Artificial Intelligence for Smart Manufacturing and Industry X.0
暫譯: 智慧製造與工業X.0的人工智慧
Islam, M. M. Manjurul, Baptista, Marcia L., Tariq, Faisal
商品描述
This book offers a foundational understanding of smart manufacturing (SM) and introduces effective AI methods tailored for smart manufacturing, including supervised, unsupervised, and reinforcement learning techniques. It also features real-world industrial case studies that demonstrate the practical applications of smart manufacturing.
Drawing from the invaluable experiences gleaned from the aviation, healthcare, and semiconductors industries, this book provides an in-depth understanding of how AI is driving transformative changes in the manufacturing landscape.
In the era of rapid technological advancements, the integration of AI into manufacturing processes has emerged as a game-changer. This book serves as an indispensable guide for navigating this transformation, presenting readers with a multidimensional perspective on the diverse applications, challenges, and opportunities that AI brings to the manufacturing sector.
The book explores the emergence of Large Language Models (LLMs) as a valuable tool in manufacturing. It presents how LLMs, especially the GPT series, can process and generate textual data, offering potential applications in areas like smart manufacturing and big-data analysis. It contains detailed case studies, illustrating the practical implementation of smart manufacturing in different industries. The aviation, healthcare, automotive, and semiconductors sectors are examined, highlighting tangible benefits, challenges faced, and lessons learned from each domain.
The book addresses the future prospects of Industry 4.0 and beyond--the interconnected, data-driven evolution of manufacturing. It examines the potential impact of emerging technologies such as the Industrial Internet of Things (IIoT), 5G, and advanced robotics on the manufacturing landscape. Challenges and future possibilities pertaining to research and advancement in smart manufacturing within the domains of Aviation, Semiconductors, and Healthcare sectors are also discussed.
The chapters will be written in a tutorial style to allow early-career researchers and industry practitioners an in-depth understanding of the various topics. The book serves as a reference for researchers, engineers, and students seeking to understand the synergy between AI, Industry 4.0, LLMs, and real-world applications.
商品描述(中文翻譯)
這本書提供了智能製造（Smart Manufacturing, SM）的基礎理解，並介紹了針對智能製造的有效人工智慧（AI）方法，包括監督式學習、非監督式學習和強化學習技術。書中還包含了真實的工業案例研究，展示智能製造的實際應用。
本書汲取了航空、醫療保健和半導體行業的寶貴經驗，深入探討了人工智慧如何推動製造業的變革。
在快速技術進步的時代，人工智慧與製造過程的整合已成為一個改變遊戲規則的因素。本書作為導航這一轉型的不可或缺的指南，為讀者提供了多維度的視角，探討人工智慧為製造業帶來的多樣應用、挑戰和機會。
本書探討了大型語言模型（Large Language Models, LLMs）作為製造業中一個有價值的工具的出現。它展示了LLMs，特別是GPT系列，如何處理和生成文本數據，並在智能製造和大數據分析等領域提供潛在應用。書中包含詳細的案例研究，說明智能製造在不同產業中的實際實施。航空、醫療保健、汽車和半導體行業被檢視，突顯了每個領域的具體好處、面臨的挑戰和所學到的經驗。
本書還探討了工業4.0及其未來前景——製造業的互聯網、數據驅動的演變。它檢視了新興技術如工業物聯網（Industrial Internet of Things, IIoT）、5G和先進機器人技術對製造業的潛在影響。書中也討論了在航空、半導體和醫療保健領域中，智能製造的研究和進展所面臨的挑戰和未來可能性。
各章將以教程風格撰寫，以便早期職業研究人員和行業從業者深入理解各種主題。本書作為研究人員、工程師和學生的參考資料，幫助他們理解人工智慧、工業4.0、大型語言模型和實際應用之間的協同效應。
作者簡介
M M Manjurul Islam received his BS in Computer Science and his MS leading to a PhD in Computer Engineering from the University of Ulsan, South Korea. He is a Research Associate in the School of Computing, Engineering, and Intelligent Systems at Ulster University, UK, and a member of the Smart Nano NI consortium project. His research is supported by UK Research and Innovation. Previously, he worked as an Assistant Professor in the Department of Computer Science at the American International University-Bangladesh and as a Postdoctoral Fellow at the Center for Digital Industry of Fondazione Bruno Kessler in Italy. Additionally, he worked as an engineer at Accenture Plc and Telenor ASA for seven years. Dr. Islam has made significant contributions to the fields of artificial intelligence, smart manufacturing, and prognostics and health management, publishing over 50 peer-reviewed papers. He has delivered talks at international conferences in Australia, China, South Korea, Spain, Italy, the UK, Canada, and the USA, and has been invited as a lecturer for the Brain Korea 21 (BK21) program. He actively reviews over 150 publications and grant applications and evaluates funding proposals for institutions such as the National Science Centre in Poland. Dr. Islam serves on the advisory panel for AI and Signals journals, has been involved in several international and national conference technical committees, and has edited special issues for journals including Energies, Frontiers in Energy Research, and Micromachines. Dr. Islam is an Associate Fellow of Advance HE and a Senior Member of IEEE.
Marcia Lourenco Baptista is an Adjunct Professor (Invited) at NOVA IMS and holds a PhD from the MIT Portugal Program (Instituto Superior Técnico). She teaches various topics in big data analytics, data science, and machine learning. Her main areas of research are predictive analytics, explainable artificial intelligence, and neural networks. She has studied maintenance and the industrial field for several years, focusing on interpretability, generative modeling, and prognostics techniques. She lectured on the course Maintenance Modeling and Analysis at TU Delft for three years. She is the author of more than 45 scientific articles, most of which are classified in Quartile 1 or published in high-impact conferences. Before joining NOVA IMS, she was an invited researcher at several international research centers, including NASA Research Center, ITA, the National Institute of Informatics in Tokyo, and Delft University of Technology.
Faisal Tariq, a Senior Lecturer in the James Watt School of Engineering (JWSE) at the University of Glasgow, leads research in applications of AI and data science in wireless communications, smart energy, manufacturing, and healthcare technologies. He also has expertise in designing privacy and security solutions using distributed ledger technology (DLT). He has edited three books on AI for smart healthcare, mobile apps engineering, and emerging 6G wireless technologies. His research is supported by the British Council Researcher Links grant, the Charles Wallace Trusts fund, and the QMUL-GCRF pump-priming grant. He is a Senior Member of IEEE and has published 50 articles, book chapters, and conference papers. He has been involved in several international and national conference technical committees, journal editorial boards, and has given invited and keynote presentations in several countries around the world.
作者簡介(中文翻譯)
M M Manjurul Islam 於南韓蔚山大學獲得計算機科學學士學位及計算機工程碩士學位，並進一步攻讀博士學位。他是英國阿爾斯特大學計算、工程與智能系統學院的研究助理，並且是 Smart Nano NI 聯盟項目的成員。他的研究得到了英國研究與創新機構的支持。之前，他曾在孟加拉美國國際大學計算機科學系擔任助理教授，並在意大利布魯諾·凱斯勒基金會的數位產業中心擔任博士後研究員。此外，他在 Accenture Plc 和 Telenor ASA 擔任工程師七年。Islam 博士在人工智慧、智慧製造及預測與健康管理領域做出了重要貢獻，發表了超過 50 篇經過同行評審的論文。他在澳洲、中國、南韓、西班牙、意大利、英國、加拿大和美國的國際會議上發表演講，並受邀擔任 Brain Korea 21 (BK21) 計畫的講師。他積極審查超過 150 篇出版物和資助申請，並為波蘭國家科學中心等機構評估資金提案。Islam 博士擔任 AI 和 Signals 期刊的顧問小組成員，參與多個國際和國內會議的技術委員會，並為包括 Energies、Frontiers in Energy Research 和 Micromachines 在內的期刊編輯特刊。Islam 博士是 Advance HE 的副研究員及 IEEE 的高級會員。
Marcia Lourenco Baptista 是 NOVA IMS 的邀請兼任教授，並擁有來自 MIT 葡萄牙計畫（Instituto Superior Técnico）的博士學位。她教授大數據分析、數據科學和機器學習等多個主題。她的主要研究領域包括預測分析、可解釋的人工智慧和神經網絡。她在維護和工業領域研究多年，專注於可解釋性、生成建模和預測技術。她在代爾夫特理工大學教授維護建模與分析課程三年。她是超過 45 篇科學文章的作者，其中大多數被歸類為四分位數 1 或發表在高影響力的會議上。在加入 NOVA IMS 之前，她曾在多個國際研究中心擔任邀請研究員，包括 NASA 研究中心、ITA、東京國立資訊學研究所和代爾夫特理工大學。
Faisal Tariq 是格拉斯哥大學詹姆斯·瓦特工程學院的高級講師，領導人工智慧和數據科學在無線通信、智慧能源、製造和醫療技術中的應用研究。他在使用分散式帳本技術 (DLT) 設計隱私和安全解決方案方面也具有專業知識。他編輯了三本關於智慧醫療、移動應用工程和新興 6G 無線技術的人工智慧書籍。他的研究得到了英國文化協會研究者聯繫資助、查爾斯·華萊士信託基金和 QMUL-GCRF 啟動資助的支持。他是 IEEE 的高級會員，已發表 50 篇文章、書籍章節和會議論文。他參與多個國際和國內會議的技術委員會、期刊編輯委員會，並在世界各地的多個國家進行邀請和主題演講。
