forecasts obtained are as good as current state-of-the-art models using multiple sensors for current time prediction.

Comparison of different lifting analysis tools in estimating lower spinal loads – Evaluation of NIOSH criterion

Excessive loads on the human spine is recognized as a risk factor for back injuries/pain. Various lifting analysis tools such as musculoskeletal models, regression equations and NIOSH (National Institute for Occupational Safety and Health) lifting equation (NLE) have been proposed to evaluate and mitigate associated risks during manual material handling activities. Present study aims to compare predicted spinal loads from 5 different lifting analysis tools as well as to critically evaluate the NIOSH recommended weight limit (RWL). Spinal loads were estimated under different symmetric/asymmetric lifting tasks in which hand-load mass at each task was set based on RWL from NLE. Estimated intradiscal pressures (IDPs) of various tools were also compared with in vivo measurements. We compared RWL by NLE versus our estimations of RWL calculated from our regression equations using biomechanical criteria (compression <3400 N with/without shear <1000, 1250 or 1500 N). Our regression equations followed by OpenSim, AnyBody, simple polynomial and 3DSSPP satisfactorily predicted L4-L5 IDPs. Lifting analysis tools estimated comparable spinal compression forces (mean Pearson’s r = 0.80; standard deviation of relative difference = 26%) while in shear, differences were greater (mean Pearson’s r = 0.68; standard deviation of relative difference = 56%). NLE estimations of RWL were conservative in comparison with our estimations for lean individuals (BMI < 25 kg/m2) when compression <3400 N and shear <1250 N were considered as the biomechanical criteria. For heavier individuals, however, NLE estimations of RWL generated spinal compression >3400 N (NIOSH biomechanical safety threshold) as well as shear >1000 N. Although RWLs estimated by NLE was body weight independent, body weight substantially altered RWLs estimated from our regression equations. For improved estimation of the risk of injury, more accurate failure criteria for spinal segments are essential.

Improving sustainability in combined manual material handling through enhanced lot-sizing models

Lot-sizing models play an important role in optimizing the performance of internal logistics systems that involve a large amount of manual material handling (MMH) tasks. The performance of MMH tasks should be assessed using multiple criteria rather than being merely cost-oriented, considering the fact that the lot size affects the workload and can result in work-related musculoskeletal disorders (WMSDs). This study aims to integrate biomechanical and physiological guidelines into a cost-based performance optimization model of MMH tasks. In this study, we consider the impact of lot size on lifting frequency, which is reflected in the Composite Lifting Index (CLI), an extension of the National Institute for Occupational Safety and Health (NIOSH). In addition, the energy expenditure rates of operators are estimated by applying an established physiological method. The energy expenditure results are used to calculate rest allowance during a handling process that help keep workload levels acceptable. To make the model more general, we consider different manual material shipping scenarios and intermodal replenishment cases. Finally, a sustainable lot-sizing model is applied in a two-stage intermodal replenishment case and several numerical experiments to determine the influence of item weight, speed, distance, and opportunity cost. The results indicate that the proposed model can ease the ergonomic strain of operators without compromising economic efficiency.