Business Intelligence for Multi-Domain Systems Engineering and Operations
Applications in Cyber-Physical Production
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Beschreibung
This book aims at capabilities for knowledge representation, collection, and integration required for business intelligence for multi-domain systems engineering and operation with applications in cyber-physical production. This book builds on established domain standards and guidelines, such as ISO 9000 quality improvement; the widely used cross-industry standard process for data mining (CRISP-DM) open standard process model to inform quality improvement; multi-disciplinary configuration management and reuse guidelines (VDI 3695) to define system configurations and engineering processes; multi-domain production engineering data on (i) products, (ii) production processes, and (iii) resources to conduct and automate production (VDI 3682) to link knowledge on product, processes and resources (PPR); the AutomationML standard (IEC 62714) to represent systems engineering knowledge independent of technologies; IT security improvement guideline (VDI 2182) to link systems engineering and operation to IT security; and failure mode and effects analysis (FMEA) (DIN 60812) to explore root causes of effects in systems engineering and operation.
To connect business intelligence for quality improvement with the required multi-domain knowledge and data on systems engineering and operation, this book consists of three main parts (1) Digital transformation based on business intelligence in multi-domain systems engineering and operation; (2) Information systems engineering for business and quality improvement; and (3) Multi-domain data refinery to provide the high-quality data required for business intelligence.
This book aims at capabilities for knowledge representation, collection, and integration required for business intelligence for multi-domain systems engineering and operation with applications in cyber-physical production. This book builds on established domain standards and guidelines, such as ISO 9000 quality improvement; the widely used cross-industry standard process for data mining (CRISP-DM) open standard process model to inform quality improvement; multi-disciplinary configuration management and reuse guidelines (VDI 3695) to define system configurations and engineering processes; multi-domain production engineering data on (i) products, (ii) production processes, and (iii) resources to conduct and automate production (VDI 3682) to link knowledge on product, processes and resources (PPR); the AutomationML standard (IEC 62714) to represent systems engineering knowledge independent of technologies; IT security improvement guideline (VDI 2182) to link systems engineering and operation to IT security; and failure mode and effects analysis (FMEA) (DIN 60812) to explore root causes of effects in systems engineering and operation.
To connect business intelligence for quality improvement with the required multi-domain knowledge and data on systems engineering and operation, this book consists of three main parts (1) Digital transformation based on business intelligence in multi-domain systems engineering and operation; (2) Information systems engineering for business and quality improvement; and (3) Multi-domain data refinery to provide the high-quality data required for business intelligence.
Business Intelligence for cyber-physical production systems in a multi-domain life cycle Practical methodologies and real-world use cases for digital transformation success Integration and harmonization of stakeholder knowledge across domains with PPR-based approaches
Autor*in
Stefan Biffl
Themen in »Business Intelligence for Multi-Domain Systems Engineering and Operations«
model-driven engineering cyber-physical systems industry 4.0 production systems systems engineering business intelligence digital transformation CRISP-DM system architecture digital twins