Objective: Cardiovascular diseases are the leading cause of death. The gold standard for their diagnosis and treatment are angiographic procedures. Clinicians rely on dedicated and specialized equipment for these interventions, e.g. angiography systems. The speed of the associated development is important as better technology enables progress in treatment methods and clinical outcomes. The goal of this article is to show how to optimize the innovation and development process such that it takes minimal time. Methods: 672 data sets on 302 topics were collected over 47 months during a long-term observation of the innovation and development process of angiographic systems. The total data collected is equivalent to efforts worth 30 man-years. This input was used to calculate key process parameters, analyse key process roles, evaluate the use of problem-solving methods and identify key technologies. We also developed a process model comprising the primary innovation sources, important input providers and key processes. This model is characterized by a continuous loop for the innovation and development process. Results: The conducted literature research identifies this closed loop process model as being unique in comparison to the well-established models proposed by Brockhoff, Cooper, Crawford, Durfee, Ebert, Eppinger, Hughes, Pleschak, Thom, Ulrich, Vahs and Witt. According to the best knowledge of the authors no comparable data collection has been performed and presented anywhere else yet. When analysing our 672 data sets, we found that the median process time ( in this data pool (n=672) was to be 10 weeks (p<0,05). The median number of task owners (xPA) per task across all topics was 2. Our data revealed that the number of task owners had a direct impact on the process time. For data sets with up to eight task owners the relationship between process time and task owners can be described as tPd=3.6*xPA^1.4. The median time of owning a topic was determined for Sales (7 weeks), Service (11 weeks), Customer Relationship Management (6 weeks), Product Lifecycle Management (10 weeks) and Research & Development (11 weeks). Main input providers were Sales (53%) and customers (28%). Sales (42%) and PLM (37%) are significant connectors. Problem solvers are PLM (35%), CRM (27%) and R&D (27%). The problem-solving methods were analysed and it was found that clarification (77%) as well as dialog and variation method (both 50%) were used most often. We found that changes to the application software (33%), mechanics, device interfaces and user interface (all 21%) are the four out of six components that were involved in most often. In the analysed datasets a potential of an up to 20% shorter process time was identified. Conclusion: This article proposes a new model for the innovation and development process. Based on our data, we recommend to apply a continuous loop process in the context of innovation and development of medical devices. Our results can, for example, be used for Activity Based Costing Approach or be applied to bring new or upgraded angiography systems faster to market benefitting patient outcome due to improved diagnosis and treatment of cardiovascular diseases.

The intention to reduce greenhouse gas emissions in the aviation industry is generating high pressure to innovate, which is also leading to an increasing need for improvements in the development process, especially as this is already subject to major changes due to changing products and value creation systems. In the future, the development process should be more digitalized and information better integrated in order to optimize the supply of information to developers. To this end, the following article presents a digital twin for product development, which is being developed as part of a research project on cross-lifecycle integration through digital twins in collaboration with Rolls-Royce Electrical and other research partners. The focus is on describing the conception of the digital twin, which produces a concept that is as user centric as possible based on user stories in order to specifically serve existing needs. The concept of the digital twin will be developed based on the current as-is process and the existing system landscape as well as the use cases derived from the user stories and presented here.

Um eine zielgerichtete Ableitung von Fahrzeugeigenschaften in frühen Entwicklungsphasen zu ermöglichen, ist eine Subsystemebene erforderlich, die eine konzeptunabhängige Auslegung des Gesamtfahrzeugverhaltens zulässt. In der vorliegenden Arbeit wird daher eine neue Methodik zur Auslegung von Fahrkomfort-Kennwerten auf Basis von Subsystemeigenschaften vorgestellt. Neben der Entwicklung eines geeigneten Modellansatzes, in dem die Subsysteme des Gesamtfahrzeugs durch Greybox-Modelle ohne Komponentenbezug miteinander verknüpft werden, stehen dabei auch dessen Parametrierung sowie die Integration der Methodik im Entwicklungsprozess im Vordergrund. Zur Ableitung der damit verbundenen physikalisch-mechanischen Zusammenhänge werden statische und dynamische Achsprüfstände sowie Simulationen eingesetzt. Die Anwendung der Methodik lässt eine gezielte Eigenschaftsableitung zwischen Gesamtfahrzeug-, Subsystem- und Komponentenebene im Fahrkomfort zu, bei der die Subsystemebene als neue Referenz für die Ableitung von Komponenteneigenschaften dient. Weiterhin erlaubt das Vorgehen eine eigenschaftsbasierte Vorauswahl optimaler Komponentenkonzepte sowie detaillierte Wettbewerbsanalysen. Dadurch wird eine nachhaltige Steigerung der Effizienz im Entwicklungsprozess des Fahrkomforts ermöglicht.

Die Weiterentwicklung von Verbrennungsmotoren ist geprägt von einer Steigerung der Effizienz, optimaler Betriebslaststeuerung, einer Absenkung des spezifischen Verbrauchs und der Erfüllung geltender Abgasemissionsgesetzgebung. Die Optimierung des Ladungswechsels spielt dabei eine entscheidende Rolle. Eine Möglichkeit den Ladungswechsel optimal zu beeinflussen, ist der Einsatz von variablen Ventiltrieben zur Veränderung der Ventilhubbewegung sowie zur Verstellung der Steuerzeiten. thyssenkrupp Dynamic Components entwickelt und stellt Schiebenockensysteme als diskret schaltbare Ventiltriebsysteme her, welche die verschiedenen Ventilhubanforderungen über unterschiedliche Nockenprofile auf dem Schiebeelement nebeneinander abbilden können. Im Entwicklungs- und Auslegungsprozesses kommt eine Simulation des Bewegungs-, Beschleunigungs- und Abbremsverhaltens sowie der Kraftverläufe beim Verstellvorgang mittels einer Mehrkörpersimulation (MKS) in der Software alaska/ModellerStudio zum Einsatz. In diesem Beitrag wird das MKS-Modell des Schiebelements sowie der Abgleich des Modells mit Versuchen vorgestellt. Es folgt eine Darstellung von Optimierungsmöglichkeiten bereits in der Simulationsumgebung, bei denen die Kontaktnormalkräfte und Beschleunigungen in mehreren Iterationsschleifen auf den gewünschten Anwendungsfall angepasst werden können. Unter Berücksichtigung der Fertigungs- und Lagertoleranzen sowie des Verschleißverhaltens kann das System mit diesem Simulationstool bereits virtuell abgeprüft werden. / The advancement of internal combustion engines is characterized by an increase in efficiency, optimum operating load control, a reduction in specific consumption and compliance with applicable exhaust emission legislation. Optimization of the charge change plays a decisive role in this. One way of optimally influencing the charge change is to use variable valve trains to change the valve lift and adjust the timing. thyssenkrupp Dynamic Components develops and manufactures sliding cam systems as discretely switchable valve train systems that can feature the various valve lift requirements side by side via different cam profiles on the sliding element. A simulation of the motion, acceleration and deceleration behavior as well as the force curves during the sliding process by means of a multi-body simulation (MBS) in the alaska/ModellerStudio is applied in the development and design process. This presentation shows the MBS model of the sliding cam and the comparison of the model with test results. Various optimization options in the simulation environment present, how the contact normal forces and accelerations can be adapted in several iteration loops to the desired application. Taking into account the manufacturing and bearing tolerances as well as the wear behavior, this simulation tool allows to virtually check the sliding cam system.