Model-Driven Optimisation of Monitoring System Configurations for Batch Production

Margraf, Andreas; Cui, Henning; Heimbach, Simon; Hähner, Jörg; Geinitz, Steffen; Rudolph, Stephan

doi:10.5220/0011688900003402

Proceedings of the 11th International Conference on Model-Based Software and Systems Engineering 2023

DOI: 10.5220/0011688900003402

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Model-Driven Optimisation of Monitoring System Configurations for Batch Production

Andreas Margraf

Henning Cui

Simon Heimbach

et al.

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Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming

Margraf,

Cui,

Stein

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

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The reconfiguration of machine vision systems heavily depends on the collection and availability of large datasets, rendering them inflexible and vulnerable to even minor changes in the data. This paper proposes a refinement of Miller's Cartesian Genetic Programming methodology, aimed at generating filter pipelines for image processing tasks. The approach is based on CGP-IP, but specifically adapted for image processing in industrial monitoring applications. The suggested method allows for retraining of filter pipelines using small datasets; this concept of self-adaptivity renders high-precision machine vision more resilient to faulty machine settings or changes in the environment and provides compact programs. A dependency graph is introduced to rule out invalid pipeline solutions. Furthermore, we suggest to not only generate pipelines from scratch, but store and reapply previous solutions and re-adjust filter parameters. Our modifications are designed to increase the likelihood of early convergence and improvement in the fitness indicators. This form of self-adaptivity allows for a more resource-efficient configuration of image filter pipelines with small datasets.

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Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming

Margraf,

Cui,

Stein

et al. 2023

2023 IEEE International Conference on Autonomic Computing and Self-Organizing Systems (ACSOS)

View full text Add to dashboard Cite

show abstract

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Model-Driven Optimisation of Monitoring System Configurations for Batch Production

Cited by 1 publication

References 0 publications

Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming

Evolving Processing Pipelines for Industrial Imaging with Cartesian Genetic Programming

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