Ovako Working Posture Analysis System Research Articles

Comparing risk assessment methods for work-related musculoskeletal disorders with in vivo joint loads during manual materials handling

The validity of observational methods in ergonomics is still challenging research. Criterion validity in terms of concurrent validity is the most commonly studied. However, studies comparing observational methods with biomechanical values are rare. Thus, the aim of this study is to compare the Ovako Working Posture Analysing System (OWAS) and the Rapid Entire Body Assessment (REBA) with in vivo load measurements at hip, spine, and knee during stoop and squat lifting of 14 participants. The results reveal that OWAS and REBA action levels (AL) can distinguish between different in vivo load measurements during manual lifting. However, the results also reveal that the same OWAS- and REBA-AL do not necessarily provide equal mean values of in vivo load measurements. For example, resultant contact force in the vertebral body replacement for squat lifting ranged from 57% body weight (%BW) in OWAS-AL1 to 138%BW in OWAS-AL3 compared to 46%BW in REBA-AL0 and 173%BW in REBA-AL3. Furthermore, the results suggest that the performed squat lifting techniques had a higher risk for work-related musculoskeletal disorders than the performed stoop lifting techniques.

A Physical Fatigue Evaluation Method for Automotive Manual Assembly: An Experiment of Cerebral Oxygenation with ARE Platform

Due to the complexity of the automobile manufacturing process, some flexible and delicate assembly work relies on manual operations. However, high-frequency and high-load repetitive operations make assembly workers prone to physical fatigue. This study proposes a method for evaluating human physical fatigue for the manual assembly of automobiles with methods: NIOSH (National Institute for Occupational Safety and Health), OWAS (Ovako Working Posture Analysis System) and RULA (Rapid Upper Limb Assessment). The cerebral oxygenation signal is selected as an objective physiological index reflecting the human fatigue level to verify the proposed physical fatigue evaluation method. Taking auto seat assembly and automobile manual assembly as an example, 18 group experiments were carried out with the ARE platform (Augmented Reality-based Ergonomic Platform). Furthermore, predictions of metabolic energy expenditure were performed for experiments in Tecnomatix Jack. Finally, it is concluded that the proposed physical fatigue evaluation method can reflect the human physical fatigue level and is more accurate than the evaluation of metabolic energy consumption in Tecnomatix Jack because of the immersion that comes with the AR devices and the precision that comes with motion capture devices.

Identifikasi Potensi Musculoskeletal Disorders (MSDs) pada Para Pekerja di Konveksi AA

AA Convection is a small household-scale industry that produces jeans for children. Almost the entire production process at the AA convection is manual handling. Therefore, it is necessary to identify work postures at work stations to determine the risk of injury or musculoskeletal disorders (MSDs). To identify working posture, a method is needed, one of which is the Ovako Working Posture Analysis System (OWAS) method used to identify MSDs from inappropriate work activities. This study aims to identify the risk level of MSDs. On sewing and packing work and recommending work position improvements to reduce MSD complaints to workers at AA Convection. The results of this study indicate that the risk of MSDs in sewing and packing work has the same ergonomic status, with a risk level of 2nd order, which means that action is needed for some time to come. The recommendation for improving work position in sewing work is to redesign tables and chairs according to the height of workers. While the recommendation for improving work posture in packing work is to provide work desks and chairs that can also be adjusted to body height to reduce complaints and the level of risk of MSDs.

Prevalence of musculoskeletal disorders and postural analysis of beekeepers

Work-related musculoskeletal disorders (WRMSDs) lead to fatigue and decreased productivity in workers, resulting in the need for many affected individuals to seek medical treatment annually. Beekeepers, like other agricultural workers, are susceptible to WRMSDs due to the continuous demands of their work and the repetitive movements involved. Thus, the objective of this study is to determine the prevalence of WRMSDs and assess the level of risk associated with different postures among beekeepers to improve their musculoskeletal health. To achieve this, a cross-sectional study was conducted involving 33 beekeepers, consisting of two stages. Firstly, the Nordic Questionnaire was utilized to assess the prevalence of WRMSDs. Subsequently, the Ovako Working Posture Analysis System (OWAS) was employed to analyze and categorize the riskiest postures into four levels of corrective measures. The findings indicate that the most commonly affected areas were the back (51.5%) and waist (45.4%). The occurrence of WRMSDs in various body regions was significantly associated with the beekeepers’ years of experience and weekly working hours. Additionally, the prevalence of neck and back pain was significantly related to their body mass index (BMI). The OWAS postural analysis revealed that the back (36.75%) and arm (21.08%) regions required corrective measures as soon as possible (level III), while the back (26.47%) and legs (14.70%) fell under the category of corrective measures needed in the near future (level II). Combining the postural analysis results, 28.43% were classified as Action Levels (AL) II, 37.73% as level III, and 0.98% as level IV. This study demonstrates that WRMSDs are relatively common among beekeepers, primarily due to their extensive work experience and the adoption of awkward postures during their tasks. As a result, recommendations regarding ergonomics and physiotherapy are provided to alleviate pain and reduce the strain on critical postures.

ANALISIS ERGONOMIS PADA ALAT MINI CULTIVATOR PENGOLAH LAHAN PERTANIAN BERDASARKAN METODE NBM DAN OWAS

This research aims to: (1) Analyzing the ergonomics of mini cultivator tools based on the Nordic Body Map (NBM) method, and (2) Analyzing the ergonomics of mini cultivator tools based on the Ovako Working Posture Analysis System (OWAS) method. The method in this study was experimental, and the data were analyzed by quantitative descriptive method. The research sample amounted to 5 farmers. The results showed that in the initial posture, namely the upright back position, a score of 1122 category 1 was obtained, which means that the posture is not dangerous and does not need to be improved. In the work posture when running the mini cultivator tool, a score of 2173 category 3 is obtained, which means that the straight work posture must be improved immediately. The results of filling out the NBM questionnaire show that farmers still feel "a little sick" in straight work postures. Meanwhile, the turning posture obtained a score of 4173 category 3 which means that immediate improvement is needed. The results of filling out the NBM questionnaire show that farmers still feel "very sick" in the turning posture. Thus, the mini cultivator tool still needs improvement in several aspects of ergonomics and is discussed in the results of this study

Ergonomics assessment of the overhead maintenance of vehicle-mounted radar antenna using digital human modelling

The maintenance of vehicle-mounted radar antenna (VMRA) is a typical overhead work by manual handling, where exertions, awkward postures and approaching the ends of range of motion are often necessitated. When performing the maintenance tasks, workers are likely to be exposed to work-related musculoskeletal disorders (WMSDs), which may generate impingement, rotator cuff injury, tendonitis, and localized muscle fatigue. To reduce the occurrence probability of WMSDs and provide effective suggestions for workers in the maintenance of VMRA, digital human modelling (DHM) is employed to evaluate, interpret, and visualize the negative impacts resulting from improper working posture. Based on task simulation builder (TSB), several methods are employed and integrated for ergonomics assessment of the maintenance of VMRA, including metabolic energy expenditure (MEE) rate, comfortability of upper limb joints, working posture analysis with Ovako working posture analysis system (OWAS), and working risk analysis with rapid upper limb assessment (RULA). Ergonomics assessment results are as follows: (1) screwing out bolts results in the most total metabolic cost; (2) disassembly sequence 4 → ​3 → 2 ​→ ​1 contributes to the highest comfortability of upper limb joints; (3) the discomfort rating of working posture is high, and upper arm and neck face the greatest risk of exposure in the maintenance of VMRA.

Analysis of Working Postures in Rubber Manufacturing Industry by using OWAS and RULA Methods

The basic conditions of working in a healthy and safe workplace are to design the job in accordance with the anthropometric measurements, body strength and personal characteristics of the person, to ensure that the materials, machinery and equipment used in the working process are suitable for the employee's capacity, and to provide an environment that will produce positive psycho-social results. Correct analysis methods should be used and evaluated in order to meet this basic requirement. Identifying the negative effects of working postures, taking corrective measures and improving them is a critical step of an efficient working environment. Working postures that are not properly analyzed cause strain on workers and even discomfort. It provides important contributions in the field of analyzing and improving working postures with scientific methods, controlling work performance and reducing musculoskeletal disorders (MSDs). OWAS (Ovako Working Posture Analyzing System) and RULA (Rapid Upper Limb Assessment) are successfully applied in various fields in the analysis of working postures. In this study, it was aimed to determine the MSDs risk levels of the workers working in the rubber industry by OWAS and RULA methods and measures were proposed for these risks. While OWAS analysis was obtained by using expert opinions in the study, CATIAV5R20 program was used for RULA analysis. The study includes the examination of 5 different postures in total. In the OWAS and RULA results of the study, it was seen that the most risky postures are attach the rubber hose to the cores and to place the rubber hoses attached to the cores in the autoclave. The results of the analysis showed that the RULA method is more suitable and reliable than the OWAS method for the analysis of the tasks in the vulcanization process workstations.

Modeling and evaluation of ergonomic risks and controlling plans through discrete-event simulation

Ergonomic risks due to repetitive, awkward and physically demanding operations in construction pose a serious threat to the health and safety of workers, stimulating the need to decide an appropriate measure to control them. This paper introduces a discrete-event simulation (DES)-based platform to model and evaluate the ergonomic risks and the controlling plans for construction processes. The ergonomics theories about energy expenditure for the fatigue, the Ovako Working Posture Analyzing System (OWAS) for the work-related musculoskeletal disorders (WMSDs), and the dynamic productivity of a worker related to his ergonomic risk level are utilized. The activity-based strategy of the DES methodology is incorporated with relevant ergonomics theories to achieve the modeling and simulation platform. Justification and application of the proposed method are presented through a construction case. This study contributes a DES methodology through incorporating the activity-based strategy with the ergonomics, facilitating effective management on workers' health without losing the construction performance.

Improvement of working posture in the metal casting industry to prevent musculoskeletal disorders

Less ergonomic work postures such as bending and squatting have the potential to pose work risks. When muscles receive static loads repeatedly and for a long time, it causes complaints of damage to joints, ligaments, and tendons commonly referred to as musculoskeletal disorders (MSDs) or injuries to the musculoskeletal system. This study aimed to determine the level of risk of work postures performed by workers in each work activity using the Rapid Entire Body Assessment (REBA) and Ovako Working Posture Analysis System (OWAS) methods and provide suggestions for improving work postures to minimise the occurrence of work risks. The research was conducted at the foundry of metal in the Casting section. Initial data in the form of Nordic Body Map (NBM) questionnaire data used to determine complaints in the musculoskeletal system and data in the form of image documentation on each work activity used as material for analysing the assessment of the REBA and OWAS methods. Proposals for improving the working posture were given in the form of adding foundations for moulding and pattern-making activities, the design of tools for metal liquid pouring activities, and furnace designs for metal smelting. Proposals for improving the working posture were given in the form of adding foundations for moulding and pattern making, the design of tools for metal liquid pouring, and furnace designs for metal smelting.

Risk Evaluation of Musculoskeletal Disorders and Design of Lifting-carrying Facilities

There are main activities of the worker in UD Askan such as splitting the fish, carrying, and lifting the tubs. Work activities are done manually and the production process continually undergoes. The frequency of activity (15 cycles) in a day causes the risk of fatigue, injury, and Musculoskeletal Disorders (MSDs). Evaluation of the work posture of four workers by Ovako Working Posture Analysis System (OWAS) and Job Strain Index (JSI) methods showed high risk in the process of lifting and carrying a tank. The previous posture caused the worker to bend forward, both legs standing or squatting with both knees, and walk by carrying a tub. The results recommend solving soonest due to the danger to the musculoskeletal. The recommendation shows that lifting methods are required and the design of lifting and transporting equipment is needed. The evaluation posture by OWAS show that the process of carrying a tank is 3 level (immediate repair because it is harmful to the musculoskeletal), and after improvement, it is 1 level (not harmful to the musculoskeletal). Then, JSI indicates any improvement from the 3 levels (posing a hazard) to level 1 (safe work).

Prediction of Ergonomic Risks and Impacts on Construction Schedule through Agent-Based Simulation

Construction workers are vulnerable to excessive workloads that may cause ergonomic risks, disturbing the construction schedule. Hence, ergonomic risks and the responding measures for mitigating them, namely ergonomic measures, need to be predicted and assessed so as to help make decisions about management policies. This study focuses on agent-based simulation to predict ergonomic risks and impacts of ergonomic measures on the construction schedule (ERIEMCS) along with the construction process consisting of physical or light tasks. Workers are regarded as the agents and their behaviors in performing tasks and ergonomic measures are modeled by considering different physical capacities due to different workers’ ages. Energy expenditure–based fatigue quantification and the Ovako working posture analyzing system (OWAS) –based quantification of work-related musculoskeletal disorder (WMSD) risk for an individual worker are the basis for quantitative prediction of the fatigue and the WMSD risks of a crew undertaking the construction process through agent-based simulation. An application study based on a prefabricated construction project is presented to demonstrate and justify the proposed method. The results indicate that ergonomic risks can be effectively reduced by adopting ergonomic measures to balance mitigating such risks and maintaining productivity. Prediction of the ERIEMCS through agent-based simulation prior to commencement of work facilitates investigating the effects of aging workers and planning their working schedules using ergonomic measures in combination with schedule management. This study contributes to the body of knowledge on simulation-based methodology for applying ergonomics in construction management, which is especially meaningful given the trend of labor aging and the direction of industrialization in construction.

Postural strain of spinner and casting workers of a small-scale aluminium utensil making factory

Background: Small scale establishments often neglect the worker safety and comfort which impacts both productivity and workers’ safety. Various studies have been conducted in such small-scale establishments but not much has been done on aluminium utensil manufacturing factories. Spinning and casting are two important processes for manufacturing of aluminium utensils. But not much has been studied to assess the hazards of the involved workers. The present study is an attempt to explore this previously unnoticed area. Methods: The study was conducted in different small scale aluminium utensil factories in West Bengal. Sixteen spinners and seventeen casting workers were evaluated for this study. The analysis of posture was done by rapid upper limb assessment (RULA), rapid entire body assessment (REBA) and Ovako working posture analysis system (OWAS). The body parts discomfort was assessed by using Cornell musculoskeletal discomfort questionnaire and Nordic questionnaire was also used to assess the pain they experience. Results: All the casting workers are experiencing postural load beyond the recommended limit whereas in case of spinner, five workers experienced less postural load due to favorable work conditions. Casting workers mainly suffered from low back, neck, right shoulder pain whereas spinners suffered from wrist and finger pain followed by lower extremity pain. Conclusions: Both group of workers are experiencing postural load and discomfort. In case of casting workers, the prevalence was high and immediate interventions are needed. The discomfort is particularly high during the end of shifts.

Does Motor Manual Pine Oleoresin Tapping Bring Work-Related Musculoskeletal Disorders Risk to the Tappers? (RoM, REBA, RULA, and OWAS Based Postural Analysis)

Rosin and turpentine oil are commercially developed non-timber forest products generated from pine oleoresin. In Indonesia, the Quarre method is utilized to tap manually or motor-manually (using handheld tapping machines). Handheld tapping machines can greatly boost productivity on the work, but they may also pose serious risks to workers’ health. This study aimed to examine the work-related musculoskeletal disorders (WMSDs) risk of motor-manual tapping by using four postural analysis instruments: Natural Range of Motion (RoM), Rapid Entire Body Assessment (REBA), Rapid Upper Limb Assessment (RULA), and the Ovako Working Posture Analyzing System (OWAS). In addition to the finding that the use of handheld machines is associated with a high WMSDs risk level, particularly in the work element of renewing the tapping faces, this study demonstrated that RULA is a postural-based risk level instrument with the highest level of sensitivity when being used to assess risk levels in tapping activities involving a great deal of upper limb movements. Despite the widespread use of OWAS for emergency corrective action, this study demonstrates that OWAS has a very low level of sensitivity. For this reason, we stress the importance of using a wide range of instruments for risk assessment to get more accurate results. Keywords: Musculoskeletal disorders, pine tapping, postural analysis, risk level

CREBAS: Computer-Based REBA Evaluation System for Wood Manufacturers Using MediaPipe

Recently, musculoskeletal disorders (MSDs) caused by repetitive working postures in industrial sites have emerged as one of the biggest problems in the field of industrial health. The risk of MSDs caused by the repetitive working postures of workers is quantitatively evaluated by using NLE (NIOSH Lifting Equation), OWAS (Ovako Working-posture Analysis System), RULA (Rapid Upper Limb Assessment), REBA (Rapid Entire Body Assessment), etc. Methods used for the working posture analysis include vision-based analysis and motion capture analysis. Vision-based analysis is a method where an expert with ergonomics knowledge watches and manually analyzes recorded working images. Although the analysis is inexpensive, it takes a lot of time to analyze. In addition, the analyst’s subjective opinions or mistakes may be reflected in the results, so it may be somewhat unreliable. On the other hand, motion capture analysis can obtain more accurate and consistent results, but its measurement equipment is very expensive and it requires a large space for measurement. In this paper, we propose a computer-based automated REBA system that can evaluate, automatically and consistently, working postures in order to supplement the shortcomings of these existing methods. The CREBA system uses the body detection learning model of MediaPipe to detect the worker’s area in the recorded images and sets the body area based on the position of the face, detected using the face tracking learning model. In the set area, the positions of joints are tracked using the posture tracking learning model, and the angles of joints are calculated based on the joint positions using the inverse kinematics, and then by automatically calculating the degree of load of the working posture with the REBA evaluation method. In order to verify the accuracy of the evaluation results of the CREBA system, we compared them with the experts’ vision-based REBA evaluation results. The result of the experiment showed a slight difference of about 1.0 points between the evaluation results of the expert group and those of the CREBA system. It is expected that the ergonomic analysis method for the working posture used in this study will reduce workers’ labor intensity and improve their safety and efficiency.

Analysis of Working Posture in Mathadi Workers using the Computerized Ovako Working Posture Analysing System (OWAS)

Background: Navi Mumbai holds a large-scale market in Vashi that is the APMC market. Hence, several mathadi workers work there on regular basis. Purpose: The analysis was done to identify the working posture of the mathadi workers and whether they require any changes or not Method: Sixty mathadi workers who had spent at least one year on the job participated in this survey. They were recruited by non-probability sample of convenience from APMC market situated in Navi mumbai.

Classification of body postures using smart workwear

BackgroundDespite advancing automation, employees in many industrial and service occupations still have to perform physically intensive work that may have negative effects on the health of the musculoskeletal system. For targeted preventive measures, precise knowledge of the work postures and movements performed is necessary.MethodsPrototype smart work clothes equipped with 15 inertial sensors were used to record reference body postures of 20 subjects. These reference postures were used to create a software-based posture classifier according to the Ovako Working Posture Analysing System (OWAS) by means of an evolutionary training algorithm.ResultsA total of 111,275 posture shots were recorded and used for training the classifier. The results show that smart workwear, with the help of evolutionary trained software classifiers, is in principle capable of detecting harmful postures of its wearer. The detection rate of the evolutionary trained classifier (bar{a}_{ccr} = 0.35 for the postures of the back, bar{a}_{ccr} = 0.64 for the arms, and bar{a}_{ccr} = 0.25 for the legs) outperforms that of a TensorFlow trained classifying neural network.ConclusionsIn principle, smart workwear – as prototypically shown in this paper – can be a helpful tool for assessing an individual’s risk for work-related musculoskeletal disorders. Numerous potential sources of error have been identified that can affect the detection accuracy of software classifiers required for this purpose.

Cost and Workload Assessment of Agricultural Drone Sprayer: A Case Study of Rice Production in Japan

The shortage of labor is one of the major challenges facing agriculture in Japan. Technological innovations are required to overcome the limitations of the workload per worker. One such innovation is smart agriculture, which utilizes advanced technologies such as robots, AI, and IoT. This study aimed to provide data on the workload and pest control costs for the development of sustainable agriculture. The cost of pest control was compared between a boom sprayer, power sprayer, and unmanned aerial vehicles (UAVs) for two model rice farmers. The Ovako Working Posture Analysis System (OWAS) and metabolic equivalent (METs) were used to measure workloads while using UAVs. The labor cost was reduced to half with the usage of UAVs compared with conventional machines. The resulting METs, or physical activity during pest-control work using UAVs, could be lower than those when using pest control machines. Through OWAS, 63.86% of the total jobs using UAVs were identified as having a low risk of musculoskeletal injury. The results suggest that UAVs could compensate for the shortage of workers, and these are effective tools to support the expansion of the agricultural area.

Ergonomic problems in agricultural farms: Explainable relationship between awkward postures and body discomforts in Iranian leafy vegetable cultivation.

Many agricultural activities excessively need human power and are associated with musculoskeletal disorders (MSDs). Leafy vegetable cultivation (LVC) is one of these. The postural workload, body discomfort, and explainable linkage between these among Iranian wintry LVC workers were investigated. Postures and body discomfort were evaluated using Ovako working posture analyzing system (OWAS) and a body map, respectively. The explainable body discomforts by working postures for each body region were descriptively discussed using some of the literature. Considering the maximum MSD risk value of 400%, irrigation and manual harvesting had the highest MSD risks with index risks of 313% and 305% respectively. Low back discomfort was the most common body discomfort in LVC which was reported for the operations of moldboard plowing, disking, manure application, chemical broadcasting, spraying, and manual harvesting. LVC operations seemed to rely heavily on the use of low back and shoulders. Bent and/or twist postures were the most common postures for the back. Almost all the body discomforts were explained by awkward postures shown by postural workload analysis. Therefore, the working posture analysis results may be reliable and utilized in future decisions around ergonomic interventions. Future studies may be conducted to investigate the simple and inexpensive ergonomic interventions to mitigate MSD risks.

An investigative sensitivity study of Ovako working posture analyzing system (OWAS)

The purpose of this study is to investigate the sensitivity of the Ovako working posture analyzing system. This paper also focuses on the identification of insensitive and highly sensitive posture zones. The OWAS sensitivity analysis, together with the ordinal regression analysis, offers deeper insights into the methodology for assessing posture. A full factorial design was used to account for all possible combinations of body members. To assess the sensitivity, one parameter of the body part was changed while other parameters were left unchanged to understand its effect on the output score. Combinations of postures in which no change was observed and corresponding ranges were noted. Posture ratings with sudden jumps were also noted. Ordinal regression analysis was performed to identify the body variable with the greatest impact and its weight in estimating the OWAS action category. Ergonomic practitioners can be made aware of insensitive and sensitive zones when assessing posture.

Systematic Comparison of OWAS, RULA, and REBA Based on a Literature Review.

This study aimed to systematically compare three representative observational methods for assessing musculoskeletal loadings and their association with musculoskeletal disorders (MSDs): Ovako Working Posture Analysis System (OWAS), Rapid Upper Limb Assessment (RULA), and Rapid Entire Body Assessment (REBA). The comparison was based on a literature review without time limitations and was conducted on various factors related to observational methods. The comparisons showed that although it has a significant limitation of comprising only two classifications for the leg postures, (1) the RULA is the most frequently used method among the three techniques; (2) many studies adopted the RULA even in evaluation of unstable lower limb postures; (3) the RULA assessed postural loads as higher risk levels in most studies reviewed in this research; (4) the intra- and inter-reliabilities for the RULA were not low; and (5) the risk levels assessed by the RULA were more significantly associated with postural load criteria such as discomfort, MHTs and % capable at the trunk, and MSDs.