@article{c025d017dd8f4353b2d91bcbce2d0fc2,
title = "Daydreaming factories",
abstract = "Optimisation of factories, a cornerstone of production engineering for the past half century, relies on formulating the challenges with limited degrees of freedom. In this paper, technological advances are reviewed to propose a “daydreaming” framework for factories that use their cognitive capacity for looking into the future or “foresighting”. Assessing and learning from the possible eventualities enable breakthroughs with many degrees of freedom and make daydreaming factories antifragile. In these factories with augmented and reciprocal learning and foresighting processes, revolutionary reactions to external and internal stimuli are unnecessary and industrial co-evolution of people, processes and products will replace industrial revolutions.",
keywords = "Domain randomization, Production, Synthesis",
author = "Aydin Nassehi and Marcello Colledani and Botond K{\'a}d{\'a}r and Eric Lutters",
note = "Funding Information: The authors would like to thank Mr Chan Muangpoon for his photographs of the augmented reality system for Factory Layout Planning and Ms Ola Al-Khuraybi for her contribution to the work on KPI characterisation. The authors would also like to express their gratitude to the CIRP colleagues who supported them with information, references, constructive criticism, and advice; especially, Dr Fazel Ansari, Dr Pinar Bilge, Professor Emanuele Carpanzano, Professor Franz Dietrich, Dr David Gyulai, Professor Hoda ElMaraghy, Professor Waguih ElMaraghy, Dr Benjamin Hafner, Professor Gisela Lanza, Professor Dimitris Mourtzis, Professor Stephen Newman, Dr Martin Peterek, Dr Sina Peukert, Professor Robert Schmitt, Professor Wilfred Sihn, Dr Alessandro Simeone and Dr Nicole Stricker. Special thanks are extended to Nitin Kaushik of Apollo Tyres, Hungary who provided details of their industrial case for inclusion in the paper. Botond K{\'a}d{\'a}r acknowledges the support received from the European Commission through the H2020 project EPIC under grant No. 739592. This work was supported by the Engineering and Physical Sciences Research Council grants EP/R013179/1 and EP/R032696/1 . Funding Information: The authors would like to thank Mr Chan Muangpoon for his photographs of the augmented reality system for Factory Layout Planning and Ms Ola Al-Khuraybi for her contribution to the work on KPI characterisation. The authors would also like to express their gratitude to the CIRP colleagues who supported them with information, references, constructive criticism, and advice; especially, Dr Fazel Ansari, Dr Pinar Bilge, Professor Emanuele Carpanzano, Professor Franz Dietrich, Dr David Gyulai, Professor Hoda ElMaraghy, Professor Waguih ElMaraghy, Dr Benjamin Hafner, Professor Gisela Lanza, Professor Dimitris Mourtzis, Professor Stephen Newman, Dr Martin Peterek, Dr Sina Peukert, Professor Robert Schmitt, Professor Wilfred Sihn, Dr Alessandro Simeone and Dr Nicole Stricker. Special thanks are extended to Nitin Kaushik of Apollo Tyres, Hungary who provided details of their industrial case for inclusion in the paper. Botond K{\'a}d{\'a}r acknowledges the support received from the European Commission through the H2020 project EPIC under grant No. 739592. This work was supported by the Engineering and Physical Sciences Research Council grants EP/R013179/1 and EP/R032696/1. Publisher Copyright: {\textcopyright} 2022 The Author(s)",
year = "2022",
month = jan,
doi = "10.1016/j.cirp.2022.05.002",
language = "English",
volume = "71",
pages = "671--692",
journal = "CIRP annals : manufacturing technology",
issn = "0007-8506",
publisher = "Elsevier Inc.",
number = "2",
}