Abstract
Nowadays, companies face new challenges and benefits with the incorporation of technologies associated with Industry 4.0 into product manufacturing. The new collaborative environments have to be capable of adapting efficiently to different levels of production as well as safely collaborating in the process with human operators. In this paper, a model for predicting human actions involved in a manufacturing process is proposed. The model uses Manufacturing Description Language combined with a statistical state graph able to provide the probability of a new action to be performed by the operator. Among other benefits, the model is able to improve the production, reducing waste in movement, time, or use of additional actions.
Keywords
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Zamora-Hernandez, MA., Ceciliano, J.A.C., Granados, A.V., Garcia-Rodriguez, J., Azorin-Lopez, J. (2022). Predicting Human Actions in the Assembly Process for Industry 4.0. In: Sanjurjo González, H., Pastor López, I., García Bringas, P., Quintián, H., Corchado, E. (eds) 16th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2021). SOCO 2021. Advances in Intelligent Systems and Computing, vol 1401. Springer, Cham. https://doi.org/10.1007/978-3-030-87869-6_38
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DOI: https://doi.org/10.1007/978-3-030-87869-6_38
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