Soft Computing in Smart Manufacturing : : Solutions toward Industry 5.0 / / ed. by Tatjana Sibalija, J. Paulo Davim.
This book aims at addressing the challenges of contemporary manufacturing in Industry 4.0 environment and future manufacturing (aka Industry 5.0), by implementing soft computing as one of the major sub-fields of artificial intelligence. It contributes to development and application of the soft compu...
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Superior document: | Title is part of eBook package: De Gruyter DG Plus DeG Package 2022 Part 1 |
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MitwirkendeR: | |
HerausgeberIn: | |
Place / Publishing House: | Berlin ;, Boston : : De Gruyter, , [2021] ©2022 |
Year of Publication: | 2021 |
Language: | English |
Series: | Advanced Mechanical Engineering ,
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Online Access: | |
Physical Description: | 1 online resource (XIV, 277 p.) |
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Other title: | Frontmatter -- Preface -- About the editors -- Contents -- List of contributing authors -- 1 Control, monitoring, modeling, and optimization of manufacturing and machining technologies -- 2 Trustworthy human–machine assistance by dynamic process security monitoring in industrial environments -- 3 Application of convolutional neural networks for visual control of intelligent robotic systems -- 4 Digital twins in smart manufacturing -- 5 A novel implementation of an open CNC PC-based and service-oriented architecture-based monitoring system for STEP-NC – a case study -- 6 Smart system based on STEP-NC for machine vision inspection (3SMVI) -- 7 Soft computing in advanced cutting processes -- 8 Modeling and optimization of AWJM process on the processing of Banana fiber-reinforced polymer composites using Taguchi-JAYA method -- Index |
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Summary: | This book aims at addressing the challenges of contemporary manufacturing in Industry 4.0 environment and future manufacturing (aka Industry 5.0), by implementing soft computing as one of the major sub-fields of artificial intelligence. It contributes to development and application of the soft computing systems, including links to hardware, software and enterprise systems, in resolving modern manufacturing issues in complex, highly dynamic and globalized industrial circumstances. It embraces heterogeneous complementary aspects, such as control, monitoring and modeling of different manufacturing tasks, including intelligent robotic systems and processes, addressed by various machine learning and fuzzy techniques; modeling and parametric optimization of advanced conventional and non-conventional, eco-friendly manufacturing processes by using machine learning and evolutionary computing techniques; cybersecurity framework for Internet of Things-based systems addressing trustworthiness and resilience in machine-to-machine and human-machine collaboration; static and dynamic digital twins integration and synchronization in a smart factory environment; STEP-NC technology for a smart machine vision system, and integration of Open CNC with Service-Oriented Architecture for STEP-NC monitoring system in a smart manufacturing. Areas of interest include but are not limited to applications of soft computing to address the following: dynamic process/system modeling and simulation, dynamic process/system parametric optimization, dynamic planning and scheduling, smart, predictive maintenance, intelligent and autonomous systems, improved machine cognition, effective digital twins integration, human-machine collaboration, robots, and cobots. |
Format: | Mode of access: Internet via World Wide Web. |
ISBN: | 9783110693225 9783110766820 9783110754001 9783110753776 9783110754070 9783110753837 |
ISSN: | 2367-3796 |
DOI: | 10.1515/9783110693225 |
Access: | restricted access |
Hierarchical level: | Monograph |
Statement of Responsibility: | ed. by Tatjana Sibalija, J. Paulo Davim. |