Design Methodology for Intelligent Technical Systems : Develop Intelligent Technical Systems of the Future (Lecture Notes in Mechanical Engineering)

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This book presents the methods needed to implement self-optimization in mechatronic systems. It details the steps required to assure a dependable product design, starting with the very early conceptual design phase.

Intelligent technical systems, which combine mechanical, electrical and software engineering with control engineering and advanced mathematics, go far beyond the state of the art in mechatronics and open up fascinating perspectives. Among these systems are so-called self-optimizing systems, which are able to adapt their behavior autonomously and flexibly to changing operating conditions. Self-optimizing systems create high value for example in terms of energy and resource efficiency as well as reliability.

The Collaborative Research Center 614 "Self-optimizing Concepts and Structures in Mechanical Engineering" pursued the long-term aim to open up the active paradigm of self-optimization for mechanical engineering and to enable others to develop self-optimizing systems.

This book is directed to researchers and practitioners alike. It provides a design methodology for the development of self-optimizing systems consisting of a reference process, methods, and tools. The reference process is divided into two phases the domain-spanning conceptual design and the domain-specific design and development. For the conceptual design a holistic approach is provided. Domain-specific methods and tools developed especially for the design and development of self-optimizing systems are described and illustrated by application examples. This book will enable the reader to identify the potential for self-optimization and to develop self-optimizing systems independently.

The Paradigm of Self-Optimization.- Examples of Self-Optimizing Systems.- Development of Self-Optimizing Systems.- Methods for the Domain-Spanning Conceptual Design.- Methods for the Design and Development.- Summary and Outlook. Prof. Dr.-Ing. Jürgen Gausemeier ist Professor für Rechnerintegrierte Produktion am Heinz Nixdorf Institut der Universität Paderborn.

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