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The appeal of a forklift-free shop floor is pushing enterprises towards lean logistic systems and tugger trains are becoming popular means of supply in intensive material handling production systems. Planning a tugger train system is a complex task influenced by a large set of interrelated parameters. The only standard available to help the planner in designing the tugger train logistic system is the draft norm VDI 5586 (April 2016). However this norm is only applicable under a set of restricting assumptions. In this paper a methodology to complement the approach proposed by the VDI is introduced and then applied to a numerical example. The results are briefly presented and discussed before suggesting forthcoming research.
While academia and industry see large potential for human-robot collaboration (HRC), only a small number of realized HRC application is currently found in industry. To gather more data about current hindrances to wider implementation of collaborative robots, a study among 15 robot manufactureres and 14 system integrators of collaborative robot technology has been conducted through a predesigned questionnaire procedure. Additionally, five industrial users of human-robot collaboration have been interviewed on the main challenges they experienced during the initial implementation process. The quantitative data has been analyzed using the Wilcoxon-Signed-Rank-Test. Accoring to the study participants, the main challenges within the implementation currently are the identification of HRC-suitable processes, the application of relevant safety norms (such as ISO 10218, ISO/TS 15066) and the application-individual risk assessment.
The success of an autonomous robotic system is influenced by several not easily identifiable interdependent factors. This paper is set to lay the foundation of an integrated approach in order to examine all the parameters and understand their contribution to success. After introducing the problem, two autonomous systems for the process of unloading of containers are presented. Then a recently developed method for modelling and interpreting all the parameters, the STIC analysis, are introduced. The preliminary results of applying such a methodology to a first study case is shortly presented. Future research is in the end recommended in order to prove that this methodology is the only way to overcome barriers to the investment in autonomous systems in the logistics sector.