Towards an Assembly Support System with Dynamic Bayesian Network

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 assistan...

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Bibliographic Details
Published in:Applied sciences 2022-02, Vol.12 (3), p.985
Main Authors: Precup, Stefan-Alexandru, Gellert, Arpad, Matei, Alexandru, Gita, Maria, Zamfirescu, Constantin-Bala
Format: Article
Language:English
Subjects:
Algorithms
Artificial intelligence
assembly assistance system
Assembly lines
Augmented reality
Automation
Bayesian analysis
dynamic Bayesian network
Experiments
Gamification
Manufacturing
Manufacturing industry
Neural networks
Sensors
Software
Support systems
Workers
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Summary: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 Bayesian network implementation can accurately recommend the next assembly step in 50% of the cases, but to the detriment of the prediction rate.
ISSN:2076-3417
2076-3417
DOI:10.3390/app12030985