Design of an optimised value creation network for zero emission ferries

Disselkamp, Jan-Philipp; Seidenberg, Tobias; Anacker, Harald; Dumitrescu, Roman

doi:10.1109/ice/itmc-iamot55089.2022.10033200

Cited by 4 publications

(1 citation statement)

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“…Standardization enables, for example, outsourcing the production of some components to specialized companies that can produce at low cost (Seidenberg et al, 2022). In addition, value creation networks can be formed that can achieve further cost reductions (Disselkamp et al, 2022). Standardising a ferry is challenging because there are a multitude of interdependencies that are mutually dependent.…”

Section: Problem Analysismentioning

confidence: 99%

Platform Approach for Modularising Battery Electric Fast Ferries

et al. 2023

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The transportation sector is responsible for a relevant share of the total emissions and offers great potentials. It is necessary to implement as many zero-emission mobility systems as possible in the shortest time. For fast ferries, which are a relevant transport manner for a large share of the global population, technical issues could be solved and the successful operation was demonstrated. Up to today high-speed ships have been fully individually designed because physical effects demand for an individual optimisation for each use-case. Specifically for battery electric ships the overall efficiency is crucial to ensure not only an ecological but also economical operation.With today's methods the design and production of such an individual designed ferry does take too long. To cover the rising demand, new approaches for mass production need to be established.In this paper we describe a method for designing a platform for ships with the example of a battery electric fast ferry. The focus is on the actual modularisation, as other aspects like requirements or results of our example case are published elsewhere and are therefore just included briefly.The method is validated on the world's first battery powered high-speed ferry.

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Section: Problem Analysismentioning

confidence: 99%