Design Methodology For Intelligent Technical Systems
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Design Methodology for Intelligent Technical Systems
Author: Jürgen Gausemeier
language: en
Publisher: Springer Science & Business Media
Release Date: 2014-01-28
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.
Material-Integrated Intelligent Systems
Combining different perspectives from materials science, engineering, and computer science, this reference provides a unified view of the various aspects necessary for the successful realization of intelligent systems. The editors and authors are from academia and research institutions with close ties to industry, and are thus able to offer first-hand information here. They adopt a unique, three-tiered approach such that readers can gain basic, intermediate, and advanced topical knowledge. The technology section of the book is divided into chapters covering the basics of sensor integration in materials, the challenges associated with this approach, data processing, evaluation, and validation, as well as methods for achieving an autonomous energy supply. The applications part then goes on to showcase typical scenarios where material-integrated intelligent systems are already in use, such as for structural health monitoring and smart textiles.
Design Methodology for Future Products
Design Methodology for Future Products – Data Driven, Agile and Flexible provides an overview of the recent research in the field of design methodology from the point of view of the members of the scientific society for product development (WiGeP - Wissenschaftliche Gesellschaft für Produktenwicklung e.V.). This book aims to contribute to design methods and their implementation for innovative future products. The main focus is the crucial data-driven, agile, and flexible way of working. Four topics are covered in corresponding chapters, Methods for Product Development and Management, Methods for Specific Products and Systems, Facing the Challenges in Product Development and Model-Based Engineering in Product Development. This publication starts with the agile strategic foresight of sustainable mechatronic and cyber-physical systems, moves on to the topics of system generation engineering in development processes, followed by the technical inheritance in data-driven product development. Product improvements are shown via agile experiential learning based on reverse engineering and via combination of usability and emotions. Furthermore, the development of future-oriented products in the field of biomechatronic systems, sustainable mobility systems and in situ sensor integration is shown. The overcoming of challenges in product development is demonstrated through context-adapted methods by focusing on efficiency and effectiveness, as well as designer-centered methods to tackle cognitive bias. Flow design for target-oriented availability of data and information in product development is addressed. Topics of model-based systems engineering are applied to the function-driven product development by linking model elements at all stages and phases of the product. The potential of model-based systems engineering for modular product families and engineering of multidisciplinary complex systems is shown.