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https://doi.org/10.21278/TOF.451020920

Data-Driven Causal Modeling of the Manufacturing System

Gabriel-Radu Frumusanu   ORCID icon orcid.org/0000-0003-3038-8758 ; Department of Manufacturing Engineering, ‘Dunarea de Jos’ University, Faculty of Engineering, Galati, Romania
Cezarina Afteni ; Department of Manufacturing Engineering, ‘Dunarea de Jos’ University, Faculty of Engineering, Galati, Romania
Alexandru Epureanu ; Department of Manufacturing Engineering, ‘Dunarea de Jos’ University, Faculty of Engineering, Galati, Romania

Puni tekst: engleski, pdf (2 MB) str. 43-62 preuzimanja: 63* citiraj
APA 6th Edition
Frumusanu, G., Afteni, C. i Epureanu, A. (2021). Data-Driven Causal Modeling of the Manufacturing System. Transactions of FAMENA, 45 (1), 43-62. https://doi.org/10.21278/TOF.451020920
MLA 8th Edition
Frumusanu, Gabriel-Radu, et al. "Data-Driven Causal Modeling of the Manufacturing System." Transactions of FAMENA, vol. 45, br. 1, 2021, str. 43-62. https://doi.org/10.21278/TOF.451020920. Citirano 24.06.2021.
Chicago 17th Edition
Frumusanu, Gabriel-Radu, Cezarina Afteni i Alexandru Epureanu. "Data-Driven Causal Modeling of the Manufacturing System." Transactions of FAMENA 45, br. 1 (2021): 43-62. https://doi.org/10.21278/TOF.451020920
Harvard
Frumusanu, G., Afteni, C., i Epureanu, A. (2021). 'Data-Driven Causal Modeling of the Manufacturing System', Transactions of FAMENA, 45(1), str. 43-62. https://doi.org/10.21278/TOF.451020920
Vancouver
Frumusanu G, Afteni C, Epureanu A. Data-Driven Causal Modeling of the Manufacturing System. Transactions of FAMENA [Internet]. 2021 [pristupljeno 24.06.2021.];45(1):43-62. https://doi.org/10.21278/TOF.451020920
IEEE
G. Frumusanu, C. Afteni i A. Epureanu, "Data-Driven Causal Modeling of the Manufacturing System", Transactions of FAMENA, vol.45, br. 1, str. 43-62, 2021. [Online]. https://doi.org/10.21278/TOF.451020920

Sažetak
In manufacturing system management, the decisions are currently made on the base of ‘what if’ analysis. Here, the suitability of the model structure based on which a model of the activity will be built is crucial and it refers to multiple conditionality imposed in practice. Starting from this, finding the most suitable model structure is critical and represents a notable challenge. The paper deals with the building of suitable structures for a manufacturing system model by data-driven causal modelling. For this purpose, the manufacturing system is described by nominal jobs that it could involve and is identified by an original algorithm for processing the dataset of previous instances. The proposed causal modelling is applied in two case studies, whereby the first case study uses a dataset of artificial instances and the second case study uses a dataset of industrial instances. The causal modelling results prove its good potential for implementation in the industrial environment, with a very wide range of possible applications, while the obtained performance has been found to be good.

Ključne riječi
manufacturing system; causal modelling; ‘what-if’ analysis; instance-based learning

Hrčak ID: 257227

URI
https://hrcak.srce.hr/257227

Posjeta: 116 *