Artificial intelligence-enabled digital twin for smart manufacturing:
An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these tech...
Gespeichert in:
| Weitere beteiligte Personen: | , , , |
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| Format: | Elektronisch E-Book |
| Sprache: | Englisch |
| Veröffentlicht: |
Hoboken, New Jersey Beverly, MA
John Wiley & Sons, Inc.
2024
Hoboken, New Jersey Beverly, MA Scrivener Publishing LLC 2024 |
| Schlagwörter: | |
| Links: | https://learning.oreilly.com/library/view/-/9781394303571/?ar |
| Zusammenfassung: | An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin--an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system's behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI's capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. |
| Beschreibung: | Description based on online resource; title from digital title page (viewed on October 15, 2024) |
| Umfang: | 1 Online-Ressource |
| ISBN: | 9781394303601 1394303602 9781394303595 1394303599 9781394303571 |
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| 520 | |a An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin--an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system's behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI's capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. | ||
| 650 | 0 | |a Computer integrated manufacturing systems | |
| 650 | 0 | |a Digital twins (Computer simulation) |x Industrial applications | |
| 650 | 0 | |a Artificial intelligence | |
| 650 | 0 | |a Manufacturing processes |x Automation | |
| 650 | 4 | |a Productique | |
| 650 | 4 | |a Intelligence artificielle | |
| 650 | 4 | |a Fabrication ; Automatisation | |
| 650 | 4 | |a artificial intelligence | |
| 700 | 1 | |a Tyagi, Amit Kumar |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Tiwari, Shrikant |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Arumugam, Senthil Kumar |e HerausgeberIn |4 edt | |
| 700 | 1 | |a Sharma, Avinash Kumar |d 1982- |e HerausgeberIn |4 edt | |
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| author2 | Tyagi, Amit Kumar Tiwari, Shrikant Arumugam, Senthil Kumar Sharma, Avinash Kumar 1982- |
| author2_role | edt edt edt edt |
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| author_facet | Tyagi, Amit Kumar Tiwari, Shrikant Arumugam, Senthil Kumar Sharma, Avinash Kumar 1982- |
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| dewey-full | 670.285 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 670 - Manufacturing |
| dewey-raw | 670.285 |
| dewey-search | 670.285 |
| dewey-sort | 3670.285 |
| dewey-tens | 670 - Manufacturing |
| discipline | Werkstoffwissenschaften / Fertigungstechnik |
| format | Electronic eBook |
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| id | ZDB-30-ORH-109653564 |
| illustrated | Not Illustrated |
| indexdate | 2025-01-17T11:22:08Z |
| institution | BVB |
| isbn | 9781394303601 1394303602 9781394303595 1394303599 9781394303571 |
| language | English |
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| publisher | John Wiley & Sons, Inc. Scrivener Publishing LLC |
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| spelling | Artificial intelligence-enabled digital twin for smart manufacturing edited by Amit Kumar Tyagi, Shrikant Tiwari, Senthil Kumar Arumugam and Avinash Kumar Sharma Hoboken, New Jersey Beverly, MA John Wiley & Sons, Inc. 2024 Hoboken, New Jersey Beverly, MA Scrivener Publishing LLC 2024 ©2024 1 Online-Ressource Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Description based on online resource; title from digital title page (viewed on October 15, 2024) An essential book on the applications of AI and digital twin technology in the smart manufacturing sector. In the rapidly evolving landscape of modern manufacturing, the integration of cutting-edge technologies has become imperative for businesses to remain competitive and adaptive. Among these technologies, Artificial Intelligence (AI) stands out as a transformative force, revolutionizing traditional manufacturing processes and making the way for the era of smart manufacturing. At the heart of this technological revolution lies the concept of the Digital Twin--an innovative approach that bridges the physical and digital realms of manufacturing. By creating a virtual representation of physical assets, processes, and systems, organizations can gain unprecedented insights, optimize operations, and enhance decision-making capabilities. This timely book explores the convergence of AI and Digital Twin technologies to empower smart manufacturing initiatives. Through a comprehensive examination of principles, methodologies, and practical applications, it explains the transformative potential of AI-enabled Digital Twins across various facets of the manufacturing lifecycle. From design and prototyping to production and maintenance, AI-enabled Digital Twins offer multifaceted advantages that redefine traditional paradigms. By leveraging AI algorithms for data analysis, predictive modeling, and autonomous optimization, manufacturers can achieve unparalleled levels of efficiency, quality, and agility. This book explains how AI enhances the capabilities of Digital Twins by creating a powerful tool that can optimize production processes, improve product quality, and streamline operations. Note that the Digital Twin in this context is a virtual representation of a physical manufacturing system, including machines, processes, and products. It continuously collects real-time data from sensors and other sources, allowing it to mirror the physical system's behavior and performance. What sets this Digital Twin apart is the incorporation of AI algorithms and machine learning techniques that enable it to analyze and predict outcomes, recommend improvements, and autonomously make adjustments to enhance manufacturing efficiency. This book outlines essential elements, like real-time monitoring of machines, predictive analytics of machines and data, optimization of the resources, quality control of the product, resource management, decision support (timely or quickly accurate decisions). Moreover, this book elucidates the symbiotic relationship between AI and Digital Twins, highlighting how AI augments the capabilities of Digital Twins by infusing them with intelligence, adaptability, and autonomy. Hence, this book promises to enhance competitiveness, reduce operational costs, and facilitate innovation in the manufacturing industry. By harnessing AI's capabilities in conjunction with Digital Twins, manufacturers can achieve a more agile and responsive production environment, ultimately driving the evolution of smart factories and Industry 4.0/5.0. Audience This book has a wide audience in computer science, artificial intelligence, and manufacturing engineering, as well as engineers in a variety of industrial manufacturing industries. It will also appeal to economists and policymakers working on the circular economy, clean tech investors, industrial decision-makers, and environmental professionals. Computer integrated manufacturing systems Digital twins (Computer simulation) Industrial applications Artificial intelligence Manufacturing processes Automation Productique Intelligence artificielle Fabrication ; Automatisation artificial intelligence Tyagi, Amit Kumar HerausgeberIn edt Tiwari, Shrikant HerausgeberIn edt Arumugam, Senthil Kumar HerausgeberIn edt Sharma, Avinash Kumar 1982- HerausgeberIn edt 1394303572 Erscheint auch als Druck-Ausgabe 1394303572 |
| spellingShingle | Artificial intelligence-enabled digital twin for smart manufacturing Computer integrated manufacturing systems Digital twins (Computer simulation) Industrial applications Artificial intelligence Manufacturing processes Automation Productique Intelligence artificielle Fabrication ; Automatisation artificial intelligence |
| title | Artificial intelligence-enabled digital twin for smart manufacturing |
| title_auth | Artificial intelligence-enabled digital twin for smart manufacturing |
| title_exact_search | Artificial intelligence-enabled digital twin for smart manufacturing |
| title_full | Artificial intelligence-enabled digital twin for smart manufacturing edited by Amit Kumar Tyagi, Shrikant Tiwari, Senthil Kumar Arumugam and Avinash Kumar Sharma |
| title_fullStr | Artificial intelligence-enabled digital twin for smart manufacturing edited by Amit Kumar Tyagi, Shrikant Tiwari, Senthil Kumar Arumugam and Avinash Kumar Sharma |
| title_full_unstemmed | Artificial intelligence-enabled digital twin for smart manufacturing edited by Amit Kumar Tyagi, Shrikant Tiwari, Senthil Kumar Arumugam and Avinash Kumar Sharma |
| title_short | Artificial intelligence-enabled digital twin for smart manufacturing |
| title_sort | artificial intelligence enabled digital twin for smart manufacturing |
| topic | Computer integrated manufacturing systems Digital twins (Computer simulation) Industrial applications Artificial intelligence Manufacturing processes Automation Productique Intelligence artificielle Fabrication ; Automatisation artificial intelligence |
| topic_facet | Computer integrated manufacturing systems Digital twins (Computer simulation) Industrial applications Artificial intelligence Manufacturing processes Automation Productique Intelligence artificielle Fabrication ; Automatisation artificial intelligence |
| work_keys_str_mv | AT tyagiamitkumar artificialintelligenceenableddigitaltwinforsmartmanufacturing AT tiwarishrikant artificialintelligenceenableddigitaltwinforsmartmanufacturing AT arumugamsenthilkumar artificialintelligenceenableddigitaltwinforsmartmanufacturing AT sharmaavinashkumar artificialintelligenceenableddigitaltwinforsmartmanufacturing |