TY - JOUR
T1 - Opportunities and Challenges to Integrate Artificial Intelligence Into Manufacturing Systems
T2 - Thoughts From a Panel Discussion [Opinion]
AU - Kovalenko, Ilya
AU - Barton, Kira
AU - Moyne, James
AU - Tilbury, Dawn M.
N1 - Publisher Copyright:
© 1994-2011 IEEE.
PY - 2023/6/1
Y1 - 2023/6/1
N2 - Rapid advances in artificial intelligence (AI) have the potential to significantly increase productivity, quality, and profitability in future manufacturing systems. (Caveat: The panel did not attempt to disentangle artificial intelligence from machine learning and used the two terms loosely interchangeably during the discussion.) Traditional mass production will give way to personalized production, with each item made to order, at the low cost and high quality consumers have come to expect. Manufacturing systems will have the intelligence to be resilient to multiple disruptions, from small-scale machine breakdowns to large-scale natural disasters. Products will be made with higher precision and lower variability. While gains have been made toward the development of these factories of the future, many challenges remain to fully realize the vision shown in Figure 1.
AB - Rapid advances in artificial intelligence (AI) have the potential to significantly increase productivity, quality, and profitability in future manufacturing systems. (Caveat: The panel did not attempt to disentangle artificial intelligence from machine learning and used the two terms loosely interchangeably during the discussion.) Traditional mass production will give way to personalized production, with each item made to order, at the low cost and high quality consumers have come to expect. Manufacturing systems will have the intelligence to be resilient to multiple disruptions, from small-scale machine breakdowns to large-scale natural disasters. Products will be made with higher precision and lower variability. While gains have been made toward the development of these factories of the future, many challenges remain to fully realize the vision shown in Figure 1.
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U2 - 10.1109/MRA.2023.3262464
DO - 10.1109/MRA.2023.3262464
M3 - Review article
AN - SCOPUS:85153401656
SN - 1070-9932
VL - 30
SP - 109
EP - 112
JO - IEEE Robotics and Automation Magazine
JF - IEEE Robotics and Automation Magazine
IS - 2
ER -