Abstract
The introduction of new technologies driven by Industry 4.0 is transforming existing logistics processes. The changing tasks of the employees in this context require a systematic review of current requirement profiles (RPs) to appropriately bundle future employee tasks in homogeneous profiles. Thus, this paper develops a method for the determination of RPs taking Industry 4.0 in logistics into account. In this way, tasks are systematically transferred into RPs on the basis of similar characteristics. A data-driven method is chosen to reduce the subjectivity of the approach by using similarity factors. These reflect the central aspects of the socio-technical system and are derived from literature and practice. The method, which has been validated at a commercial vehicle manufacturer, helps in making decisions about RPs and can provide information about how eliminated, changed and new tasks affect the composition of employee RPs.
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Acknowledgements
This research was funded in part by MAN Truck & Bus SE and in part by the Chair of Materials Handling, Material Flow, Logistics (fml) at the Technical University of Munich. All support is gratefully acknowledged. Any opinions, findings, conclusions, or recommendations expressed in this paper are those of the writers and do not necessarily reflect the views of MAN Truck & Bus SE or the fml.
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Kohl, M., Häring, S., Lopitzsch, J., Fottner, J. (2021). Data-Driven Determination and Plausibility Check of Requirement Profiles in Logistics. In: Trzcielinski, S., Mrugalska, B., Karwowski, W., Rossi, E., Di Nicolantonio, M. (eds) Advances in Manufacturing, Production Management and Process Control. AHFE 2021. Lecture Notes in Networks and Systems, vol 274. Springer, Cham. https://doi.org/10.1007/978-3-030-80462-6_39
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DOI: https://doi.org/10.1007/978-3-030-80462-6_39
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