TY - GEN
T1 - Human Model For Industrial System And Product Design In Industry 5.0
T2 - IISE Annual Conference and Expo 2023
AU - Allemang-Trivalle, Arnaud
AU - Donjat, Jérémie
AU - Bechu, Gaëlic
AU - Coppin, Gilles
AU - Klaproth, Oliver W.
AU - Mitschke, Andreas
AU - Schirrmann, Arnd
AU - Chollet, Mathieu
AU - Cao, Caroline G.L.
N1 - This work was performed under Airbus Contract SP2104350 DISM. We thank the production line workers and managers at Airbus Hamburg for their expertise, the Region Bretagne and FEDER for funding the Chair for Industry of the Future (Prof. Cao), the International Max Planck Research School for Intelligent Systems (IMPRS-IS) and the AI@IMT program for funding Arnaud Allemang--Trivalle.
PY - 2023
Y1 - 2023
N2 - Human performance models can be included in industrial system models to improve the design of the industrial system, manufacturing processes, and product design. In our use case, a critical process in the production of a new airplane was being considered for automation. This process requires the highest quality assurance and is normally performed manually. Robot assistance could improve quality and efficiency. A human performance model focused on worker fatigue was developed, taking into account characteristics of the workers, robots, and tasks. Two different automation scenarios (fully manual, semi-automated), with different worker characteristics such as skill, age, motivation, etc. were studied. Using historical production line data in the fully manual scenario, and simulated data for the semi-automated scenario, global fatigue scores and graphical visualization were generated by the model for each scenario, allowing the system architects to understand the effects of the future production system on workers, including errors, time lost, costs and overall resilience of the system.
AB - Human performance models can be included in industrial system models to improve the design of the industrial system, manufacturing processes, and product design. In our use case, a critical process in the production of a new airplane was being considered for automation. This process requires the highest quality assurance and is normally performed manually. Robot assistance could improve quality and efficiency. A human performance model focused on worker fatigue was developed, taking into account characteristics of the workers, robots, and tasks. Two different automation scenarios (fully manual, semi-automated), with different worker characteristics such as skill, age, motivation, etc. were studied. Using historical production line data in the fully manual scenario, and simulated data for the semi-automated scenario, global fatigue scores and graphical visualization were generated by the model for each scenario, allowing the system architects to understand the effects of the future production system on workers, including errors, time lost, costs and overall resilience of the system.
KW - Industry 5.0
KW - Production and manufacturing
KW - Simulation model
KW - Worker fatigue
UR - http://www.scopus.com/inward/record.url?scp=85174936878&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85174936878&partnerID=8YFLogxK
U2 - 10.21872/2023IISE_1962
DO - 10.21872/2023IISE_1962
M3 - Conference contribution
AN - SCOPUS:85174936878
T3 - IISE Annual Conference and Expo 2023
BT - IISE Annual Conference and Expo 2023
A2 - Babski-Reeves, K.
A2 - Eksioglu, B.
A2 - Hampton, D.
PB - Institute of Industrial and Systems Engineers, IISE
Y2 - 21 May 2023 through 23 May 2023
ER -