A meta-model based simulation optimization using hybrid simulation-analytical modeling to increase the productivity in automotive industry

DOI10.1016/j.matcom.2015.07.005OpenAlexW939565519MaRDI QIDQ2228751

Berna Dengiz, Onder Belgin, Yusuf Tansel İç

Publication date: 19 February 2021

Published in: Mathematics and Computers in Simulation (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.matcom.2015.07.005

zbMATH Keywords

design of experimentsimulation optimizationautomotive industrymultiple linear regression modelpaint shop production line

Mathematics Subject Classification ID

Systems theory; control (93-XX) Operations research, mathematical programming (90-XX)

Cites Work

• Unnamed Item
• Group screening and Taguchi design in the optimization of multi-echelon maintenance float simulation metamodels
• Manufacturing cell operating characteristics
• A methodology for fitting and validating metamodels in simulation
• Solving a multiresponse simulation-optimization problem with discrete variables using a multiple-attribute decision-making method
• Simulation optimization of buffer allocations in production lines with unreliable machines
• Multi-level scheduling decisions in a class of FMS using simulation based metamodels
• The Metamodel in Simulation Analysis: Can It Be Trusted?
• The construction and implementation of metamodels
• Metamodels in manufacturing: a review
• A case study of the body shop design in an automotive factory using 3D simulation

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