Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process
Uncertainty in industrial processes is very common, but it is particularly high in the grinding process (GP), due to the set of interacting operating/design parameters. This uncertainty can be evaluated in different ways, but, without a doubt, one of the most important parameters that characterise a...
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-08-01
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| Series: | Minerals |
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| Online Access: | https://www.mdpi.com/2075-163X/11/8/862 |
| _version_ | 1797522769863245824 |
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| author | José Delgado Freddy A. Lucay Felipe D. Sepúlveda |
| author_facet | José Delgado Freddy A. Lucay Felipe D. Sepúlveda |
| author_sort | José Delgado |
| collection | DOAJ |
| description | Uncertainty in industrial processes is very common, but it is particularly high in the grinding process (GP), due to the set of interacting operating/design parameters. This uncertainty can be evaluated in different ways, but, without a doubt, one of the most important parameters that characterise all GPs is the particle size distribution (PSD). However, is the PSD a good way to quantify the uncertainty in the milling process? This is the question we attempt to answer in this paper. To do so, we use 10 experimental grinding repetitions, 3 grinding times, and 14 Tyler meshes (more than 400 experimental results). The most relevant results were compared for the weight percentage for each size (WPES), cumulative weight undersize (CWU), or the use of particle size distribution models (PSDM), in terms of continuous changes in statistical parameters in WPES for different grinding times. The probability distribution was found to be changeable when reporting the results of WPES/CWU/PSDM, we detected the over-/under-estimation of uncertainty when using WPES/CWU, and variations in the relationships between sizes were observed when using WPES/CWU. Finally, our conclusion was that the way in which the data are analysed is not trivial, due to the possible deviations that may occur in the uncertainty process. |
| first_indexed | 2024-03-10T08:34:03Z |
| format | Article |
| id | doaj.art-4af6a6d0748545bda1948bf011f05643 |
| institution | Directory Open Access Journal |
| issn | 2075-163X |
| language | English |
| last_indexed | 2024-03-10T08:34:03Z |
| publishDate | 2021-08-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Minerals |
| spelling | doaj.art-4af6a6d0748545bda1948bf011f056432023-11-22T08:50:03ZengMDPI AGMinerals2075-163X2021-08-0111886210.3390/min11080862Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding ProcessJosé Delgado0Freddy A. Lucay1Felipe D. Sepúlveda2Departamento de Ingeniería en Minas, Universidad de Antofagasta, Antofagasta 1240000, ChileEscuela de Ingeniería Química, Pontificia Universidad Católica de Valparaíso, Valparaíso 2340000, ChileDepartamento de Ingeniería en Minas, Universidad de Antofagasta, Antofagasta 1240000, ChileUncertainty in industrial processes is very common, but it is particularly high in the grinding process (GP), due to the set of interacting operating/design parameters. This uncertainty can be evaluated in different ways, but, without a doubt, one of the most important parameters that characterise all GPs is the particle size distribution (PSD). However, is the PSD a good way to quantify the uncertainty in the milling process? This is the question we attempt to answer in this paper. To do so, we use 10 experimental grinding repetitions, 3 grinding times, and 14 Tyler meshes (more than 400 experimental results). The most relevant results were compared for the weight percentage for each size (WPES), cumulative weight undersize (CWU), or the use of particle size distribution models (PSDM), in terms of continuous changes in statistical parameters in WPES for different grinding times. The probability distribution was found to be changeable when reporting the results of WPES/CWU/PSDM, we detected the over-/under-estimation of uncertainty when using WPES/CWU, and variations in the relationships between sizes were observed when using WPES/CWU. Finally, our conclusion was that the way in which the data are analysed is not trivial, due to the possible deviations that may occur in the uncertainty process.https://www.mdpi.com/2075-163X/11/8/862experimental uncertainty analysisbatch grinding |
| spellingShingle | José Delgado Freddy A. Lucay Felipe D. Sepúlveda Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process Minerals experimental uncertainty analysis batch grinding |
| title | Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process |
| title_full | Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process |
| title_fullStr | Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process |
| title_full_unstemmed | Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process |
| title_short | Experimental Uncertainty Analysis for the Particle Size Distribution for Better Understanding of Batch Grinding Process |
| title_sort | experimental uncertainty analysis for the particle size distribution for better understanding of batch grinding process |
| topic | experimental uncertainty analysis batch grinding |
| url | https://www.mdpi.com/2075-163X/11/8/862 |
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