Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Chapter
}
TY - CHAP
T1 - Data-driven parameters tuning for predictive performance improvement of wire bonder multi-body model
AU - Cheng, Xiaodong
AU - di Busshianico, Alessandro
AU - Javanmardi, N
AU - de Jong, Matthijs
AU - Diget, E.L.
AU - Please, Colin
AU - Lahaye, Domenico
AU - Peng, Qiyao (Alice)
AU - Reisch, Cordula
AU - Sclosa, D.
PY - 2023/1/30
Y1 - 2023/1/30
N2 - This report describes work performed during SWI 2023 at the Universityof Groningen in relation with Problem 1 posed by the company ASMPT.ASMPT makes a very large number of different machines for manufacturing ofelectronic devices. They have detailed simulation software of one of these machinesand they compare the results of this with physical experimental results. There is asignificant difference between the simulated and measured data, and it is the goal of this work to study how to estimate the parameters in the simulation model using the experimentally measured frequency response.First, two toy models are studied to understand the challenges of parameter estimation in the frequency domain. Later, optimization methods are applied. Several different approaches of reducing the dimensionality of the parameter space are explored, including determining the parameter sensitivity. A suggestion for increasing the detail of the model, specifically related to the machine base, is also outlined.In the summary, we supply a discussion of the key insights we gained during theweek.
AB - This report describes work performed during SWI 2023 at the Universityof Groningen in relation with Problem 1 posed by the company ASMPT.ASMPT makes a very large number of different machines for manufacturing ofelectronic devices. They have detailed simulation software of one of these machinesand they compare the results of this with physical experimental results. There is asignificant difference between the simulated and measured data, and it is the goal of this work to study how to estimate the parameters in the simulation model using the experimentally measured frequency response.First, two toy models are studied to understand the challenges of parameter estimation in the frequency domain. Later, optimization methods are applied. Several different approaches of reducing the dimensionality of the parameter space are explored, including determining the parameter sensitivity. A suggestion for increasing the detail of the model, specifically related to the machine base, is also outlined.In the summary, we supply a discussion of the key insights we gained during theweek.
M3 - Chapter
SP - 1
EP - 24
BT - Scientific Proceedings 170th European Study Group with Industry
A2 - Koellermeier, Julian
A2 - Tibboel, Pieter
A2 - Trenn, Stephan
CY - Leiden
ER -