TY - CHAP
T1 - Towards Data-Driven and Human-Centric Intelligent Manufacturing Through the Integration of AI, IoT, and Blockchain
AU - Ulandari, Defia
AU - Anggraini, Deswita
AU - Laksono, Mohammad Norman Gaza
AU - Chui, Kwok Tai
AU - Ponkumar, D. David Neels
N1 - Publisher Copyright:
Copyright © 2026, IGI Global Scientific Publishing. Copying or distributing in print or electronic forms without written permission of IGI Global Scientific Publishing is prohibited. Use of this chapter to train generative artificial intelligence (AI) technologies is expressly prohibited. The publisher reserves all rights to license its use for generative AI training and machine learning model development.
PY - 2026
Y1 - 2026
N2 - The transformation to Industry 5.0 is driving manufacturing to adopt a more intelligent, adaptive, and humanized approach through the integration of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain. This chapter proposes an integrative framework of the three technologies, which makes AI the center of analytics and decision-making, IoT the nervous system that collects data in real-time, and Blockchain the foundation of trust through secure and transparent data recording. This approach not only improves operational efficiency, predictivity, and product personalization, but also supports sustainability and industry ethics. Case studies such as predictive maintenance, mass customization, and supply chain visibility demonstrate the effectiveness of this integration in the field. The chapter also details implementation challenges as well as future trends, such as federated learning and quantum-resistant Blockchain. Overall, this framework provides strategic direction for a resilient, adaptive, and people-oriented manufacturing ecosystem.
AB - The transformation to Industry 5.0 is driving manufacturing to adopt a more intelligent, adaptive, and humanized approach through the integration of Artificial Intelligence (AI), Internet of Things (IoT), and Blockchain. This chapter proposes an integrative framework of the three technologies, which makes AI the center of analytics and decision-making, IoT the nervous system that collects data in real-time, and Blockchain the foundation of trust through secure and transparent data recording. This approach not only improves operational efficiency, predictivity, and product personalization, but also supports sustainability and industry ethics. Case studies such as predictive maintenance, mass customization, and supply chain visibility demonstrate the effectiveness of this integration in the field. The chapter also details implementation challenges as well as future trends, such as federated learning and quantum-resistant Blockchain. Overall, this framework provides strategic direction for a resilient, adaptive, and people-oriented manufacturing ecosystem.
UR - https://www.scopus.com/pages/publications/105040317562
U2 - 10.4018/979-8-2600-0013-7.ch007
DO - 10.4018/979-8-2600-0013-7.ch007
M3 - Chapter
AN - SCOPUS:105040317562
SN - 9798260000137
SN - 9798260000144
SP - 233
EP - 265
BT - Coresource 4
ER -