Real-Time Assembly Support System with Hidden Markov Model and Hybrid Extensions

Autor: Arpad Gellert, Stefan-Alexandru Precup, Alexandru Matei, Bogdan-Constantin Pirvu, Constantin-Bala Zamfirescu
Jazyk: angličtina
Rok vydání: 2022
Předmět:
Zdroj: Mathematics, Vol 10, Iss 15, p 2725 (2022)
Druh dokumentu: article
ISSN: 10152725
2227-7390
DOI: 10.3390/math10152725
Popis: This paper presents a context-aware adaptive assembly assistance system meant to support factory workers by embedding predictive capabilities. The research is focused on the predictor which suggests the next assembly step. Hidden Markov models are analyzed for this purpose. Several prediction methods have been previously evaluated and the prediction by partial matching, which was the most efficient, is considered in this work as a component of a hybrid model together with an optimally configured hidden Markov model. The experimental results show that the hidden Markov model is a viable choice to predict the next assembly step, whereas the hybrid predictor is even better, outperforming in some cases all the other models. Nevertheless, an assembly assistance system meant to support factory workers needs to embed multiple models to exhibit valuable predictive capabilities.
Databáze: Directory of Open Access Journals
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