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OBJECTIVE: Many studies on the efficiency and effectiveness of automated order picking systems have focused solely on system performance. Both types of goods-to-picker systems aim to reduce the picker’s travel time required to determine product locations and to move these products to meet customer requests.
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Most advanced order picking systems can be classified into automated storage and retrieval system (AS/RS) and moving robot types. Although various automated order picking technologies have been developed recently, human intervention continues to be required. The models are further employed in testing the safety and comfort level of the walking aid currently used by the participants, resulting the need of immediate changes in the device.īACKGROUND: Order picking activities are the most labor-intensive processes in retail warehouses.
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Using the Human Builder module in CATIA V5 two human models are generated with the help of anthropometric data collected from a group of >65 years old participants living in assistive care centers. The use of DHM in order to improve certain features of a system or product is not a new concept, various types of digital human models being used for over 35 years. This paper briefly presents some of the basic principles of user-centered design and their relationship to ergonomics, together with the application of digital human modeling (DHM) in the design process of an assistive walking aid for elderly users with low mobility, considering the assessment of risk and comfort of the system. The results also highlight tradeoffs in using an assist device which can decrease injury risk in some cases, while having an adverse impact on the productivity of the assembly line.Īs ergonomics has become an integral part of the design process, digital human modeling is a rapidly emerging area that links computer-aided engineering design, human factors engineering and applied ergonomics. Based on the findings of this study, the methodology appears to be appropriate for assessing and predicting potential risks associated with the design of industrial workstations and work tasks. The results suggest although using the assist device decreased injury risk potentially, use of the assist device had an adverse impact on the productivity of the assembly line. Muscle activity was also measured by wireless electromyography (EMG) in order to identify physiological indicators of stress and strain. The work tasks were decomposed into subtasks before analysis.
#Human brain mapping sci journal software
UGS™ JACK digital human modelling software was used for the computer-based ergonomic analysis to evaluate the potential injury risk of the current task, considering difference between using and not using the assist device. An optical motion capture system was setup and calibrated in the industrial workplace to collect motion data. An ergonomic risk assessment was conducted on a sample of operators performing a lifting task manually and using an assist device. The purpose of this evaluation was the development of a motion capture-based methodology for evaluating workstations to identify potential design issues that could result in musculoskeletal injury in a real work environment. This study examined an existing industrial workstation at an automobile assembly plant using computer aided ergonomics and digital human models.