JIDOKA. Integration of Human and AI within Industry 4.0 Cyber Physical Manufacturing Systems

Edited by
April 2022
188 pages
  • ISBN978-3-0365-3812-9 (Hardback)
  • ISBN978-3-0365-3811-2 (PDF)

This book is a reprint of the Special Issue JIDOKA. Integration of Human and AI within Industry 4.0 Cyber Physical Manufacturing Systems that was published in

Chemistry & Materials Science
Environmental & Earth Sciences

This book is about JIDOKA, a Japanese management technique coined by Toyota that consists of imbuing machines with human intelligence. The purpose of this compilation of research articles is to show industrial leaders innovative cases of digitization of value creation processes that have allowed them to improve their performance in a sustainable way. This book shows several applications of JIDOKA in the quest towards an integration of human and AI within Industry 4.0 Cyber Physical Manufacturing Systems. From the use of artificial intelligence to advanced mathematical models or quantum computing, all paths are valid to advance in the process of human–machine integration.

  • Hardback
© 2022 by the authors; CC BY-NC-ND license
healthy operator 4.0; human–cyber–physical system; industrial internet of things; industry 4.0; smart workplaces; EEG sensors; manufacturing systems; shopfloor management; machine learning; deep learning; industry 4.0; reference architecture model; interoperability; digital twin; distributed ledger technology; GDPR; RAMI 4.0; LASFA; quantum computing; strategic organizational design; Industry 4.0; complex networks; cyber-physical systems; lean management systems; quantum strategic organizational design; industry 4.0; quantum circuits; quantum simulation; JIDOKA; industry 4.0; shopfloor management; Industry 4.0; Operator 4.0; process variability; JIDOKA; integration explaining variability; Industry 4.0; quantum approximate optimization algorithm; value–stream networks; optimization; maintenance interval; maintenance model; semi-Markov process; right-censored data; finite horizon; maintenance cost; Cyber-Physical Systems; Lean Manufacturing; Directed Acyclic Graphs; scikit-learn; pipegraph; machine learning models