TY - CHAP
T1 - A Holistic Approach
T2 - Issues and Challenges in Autonomic Computation Toward Industry 4.0
AU - Gautami, A.
AU - Gowthaman, Naveenbalaji
N1 - Publisher Copyright:
© 2021, Springer Nature Switzerland AG.
PY - 2021/8
Y1 - 2021/8
N2 - Industry 4.0 is an essence of innovative technologies such as industrial Internet of things, cyber-physical systems, cloud computing, artificial intelligence, and cognitive computation. Digitalization is a key factor in Industry 4.0 which acts as a liaison between humans and technology. Industry 4.0 or smart factory is formulated with principles of interconnectivity, transparent characteristics, and decentralized decision-making. The significant advancement in autonomous decision-making, data analytics, higher degree predictive analysis, and end-to-end supply chain encourages the need for smart factories in this digitized world. However, leading manufacturers are facing lots of challenges to satisfy customer’s requirements and transforming from conventional technologies to smart IoT-enabled technologies. The main objective of this chapter highlights the issues and challenges of Industry 4.0 such as (1) interoperability of data in open ecosystems, (2) autonomous decision-making capabilities, (3) efficient design to promise safety and sustainability, and (4) market risks and vulnerability associated with the malicious attacks.
AB - Industry 4.0 is an essence of innovative technologies such as industrial Internet of things, cyber-physical systems, cloud computing, artificial intelligence, and cognitive computation. Digitalization is a key factor in Industry 4.0 which acts as a liaison between humans and technology. Industry 4.0 or smart factory is formulated with principles of interconnectivity, transparent characteristics, and decentralized decision-making. The significant advancement in autonomous decision-making, data analytics, higher degree predictive analysis, and end-to-end supply chain encourages the need for smart factories in this digitized world. However, leading manufacturers are facing lots of challenges to satisfy customer’s requirements and transforming from conventional technologies to smart IoT-enabled technologies. The main objective of this chapter highlights the issues and challenges of Industry 4.0 such as (1) interoperability of data in open ecosystems, (2) autonomous decision-making capabilities, (3) efficient design to promise safety and sustainability, and (4) market risks and vulnerability associated with the malicious attacks.
KW - Autonomic computation
KW - Cloud computing
KW - Cyber-physical systems
KW - Industry 4.0
KW - Internet of things
UR - http://www.scopus.com/inward/record.url?scp=85112433789&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-71756-8_6
DO - 10.1007/978-3-030-71756-8_6
M3 - Chapter
AN - SCOPUS:85112433789
SN - 978-3-030-71755-1
T3 - EAI/Springer Innovations in Communication and Computing
SP - 111
EP - 121
BT - Autonomic Computing in Cloud Resource Management in Industry 4.0.
A2 - Choudhury, Tanupriya
A2 - Dewangan, Bhupesh Kumar
A2 - Tomar, Ravi
A2 - Singh, Bhupesh Kumar
A2 - Teoh, Teik Toe
A2 - Nguyen, Gia Nhu
PB - Springer
ER -