In the context of industrial engineering, the predetermined time systems (PTS) play an important role in workplaces because inefficiencies are found in assembly processes that require manual manipulations. In this study, an approach is proposed with the aim to analyze time and motions in a manual process using a capture motion system embedded to a virtual environment. Capture motion system tracks IR passive markers located on the hands to take the positions of each one. For our purpose, a real workplace is virtually represented by domains to create a virtual workplace based on basic geometries. Motion captured data are combined with the virtual workplace to simulate operations carried out on it, and a time and motion analysis is completedby means of an algorithm. To test the methodology of analysis, a case study was intentionally designed using and violating the principles of motion economy. In the results, it was possible to observe where the hands never crossed as well as where the hands passed by the same place. In addition, the activities done in each zone were observed and some known deficiencies were identified in the distribution of the workplace by computational analysis. Using a frequency analysis of hand velocities, errors in the chosen assembly method were revealed showing differences in the hand velocities. An opportunity is seen to classify some quantifiable aspects that are not identified easily in a traditional time and motion analysis. The automated analysis is considered as the main contribution in this study. In the industrial context, a great application is perceived in terms of monitoring the workplace to analyze repeatability, PTS, workplace and labor activities redistribution using the proposed methodology.


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    Title :

    An automated time and hand motion analysis based on planar motion capture extended to a virtual environment


    Contributors:

    Publication date :

    2015-01-01



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629 / 650




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