The conceivable development of information and communication technology will enable mechatronic systems with inherent partial intelligence. We refer to this by using the term "self-optimization". Self-Optimizing systems react autonomously and flexibly on changing operation conditions. They are able to learn and optimize their behavior at runtime. The development of mechatronic and especially self-optimizing systems is still a challenge. A significant milestone within the development is the principle solution. It determines the basic structure as well as the operation mode of the system and is the result of the conceptual design. Additionally it is the basis for the concretization of the system which involves experts from several domains, such as mechanics, electrical engineering/electronics, control engineering and software engineering. This contribution presents a new specification technique for the conceptual design of mechatronic and self-optimizing systems. It also uses the railway technology as a complex example, to demonstrate how to use this specification technique and in which way it profits for the development of future mechanical engineering systems.
We present the design, implementation and initial evaluation of a zoomable interface dedicated to present a large hierarchical design model of a complex mechatronic system. The large hierarchical structure of the model is illustrated by means of a visual notation and consists of over 800 elements. An efficient presentation of this complex model is realized by means of a zoomable user interface that is rendered on a large Virtual Reality wall with a high resolution (3860 x 2160). We assume that this visualization set-up combined with dedicated interaction techniques for selection and navigation reduces the cognitive workload of a passive audience and supports the understanding of complex hierarchical structures. To validate this assumption we have designed a small experiment that compares the traditional visualization techniques PowerPoint and paper sheets with this new presentation form.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.