0000000001195834

AUTHOR

Maria Gita

showing 1 related works from this author

Towards an Assembly Support System with Dynamic Bayesian Network

2022

Due to the new technological advancements and the adoption of Industry 4.0 concepts, the manufacturing industry is now, more than ever, in a continuous transformation. This work analyzes the possibility of using dynamic Bayesian networks to predict the next assembly steps within an assembly assistance training system. The goal is to develop a support system to assist the human workers in their manufacturing activities. The evaluations were performed on a dataset collected from an experiment involving students. The experimental results show that dynamic Bayesian networks are appropriate for such a purpose, since their prediction accuracy was among the highest on new patterns. Our dynamic Bay…

Fluid Flow and Transfer ProcessesTechnologyQH301-705.5TPhysicsQC1-999Process Chemistry and TechnologyGeneral Engineeringdynamic Bayesian networkEngineering (General). Civil engineering (General)assembly assistance systemComputer Science ApplicationsChemistryassembly assistance system; dynamic Bayesian networkGeneral Materials ScienceTA1-2040Biology (General)QD1-999InstrumentationApplied Sciences; Volume 12; Issue 3; Pages: 985
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