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Ulaczyk, J., Morawiec, K., Zabierowski, P., Drobiazg, T. & Barreau, N. (2017) Finding Relevant Parameters for the Thin-film Photovoltaic Cells Production Process with the Application of Data Mining Methods. Molecular Informatics, 36 UNSP 1600161. 
Added by: Richard Baschera (2017-10-24 13:30:33)   Last edited by: Richard Baschera (2017-10-24 13:47:48)
Type de référence: Article
DOI: 10.1002/minf.201600161
Numéro d'identification (ISBN etc.): 1868-1743
Clé BibTeX: Ulaczyk2017
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Créateurs: Barreau, Drobiazg, Morawiec, Ulaczyk, Zabierowski
Collection: Molecular Informatics
Consultations : 2/275
Indice de consultation : 2%
Indice de popularité : 0.5%
A data mining approach is proposed as a useful tool for the control parameters analysis of the 3-stage CIGSe photovoltaic cell production process, in order to find variables that are the most relevant for cell electric parameters and efficiency. The analysed data set consists of stage duration times, heater power values as well as temperatures for the element sources and the substrate - there are 14 variables per sample in total. The most relevant variables of the process have been found based on the so-called random forest analysis with the application of the Boruta algorithm. 118 CIGSe samples, prepared at Institut des Materiaux Jean Rouxel, were analysed. The results are close to experimental knowledge on the CIGSe cells production process. They bring new evidence to production parameters of new cells and further research.
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