Hybrid Modeling of an Adhesive Bonding Process, Case Study: Polyphenylene Sulfide

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@InProceedings{Goharoodi:2023:CoDIT,

• author = "Saeideh Khatiry Goharoodi and Jeroen Jordens and Bart {Van Doninck} and Guillaume Crevecoeur",
• booktitle = "2023 9th International Conference on Control, Decision and Information Technologies (CoDIT)",
• title = "Hybrid Modeling of an Adhesive Bonding Process, Case Study: Polyphenylene Sulfide",
• year = "2023",
• pages = "1786--1791",
• abstract = "Adhesive bonding is a joining process used in several industries such as aerospace, automotive, civil construction and manufacturing. Traditionally, the optimisation of the parameters for this process is performed by adhesive experts via trial and error which is expensive and time-consuming. Therefore having a process model for optimisation purposes is of great interest. In this study, we develop such process model which includes cost, visual quality and joint strength properties for Polyphenylene sulfide bonding use-case. We adopt analytical modelling approaches for those process properties that do not require extensive system knowledge and are not effected by large number of process parameters, namely cost and visual quality. Additionally, we use data-driven genetic programming approach to model the more nonlinear process property, meaning joint strength of the bond. Consequently, we employ a hybrid approach by combining available knowledge and experimental data. The process model can then be implemented for process optimisation or to create a digital twin which predicts if the product quality is in scope.",
• keywords = "genetic algorithms, genetic programming, Industries, Visualization, Costs, Predictive models, Product design, Quality assessment, Manufacturing",
• DOI = "doi:10.1109/CoDIT58514.2023.10284411",
• ISSN = "2576-3555",
• month = jul,
• notes = "Also known as \cite{10284411}",

}

Genetic Programming entries for Saeideh Khatiry Goharoodi Jeroen Jordens Bart Van Doninck Guillaume Crevecoeur

Citations