Verfahren zur Konzipierung imitationsgeschützter Produkte und Produktionssysteme. - Kokoschka, Martin

Verfahren zur Strategieentwicklung und -umsetzung auf Basis einer Retropolation von Zukunftsszenarien. - Reymann, Felix

Planung von Cross-Industry-Innovationen – Methodik für einen branchenübergreifenden Lösungstransfer} - Amshoff, Benjamin; Echterhoff, Niklas; Gausemeier, Jürgen; Grote, Anne-Christin

The production system of the future thinks and learns - Gausemeier, J {\ "u} rgen; Iwanek, Peter; K ö chling, Daniel (Industrieanzeiger)

Market and competitive strategies for {\" u } r the MRO business {\ "a} ft of the civil aviation industry

Technology push-oriented product planning

Foresight and technology planning . 8th Symposium for ü r foresight and technology planning

Solution Patterns of Software Engineering for the System Design of Advanced Mechatronic Systems - Anacker, Harald; Gausemeier, Jürgen; Dumitrescu, Roman; Dziwok, Stefan; Schäfer, Wilhelm (Proceedings of the 9th France-Japan / 7th Europe-Asia Congress 13th International Workshop on Research and Education in Mechatronics (MECATRONICS-REM 2012))

Unterstützung des mechatronischen Entwurfs durch die effektive Suche nach Lösungselementen mithilfe von semantischen Technologien - Oestersötebier, Felix; Dziwok, Stefan; Bauer, Frank; Trächtler, Ansgar; Schäfer, Wilhelm; Gausemeier, Jürgen

Simulative Absicherung mechatronischer Systeme in der frühen Phase der Produktentstehung - Bauer, Frank; Gausemeier, Jürgen; Köchling, Daniel; Oestersötebier, Felix

integrative development of product and technology strategies - Brink, Volker; Gausemeier, J {\ "u} rgen; Reymann, Felix (construction, issue 11/2012)

Computer-Aided Planning and Optimisation of Manufacturing Processes for Functional Graded Components - Biermann, Dirk; Gausemeier, Jürgen; Heim, Hans-Peter; Hess, Stefan; Petersen, Marcus; Ries, Angela; Wagner, T
In this paper, a comprehensive framework for the computer-aided planning and optimisation of process chains for functional graded components is presented. The framework is divided into three modules – the component description, the expert system, and the modelling and process chain optimisation. The component description module enhances a standard CAD model by a voxel-based representation of the graded properties. It allows the target properties to be defined. The expert system proposes process chains capable of producing components according to the requirements of the enhanced CAD model. They usually consist of a sequence of heating, forming, and cooling processes. The dependencies between the applied manufacturing processes need to be considered. Therefore, the robustness of the property distributions achieved in a process step with respect to variations in the input properties is analysed in the third module, in which the process chains are optimised. A method to accomplish this task by performing a model-based sensitivity analysis and subsequent Monte-Carlo simulations of the important parameters is proposed in this paper. The applicability of the method is shown for a thermo-mechanically coupled compression moulding process.

Strategic leadership with scenarios - Gausemeier, J {\ "u} rgen; Grote, Anne-Christin (CONTROLLING - magazine for { \ "u} r success-oriented corporate management)

Systems Thinking: Sensitizing for Systems Engineering - Experiences from academic teaching and industry workshops - Gausemeier, Jürgen; Tschirner, Christian; Vaßholz, Mareen

GPU-based Local Tone Mapping in the Context of Virtual Night Driving - Berssenbrügge, Jan; Bonner, Erik (Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference)

Self-Assessment for Evaluation and Improving the Product Development Processes in SMEs - Bensiek, Tobias; Kühn, Arno; Gausemeier, Jürgen; Grafe, Michael (Proceedings of the ASME 2012 International Design Engineering Technical Conferences & Computers and Information in Engineering Conference, IDETC/CIE 2012, Chicago, IL, USA, August 12 – 15)

Model-Based Design of Mechatronic Systems by Means of Semantic Web Ontologies and Reusable Solution Element - Oestersötebier, Felix; Just, Viktor; Trächtler, Ansgar; Bauer, Frank; Dziwok, Stefan (Proceedings of the ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis)
When designing complex mechatronic systems, a team of developers will be facing many challenges that can impede progress and innovation if not tackled properly. In meeting them simulation tools play a central role. Yet it is often impossible for a single developer to foresee the overall impact a design decision will have on the system and on the other domains involved. For this task multi-domain simulation tools exists, but because of its complexity and the different levels of detail that are needed, the effort to specify a complete system from scratch is very high. Another challenge is the selection of the most suitable solution elements provided by the manufacturers. Currently they are often chosen manually from catalogues. The development engineer is therefore usually inclined to employ well-known solution elements and suppliers. To tackle both challenges our aim is an increase in efficiency and innovation by means of generally available solution knowledge, such as well-proven solution patterns, ready-to-use solution elements, and established simulation models [1]. Our paper presents a tool-supported, sequential design process. From the outset, the comprehensive functional capability of the designed system is supervised by means of multi-domain simulation. At significant points in the design process, solution knowledge can be accessed as it is stored in ontologies and therefore available via Semantic Web [2]. Thus, one can overcome barriers resulting from different terminologies or referential systems and furthermore infer further knowledge from the stored knowledge. The paper focuses on an early testing in the conceptual design stage and on the subsequent semantic search for suitable solution elements. After the specification of a principle solution for the mechatronic system by combining solution patterns, an initial multi-domain model of the system is created. This is done on the basis of the active structure and of idealized simulation models which are part of a free library and associated with the chosen solution patterns via the ontologies. In further designing the controlled system and its parameters with the completed model, the developer defines additional criteria to be fed into the subsequent semantic search for solution elements. Information on the latter is provided by the manufacturers as well as detailed simulation models, which are used to analyze the functional capability of the concretized system. Therefore, the corresponding idealized models are replaced automatically with the parameterized models of the solution elements containing for example the specific friction model for the chosen motor. We show this process using the concrete example of a dough-production system. In particular, we focus on its transport system. Resulting requirements for the simulation models and their level of detail are expound, as well as the architecture and benefits of the ontologies. [1] Bauer, F., Anacker, H., Gaukstern, T., Gausemeier, J., Just, V., (2011), “Analyzing the dynamic behavior of mechatronic systems within the conceptual design”, Proceedings of the 18th International Conference on Engineering Design (ICED11), 4, Copenhagen, pp. 329-336. [2] Berners-Lee, T., Hendler, J.; Lassila, O., (2001), “The Semantic Web”, Scientific American, 284(5), pp. 34–43.

Computer support for the identification of solution patterns for the conceptual design of advanced mechatronic systems - Dumitrescu, Roman; Anacker, Harald; Bauer, Frank; Gausemeier, Jürgen (Proceedings of the ASME 2012 11th Biennial Conference on Engineering Systems Design and Analysis)

Development of Product Piracy Robust Products and Production Systems - Kokoschka, Martin; Gausemeier, Jürgen; Lehner, Markus (Proceedings of 18th International ICE-Conference on Engineering, Technology and Innovation)

Development of Product Piracy Robust Products and Production Systems