This book discusses challenges and solutions for the required information processing and management within the context of multi-disciplinary engineering of production systems. The authors consider methods, architectures, and technologies applicable in use cases according to the viewpoints of product engineering and production system engineering, and regarding the triangle of (1) product to be produced by a (2) production process executed on (3) a production system resource. With this book industrial production systems engineering researchers will get a better understanding of the challenges and requirements of multi-disciplinary engineering that will guide them in future research and development activities. Engineers and managers from engineering domains will be able to get a better understanding of the benefits and limitations of applicable methods, architectures, and technologies for selected use cases. IT researchers will be enabled to identify research issues related to the development of new methods, architectures, and technologies for multi-disciplinary engineering, pushing forward the current state of the art.
Table of Content
Introduction to the Multi-Disciplinary Engineering for Cyber-Physical Production Systems.- Product and Systems Engineering/CA* Tool Chains.- Cyber-Physical Product-Service Systems.- Product Lifecycle Management Challenges of CPPS.- Fundamentals of Artifact Reuse in CPPS.- Identification of Artifacts in Life Cycle Phases of CPPS.- Description Means for Information Artifacts throughout the Life Cycle of CPPS.- Engineering of Next Generation Cyber-Physical Automation System Architectures.- Engineering Workflow and Software Tool Chains of Automated Production Systems.- Standardized Information Exchange within Production System Engineering.- Model-Driven Systems Engineering: Principles and Application in the CPPS Domain.- Semantic Web Technologies for Data Integration in Multi-Disciplinary Engineering.- Patterns for Self-Adaptation in Cyber-Physical Systems.- Service-Oriented Architectures for Interoperability in Industrial Enterprises.- A Deterministic Product Ramp-up Process – How to Integrate a Multi-disciplinary Knowledge Base.- Towards Model Quality Assurance for Multi-Disciplinary Engineering – Needs, Challenges, and Solution Concept.- Conclusions and Outlook on Research for Multi-Disciplinary Engineering for Cyber-Physical Production Systems.
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