Abnormal Operation Tracking through Big-Data-Based Gram–Schmidt Orthogonalization: Production of n-Propyl Propionate in a Simulated Moving-Bed Reactor: A Case Study

Autor:	Márcio A. F. Martins, Alírio E. Rodrigues, Vinicius V. Santana, José M. Loureiro, Ana M. Ribeiro, Idelfonso B.R. Nogueira
Rok vydání:	2021
Předmět:	chemistry.chemical_classification business.industry Computer science General Chemical Engineering Data management Big data Process (computing) 02 engineering and technology General Chemistry 021001 nanoscience & nanotechnology computer.software_genre Tracking (particle physics) Industrial and Manufacturing Engineering chemistry.chemical_compound 020401 chemical engineering chemistry Propionate Production (economics) Data mining Gram–Schmidt process 0204 chemical engineering Simulated moving bed 0210 nano-technology business computer
Zdroj:	Industrial & Engineering Chemistry Research. 60:4060-4071
ISSN:	1520-5045 0888-5885
Popis:	Big Data Analytics plays a crucial role in Industry 4.0 by offering tools to improve the decision-making process. These tools comprise data management infrastructures and analytical methods. Among ...
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::b62df9800b5ab3ad58c0e05a7cee2601 https://doi.org/10.1021/acs.iecr.1c00214 Zobrazit plný text záznamu