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Talks and Poster Presentations (with Proceedings-Entry):

M. Sarna, K. Meixner, S. Biffl, A. Lüder:
"Reducing Risk in Industrial Bin Picking With PPRS Configuration and Dependency Management";
Talk: 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA), Västerås, Sweden; 2021-09-07 - 2021-09-10; in: "Proceedings 2021 26th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA)", (2021), ISBN: 978-1-6654-2478-3.



English abstract:
Industrial Bin Picking Applications (IBPAs) shall
improve production and economic efficiency, but still, they are
hard to design efficiently, with sufficient system accuracy, cycle
time, and technical availability. However, it is not clear how to
represent the knowledge on quantitative means for IBPA subsystem analysis and specified quality parameters. This paper
aims to close this gap by introducing the Risk-Aware Bin Picking
Configuration (RABPC) model on sub-system configurations and
their dependencies to quality characteristics of the IBPA. In the
RABPC model, a configuration matrix represents the involved
sub-systems, and a Product-Process-Resource-Skill (PPRS) Network describes quality dependencies of library components to
reduce the risk of deficient applications. We evaluate the RABPC
model with a Bin Picking use case from the automotive industry.

Keywords:
Industrial Bin Picking, skill-based modeling, model-based engineering, complexity management

Created from the Publication Database of the Vienna University of Technology.