Hier finden Sie wissenschaftliche Publikationen aus den Fraunhofer-Instituten.

Internet of Things Canvas for Ideation in Model-Based Product Generation Planning

: Albers, A.A.; Bernijazov, R.; Kaiser, L.; Dumitrescu, R.


13th System of Systems Engineering Conference, SoSE 2018 : June 19-22, 2018, Sorbonne université, campus Pierre et Marie Curie, Paris, France
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-4876-6
ISBN: 978-1-5386-4875-9
ISBN: 978-1-5386-4877-3
International Conference on System of Systems Engineering (SoSE) <13, 2018, Paris>
Fraunhofer IEM ()

Product generation planning deals with the strategic planning of new product generations. An important task of this procedure is to find ideas for new product features based on an existing reference product. In industrial practice, usually technical models of the reference product (e.g. CAD models) are employed in the scope of product feature ideation. However, these models alone do not provide sufficient information for the identification of new Internet of Things (IoT) features. These features require the consideration of the available flows, the utilized communication technologies, and the surrounding System of Systems (SoS). A potential solution for this problem is provided by Model-Based Systems Engineering (MBSE). MBSE provides a holistic system model that describes the logical architecture as well as the environment of the reference product. However, there is a lack of methodological support for the utilization of system models in the scope of strategic product planning. This paper presents a novel method for IoT feature ideation based on the system model of a reference product. The core of this method is the so-called IoT canvas, which constitutes an IoT-specific view on the system model of the reference product. It can be systematically derived from the system model and serves as the starting point for product feature ideation. The presented method was evaluated in the scope of an innovation project with a German manufacturing company and showed high potential for industrial practice.