A comparison of risk assessment of single and combination manual handling tasks: 3. Biomechanical measures

Anecdotal evidence suggests organisations experience difficulty assessing the risk in manual handling tasks. One reason for this difficulty may be that many common tasks are a combination of lift, lower, push, pull and carry tasks. No prior reports of attempts to assess the risk in combination tasks using biomechanical measures could be found. The aim of the study was to compare the risks assessed in single manual handling tasks with those in combination tasks. Nine male and nine female students performed combination and single handling tasks. The force applied by subjects to a box was recorded and, together with kinematic data on subject posture collected via video, used in a twodimensional dynamic model to estimate the lumbar compression force and lumbar shear force. The hand force, peak lumbar compression force and peak lumbar shear force for each combination task were each compared with the same variable for the single tasks which comprised the combination, using repeated measured analysis of variance with specific contrasts. In at least one of the twelve comparisons performed for each dependent variable, the combination task value was significantly different to the single task value. It is concluded that the risk in combination manual handling tasks can not be accurately assessed by using estimates based on biomechanical measures of single tasks.     

The development of a model to predict the effects of worker and task factors on foot placements in manual material handling tasks

Accurate prediction of foot placements in relation to hand locations during manual materials handling tasks is critical for prospective biomechanical analysis. To address this need, the effects of lifting task conditions and anthropometric variables on foot placements were studied in a laboratory experiment. In total, 20 men and women performed two-handed object transfers that required them to walk to a shelf, lift an object from the shelf at waist height and carry the object to a variety of locations. Five different changes in the direction of progression following the object pickup were used, ranging from 45° to 180° relative to the approach direction. Object weights of 1.0 kg, 4.5 kg, 13.6 kg were used. Whole-body motions were recorded using a 3-D optical retro-reflective marker-based camera system. A new parametric system for describing foot placements, the Quantitative Transition Classification System, was developed to facilitate the parameterisation of foot placement data. Foot placements chosen by the subjects during the transfer tasks appeared to facilitate a change in the whole-body direction of progression, in addition to aiding in performing the lift. Further analysis revealed that five different stepping behaviours accounted for 71% of the stepping patterns observed. More specifically, the most frequently observed behaviour revealed that the orientation of the lead foot during the actual lifting task was primarily affected by the amount of turn angle required after the lift (R(2) = 0.53). One surprising result was that the object mass (scaled by participant body mass) was not found to significantly affect any of the individual step placement parameters. Regression models were developed to predict the most prevalent step placements and are included in this paper to facilitate more accurate human motion simulations and ergonomics analyses of manual material lifting tasks. STATEMENT OF RELEVANCE: This study proposes a method for parameterising the steps (foot placements) associated with manual material handling tasks. The influence of task conditions and subject anthropometry on the foot placements of the most frequently observed stepping pattern during a laboratory study is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses and improved biomechanical job evaluations.     

The development of a model to predict the effects of worker and task factors on foot placements in manual material handling tasks

Accurate prediction of foot placements in relation to hand locations during manual materials handling tasks is critical for prospective biomechanical analysis. To address this need, the effects of lifting task conditions and anthropometric variables on foot placements were studied in a laboratory experiment. In total, 20 men and women performed two-handed object transfers that required them to walk to a shelf, lift an object from the shelf at waist height and carry the object to a variety of locations. Five different changes in the direction of progression following the object pickup were used, ranging from 45° to 180° relative to the approach direction. Object weights of 1.0 kg, 4.5 kg, 13.6 kg were used. Whole-body motions were recorded using a 3-D optical retro-reflective marker-based camera system. A new parametric system for describing foot placements, the Quantitative Transition Classification System, was developed to facilitate the parameterisation of foot placement data. Foot placements chosen by the subjects during the transfer tasks appeared to facilitate a change in the whole-body direction of progression, in addition to aiding in performing the lift. Further analysis revealed that five different stepping behaviours accounted for 71% of the stepping patterns observed. More specifically, the most frequently observed behaviour revealed that the orientation of the lead foot during the actual lifting task was primarily affected by the amount of turn angle required after the lift (R ² = 0.53). One surprising result was that the object mass (scaled by participant body mass) was not found to significantly affect any of the individual step placement parameters. Regression models were developed to predict the most prevalent step placements and are included in this paper to facilitate more accurate human motion simulations and ergonomics analyses of manual material lifting tasks.

Statement of Relevance: This study proposes a method for parameterising the steps (foot placements) associated with manual material handling tasks. The influence of task conditions and subject anthropometry on the foot placements of the most frequently observed stepping pattern during a laboratory study is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses and improved biomechanical job evaluations.     

Assessment of factors considered to be important in handling tasks by expert handlers

Twenty-eight experienced handlers, considered the best in two transport companies, were interviewed using a questionnaire consisting of partially closed-ended questions. They had to assess 20 videotape handling sequences showing two different handling methods to determine, for 10 factors and overall, which one was the best. They were asked about the inportance of these factors in their choices of the best method. The aims of the study were to verify whether there was a consensus among experienced handlers as to what was a good handling method and to identify the factors taken into consideration by them. Results show the lack of consensus on the best methods. Handlers favor different strategies depending on the worjk context and their own priorities.     

Applications of nonlinear finite element method to contact problems and paper handling problems

A model that predicts the paper behavior during the printing process at various time intervals is proposed. The tendency of wrinkling can therefore be observed. This model will accommodate any paper topology induced by moisture effects or otherwise, and can analyze virtually any roll geometry and roll combinations.Nonlinear Finite Element Method is applied to the contact problem of two layered cylinders compressing a paper with arbitrary initial shape. The analysis assumed plane strain condition, the paper can therefore be treated as a beam. The result from the contact problem is applied to predict the behavior of the paper as it is feeding through the roll system. The Total Lagrange Formulation with Piola-Kirchoff Stress and Green-Lagrange strained is used. The quasi-static solution at different time intervals is presented. It was found that they agreed favorably with experiments.     

A comparison of risk assessment of single and combination manual handling tasks: 2. Discomfort,Rating of Perceived Exertion and heart rate measures

Although many manual handling activities involve combinations of pull, lift, carry, lower and push, there are few reports of investigation of how to assess the risk in these combination tasks. Two strategies have been suggested in the literature for estimating the risk in a combination task based on the measures of the separate components of that task. The aim of the study was to compare the risks assessed in single manual handling tasks with those in combination tasks. Ratings of discomfort, exertion and heart rate were collected from nine male and nine female students, performing combination and single tasks. Combination tasks consisted of sequences of pull, lift, carry, lower and push tasks. Combination tasks were performed at 1.min^?1 and 3.min^?1 whilst single tasks (lift, lower, push, pull and carry) were performed at 3.min^?1 and 6.min^?1. The rating of exertion and heart rate for each combination task was compared to the exertion rating and heart rate of the single tasks which comprised the combination task using repeated measures anaylsis of variance with specified contrasts. Similar comparisons for the discomfort data were performed using Friedman and Wilcoxon tests. In at least one of the twelve comparisons performed for each dependent variable, the combination task value was significantly different to each single task value. The differences occurred regardless of whether the most critical single task value or an average of all single task values was used. It was concluded that the risk in combination manual tasks can not be accurately assessed by using estimates from discomfort, exertion ratings and heart rate measures of single tasks.     

Classifying the risk of work related low back disorders due to manual material handling tasks

Work related low back disorders (LBDs) due to manual lifting tasks (MLTs) have long been recognized as one of the main occupational disabling injury that affects the quality of life of the industrial working population in the U.S. There have been a number of intensive research efforts devoted to understanding the phenomena of LBDs and building classification models that could effectively distinguish between high risk and low risk MLTs that contribute to LBDs. As of today, however, such models and the occupational exposure limits of different risk factors causing LBDs as well as the guidelines preventing them have not yet been fully proposed. One of the first efforts to comprehend the nature and phenomenon of LBDs was undertaken by Marras et al. (1993). They created a seminal data set and used it to build logistic regression (LR) models to identify significant variables and classify MLTs into high risk and low risk with respect to LBDs. Since then a number of studies have used the same data set to build and test various classifiers to detect the likelihood of LBDs due to manual material handling jobs. This paper summarizes and critiques the previous studies. It also employs this data set to build and test seven classification models, two of which have not been applied in this context yet. The parameters of the models have been calibrated for the best performance, and the models were constructed and validated on the full set and the reduced set of features. Though the performances of our best models are better than those reported in National Institute for Occupational Health and Safety (NIOHS) Guides and two of our previous studies, they are generally less optimistic than those reported in several other studies; this paper proposes a systematic and more reliable approach to creating and validating classifiers to distinguish between low and high risk MLTs that contribute to LBDs.     

An evaluation of EU legislation concerning risk assessment and preventive measures in occupational safety and health

The European Council Directive 89/391/EC of 12 June 1989 is concerned with the introduction of measures to encourage improvements in the occupational safety and health. For example, it deals with risk assessment and preventive measures. The Finnish legislation enacts the risk assessment and prevention measures in a similar way as the EU Directive 89/391/EC. The aim of this study was to examine: 1) the implementation of risk assessment process as a part of OSH management, and 2) the effectiveness of the OSH legislation concerned with risk assessment. The quantitative method involved an online questionnaire. The respondents were employers (N = 1478), workers (N = 1416) and occupational care (OHC) professionals’ units (N = 469). Three quarters of the employer respondents and two thirds of the workers and OHC service providers felt that the EU legislative provisions have promoted the engagement of the management. According to the study, improvement is needed in ensuring the cooperation between employers and workers. The combined variables of Risk Assessment Process revealed positive impacts both on Cooperation and Management Measures and on the Concrete Preventive Measures among the employers and the workers. The combined variables of Use of Documents of Risk Assessments highlighted positive impacts on both the Exploiting of Results of Risk Assessments in Planning and Management and on the Exploiting of Results of Risk Assessment in Cooperation and Technology.     

Acceptable weights and physiological costs of performing combined manual handling tasks in restricted postures

Eight healthy, male underground coal miners (mean age=36·9 yrs±4·5 SD) participated in a study examining psychophysical acceptable weights and physiological costs of performing combined lifting and lowering tasks in restricted headroom conditions. Independent variables included posture (stooping or kneeling on two knees), task symmetry (symmetric or asymmetric), and vertical lift distance (35 cm or 60cm). All tasks were 10min in duration and were performed under a 1·22 m ceiling to restrict the subject's posture. Subjects were required to raise and lower a lifting box every 10 s, and asked to adjust the box weight to the maximum amount they could handle without undue strain or fatigue. During the final 5 min of each test, data were collected to determine the energy expenditure requirements of the task. Results of this study demonstrated that psychophysical lifting capacity averaged 11·3% lower when kneeling as compared to stooping. Subjects selected 3·5% more weight in asymmetric tasks, and lifted 5·0% less weight to the 60 cm shelf compared to the 35 cm shelf. Heart rate was not significantly affected by posture, but was increased an average of 4 beats/min in asymmetric conditions, and by 3·5 beats/min while lifting/lowering to/from the high shelf. Oxygen uptake was increased by 9% when stooped, by 10% when lifting/lowering asymmetrically, and by 8·2% when performing the task to the high shelf. Results of this study indicate that, wherever possible, materials that must be lifted manually in low-seam coal mines be designed in accordance with the decreased lifting capacity exhibited in the kneeling posture.     

The design of manual handling tasks: revised tables of maximum acceptable weights and forces.

Four new manual handling experiments are reviewed. The experiment used male and female subjects to study lifting, lowering, pushing, pulling, and carrying tasks. Each experiment used a psychophysical methodology with measurements of oxygen consumption, heart rate, and anthropometric characteristics. Independent variables included task frequency, distance, height and duration; object size and handles; extended horizontal reach; and combination tasks. The results of the four experiments were integrated with the results of seven similar experiments published previously by this laboratory. The integrated data were used to revise maximum acceptable weights and forces originally published in 1978. The revised tables are presented and compared with the original tables.     

Acceptable weights and physiological costs of performing combined manual handling tasks in restricted postures

Eight healthy, male underground coal miners (mean age = 36.9 yrs +/- 4.5 SD) participated in a study examining psychophysically acceptable weights and physiological costs of performing combined lifting and lowering tasks in restricted head-room conditions. Independent variables included posture (stooping or kneeling on two knees), task symmetry (symmetric or asymmetric), and vertical lift distance (35 cm or 60 cm). All tasks were 10 min in duration and were performed under a 1.22 m ceiling to restrict the subject's posture. Subjects were required to raise and lower a lifting box every 10s, and asked to adjust the box weight to the maximum amount they could handle without undue strain or fatigue. During the final 5 min of each test, data were collected to determine the energy expenditure requirements of the task. Results of this study demonstrated that psychophysical lifting capacity averaged 11.3% lower when kneeling as compared to stooping. Subjects selected 3.5% more weight in asymmetric tasks, and lifted 5.0% less weight to the 60 cm shelf compared to the 35 cm shelf. Heart rate was not significantly affected by posture, but was increased an average of 4 beats/min in asymmetric conditions, and by 3.5 beats/min while lifting/lowering to/from the high shelf. Oxygen uptake was increased by 9% when stooped, by 10% when lifting/lowering asymmetrically, and by 8.2% when performing the task to the high shelf. Results of this study indicate that, wherever possible, materials that must be lifted manually in low-seam coal mines be designed in accordance with the decreased lifting capacity exhibited in the kneeling posture.     

Optimizing the stretch of independent tasks on a cluster: From sequential tasks to moldable tasks

This paper addresses the problem of scheduling non-preemptive moldable tasks to minimize the stretch of the tasks in an online non-clairvoyant setting. To the best of the authors’ knowledge, this problem has never been studied before. To tackle this problem, first the sequential subproblem is studied through the lens of the approximation theory. An algorithm, called DASEDF, is proposed and, through simulations, it is shown to outperform the first-come, first-served scheme. Furthermore, it is observed that machine availability is the key to getting good stretch values. Then, the moldable task scheduling problem is considered, and, by leveraging the results from the sequential case, another algorithm, DBOS, is proposed to optimize the stretch while scheduling moldable tasks. This work is motivated by a task scheduling problem in the context of parallel short sequence mapping which has important applications in biology and genetics. The proposed DBOS algorithm is evaluated both on synthetic data sets that represent short sequence mapping requests and on data sets generated using log files of real production clusters. The results show that the DBOS algorithm significantly outperforms the two state-of-the-art task scheduling algorithms on stretch optimization.     

Path deformation method for robot motion planning problems in the presence of obstacles

This paper studies the following path planning problem for a robot. There is a given path avoiding obstacles. If existing obstacles change their location or new obstacles appear, the preplanned path must be appropriately deformed for all obstacles avoidance. We develop a solution approach based on the component-wise method of smoothing the path curvature and the method of potentials. The proposed approach enables to avoid obstacles and smooth the path and its curvature (in the 2D and 3D cases).     

Physical training: a tool for increasing work tolerance limits of employees engaged in manual handling tasks

The lack of physical fitness is a contributing factor to the etiology of musculoskeletal disorders resulting from the manual handling of material in industry. Thus the major objectives of this paper were (1) to discuss the role of physical fitness in the control of occupational injuries; (2) to review techniques available in the exercise physiology literature for increasing human physical capacity in industry; and (3) to review and evaluate studies on the effects of physical training on individuals engaged in manual handling tasks.     

Foot motions in manual material handling transfer tasks: A taxonomy and data from an automotive assembly plant

Ergonomic job analysis commonly applies static postural and biomechanical analysis tools to particular postures observed during manual material handling (MMH) tasks, usually focusing on the most extreme postures or those involving the highest loads. When these analyses are conducted prospectively using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses. In automotive assembly jobs, workers frequently take several steps between task elements, for example, picking up a part at one location and moving to another location to place it on the vehicle. A detailed understanding of the influence of task type and task sequence on the stepping pattern is necessary to accurately predict the foot placements associated with MMH tasks. The current study examined the patterns of foot motions observed during automotive assembly tasks. Video data for 529 pickup and delivery tasks from 32 automotive assembly jobs were analysed. A minimum of five cycles was analysed for each task. The approach angle, departure angle, hand(s) used, manipulation height and patterns of footsteps were coded from the video. Object mass was identified from the job information sheet provided by the assembly plant. Three independent raters coded each video and demonstrated an intraclass correlation coefficient of 0.54 for identification of the configuration of the lower extremities during terminal stance. Based on an analysis of the distribution of stepping behaviours during object transitions (pickups or deliveries), a transition classification system (TRACS) was developed. TRACS uses a compact notation to quantify the sequence of steps associated with a MMH transition. Five TRACS behaviour groups accounted for over 90% of the transition stepping behaviours observed in the assembly plant. Approximately two-thirds (68.4%) of the object transfers observed were performed with only one foot in contact with the ground during the terminal posture. The results from this paper suggest that a predictive model for choosing a transition stepping behaviour, coupled with a model to scale the selected foot behaviours, is needed to facilitate accurate prospective ergonomic analyses. This study proposes a method for categorising the stepping patterns associated with MMH tasks. The influence of task type and task sequence on the stepping patterns observed during several automotive assembly tasks is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses.     

Foot motions in manual material handling transfer tasks: a taxonomy and data from an automotive assembly plant

Ergonomic job analysis commonly applies static postural and biomechanical analysis tools to particular postures observed during manual material handling (MMH) tasks, usually focusing on the most extreme postures or those involving the highest loads. When these analyses are conducted prospectively using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses. In automotive assembly jobs, workers frequently take several steps between task elements, for example, picking up a part at one location and moving to another location to place it on the vehicle. A detailed understanding of the influence of task type and task sequence on the stepping pattern is necessary to accurately predict the foot placements associated with MMH tasks. The current study examined the patterns of foot motions observed during automotive assembly tasks. Video data for 529 pickup and delivery tasks from 32 automotive assembly jobs were analysed. A minimum of five cycles was analysed for each task. The approach angle, departure angle, hand(s) used, manipulation height and patterns of footsteps were coded from the video. Object mass was identified from the job information sheet provided by the assembly plant. Three independent raters coded each video and demonstrated an intraclass correlation coefficient of 0.54 for identification of the configuration of the lower extremities during terminal stance. Based on an analysis of the distribution of stepping behaviours during object transitions (pickups or deliveries), a transition classification system (TRACS) was developed. TRACS uses a compact notation to quantify the sequence of steps associated with a MMH transition. Five TRACS behaviour groups accounted for over 90% of the transition stepping behaviours observed in the assembly plant. Approximately two-thirds (68.4%) of the object transfers observed were performed with only one foot in contact with the ground during the terminal posture. The results from this paper suggest that a predictive model for choosing a transition stepping behaviour, coupled with a model to scale the selected foot behaviours, is needed to facilitate accurate prospective ergonomic analyses. This study proposes a method for categorising the stepping patterns associated with MMH tasks. The influence of task type and task sequence on the stepping patterns observed during several automotive assembly tasks is discussed. For prospective postural analyses conducted using digital human models, accurate prediction of the foot placements is critical to realistic postural analyses.     

IDSSs opportunities and problems: Steps to development of an IDSS

IDSSs should contribute to the enhancement of human performance, but their effectiveness can be guaranteed only in the case of certain decision types. The issues explored in this paper show that they can help to overcome some human limitations, especially in complex data and information processes, in uncertainty management, and in coherent reasoning. Integrating human and machine expertise is clearly beneficial, nevertheless with the aim of building intelligent solutions we should not ignore the role of human factors and the problems deriving from the integration of knowledge of multiple experts. The risk is that the systems will become clumsy and vulnerable to embarrassing failures. The paper explores the opportunities for exploitation of IDSSs to provide intelligent advice, intelligent analysis and intelligent evaluation. Some suggestions for research have been proposed looking at the ideas put forward in a recent research project dealing with the development of a system supporting local government authorities on environmental impact assessment procedure.     

TROPHI: development of a tool to measure complex,multi-factorial patient handling interventions

Patient handling interventions are complex and multi-factorial. It has been difficult to make comparisons across different strategies due to the lack of a comprehensive outcome measurement method. The Tool for Risk Outstanding in Patient Handling Interventions (TROPHI) was developed to address this gap by measuring outcomes and comparing performance across interventions. Focus groups were held with expert patient handling practitioners (n = 36) in four European countries (Finland, Italy, Portugal and the UK) to identify preferred outcomes to be measured for interventions. A systematic literature review identified 598 outcome measures; these were critically appraised and the most appropriate measurement tool was selected for each outcome. TROPHI was evaluated in the four EU countries (eight sites) and by an expert panel (n = 16) from the European Panel of Patient Handling Ergonomics for usability and practical application. This final stage added external validity to the research by exploring transferability potential and presenting the data and analysis to allow respondent (participant) validation.

Practitioner Summary: Patient handling interventions are complex and multi-factorial and it has been difficult to make comparisons due to the lack of a comprehensive outcome measurement method. The Tool for Risk Outstanding in Patient Handling Interventions (TROPHI) was developed to address this gap by measuring outcomes to compare performance across interventions.     

Matrix generalized inverses in the handling of control problems containing input derivatives

A solution method using generalized matrix inverses is proposed for the following problem. Given a linear control system consisting of a plant equation and an output. equation, the latter or both containing the first derivative of the input vector. If the output vector is a given function of the time variable t, find input vectors which yield the desired output.     

Physical training: a tool for increasing work tolerance limits of employees engaged in manual handling tasks.

The lack of physical fitness is a contributing factor to the etiology of musculoskeletal disorders resulting from the manual handling of material in industry. Thus the major objectives of this paper were (1) to discuss the role of physical fitness in the control of occupational injuries; (2) to review techniques available in the exercise physiology literature for increasing human physical capacity in industry; and (3) to review and evaluate studies on the effects of physical training on individuals engaged in manual handling tasks.