Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame
Ferronickel contains 60–80 wt% Fe and 40–20 wt% Ni and is a feedstock for manufacturing stainless steel and other ferrous alloys. The primary pyrometallurgical route to produce ferronickel from laterite nickel ores is the Rotary Kiln-Electric Furnace (RKEF) process. In the RKEF process, minerals und...
| Main Authors: | , , , , , , , , |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2022-04-01
|
| Series: | Alexandria Engineering Journal |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1110016821005512 |
| _version_ | 1818284129722040320 |
|---|---|
| author | Johanna M. Romero Yuleisy S. Pardo Maricel Parra Andy De J. Castillo Heriberto Maury Lesme Corredor Iván Sánchez Bernardo Rueda Arturo Gonzalez-Quiroga |
| author_facet | Johanna M. Romero Yuleisy S. Pardo Maricel Parra Andy De J. Castillo Heriberto Maury Lesme Corredor Iván Sánchez Bernardo Rueda Arturo Gonzalez-Quiroga |
| author_sort | Johanna M. Romero |
| collection | DOAJ |
| description | Ferronickel contains 60–80 wt% Fe and 40–20 wt% Ni and is a feedstock for manufacturing stainless steel and other ferrous alloys. The primary pyrometallurgical route to produce ferronickel from laterite nickel ores is the Rotary Kiln-Electric Furnace (RKEF) process. In the RKEF process, minerals undergo calcination and partial reduction in a rotary kiln. Large amounts of mineral dust leave the kiln entrained in flue gases. Dust insufflation is a potential solution in which dust particles enter directly into the burner flame. The aim is that the insufflated dust softens, agglomerates, and finally joins the minerals stream that goes into the electric furnace. We applied data analytics techniques to a 1-year operation database to assess the operation before and after dust insufflation in an industrial rotary kiln furnace. Bootstrapping revealed statistically significant differences in the operation with and without dust insufflation. Principal Component Analysis (PCA) and k-means clustering were used as exploratory techniques. PCA showed subsets of variables that significantly influence the dataset variance, and k-means allowed distinguishing operation conditions for dust insufflation with encouraging results for the calcine-to-fresh mineral and the natural gas-to-calcine ratios. These results pave the way towards successfully implementing dust insufflation in the RKEF process. |
| first_indexed | 2024-12-13T00:47:54Z |
| format | Article |
| id | doaj.art-981081f2143f4324823d24a2a0caff5b |
| institution | Directory Open Access Journal |
| issn | 1110-0168 |
| language | English |
| last_indexed | 2024-12-13T00:47:54Z |
| publishDate | 2022-04-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Alexandria Engineering Journal |
| spelling | doaj.art-981081f2143f4324823d24a2a0caff5b2022-12-22T00:05:00ZengElsevierAlexandria Engineering Journal1110-01682022-04-0161432153228Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flameJohanna M. Romero0Yuleisy S. Pardo1Maricel Parra2Andy De J. Castillo3Heriberto Maury4Lesme Corredor5Iván Sánchez6Bernardo Rueda7Arturo Gonzalez-Quiroga8Department of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaDepartment of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaDepartment of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaDepartment of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaDepartment of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaUREMA Research Unit, Department of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, ColombiaCerro Matoso S.A, Montelíbano, ColombiaCerro Matoso S.A, Montelíbano, ColombiaUREMA Research Unit, Department of Mechanical Engineering, Universidad del Norte, Barranquilla 080001, Colombia; Corresponding author.Ferronickel contains 60–80 wt% Fe and 40–20 wt% Ni and is a feedstock for manufacturing stainless steel and other ferrous alloys. The primary pyrometallurgical route to produce ferronickel from laterite nickel ores is the Rotary Kiln-Electric Furnace (RKEF) process. In the RKEF process, minerals undergo calcination and partial reduction in a rotary kiln. Large amounts of mineral dust leave the kiln entrained in flue gases. Dust insufflation is a potential solution in which dust particles enter directly into the burner flame. The aim is that the insufflated dust softens, agglomerates, and finally joins the minerals stream that goes into the electric furnace. We applied data analytics techniques to a 1-year operation database to assess the operation before and after dust insufflation in an industrial rotary kiln furnace. Bootstrapping revealed statistically significant differences in the operation with and without dust insufflation. Principal Component Analysis (PCA) and k-means clustering were used as exploratory techniques. PCA showed subsets of variables that significantly influence the dataset variance, and k-means allowed distinguishing operation conditions for dust insufflation with encouraging results for the calcine-to-fresh mineral and the natural gas-to-calcine ratios. These results pave the way towards successfully implementing dust insufflation in the RKEF process.http://www.sciencedirect.com/science/article/pii/S1110016821005512Nickel lateriteCalcinationReductionAgglomerationMachine learningData handling |
| spellingShingle | Johanna M. Romero Yuleisy S. Pardo Maricel Parra Andy De J. Castillo Heriberto Maury Lesme Corredor Iván Sánchez Bernardo Rueda Arturo Gonzalez-Quiroga Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame Alexandria Engineering Journal Nickel laterite Calcination Reduction Agglomeration Machine learning Data handling |
| title | Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame |
| title_full | Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame |
| title_fullStr | Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame |
| title_full_unstemmed | Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame |
| title_short | Improving the rotary kiln-electric furnace process for ferronickel production: Data analytics-based assessment of dust insufflation into the rotary kiln flame |
| title_sort | improving the rotary kiln electric furnace process for ferronickel production data analytics based assessment of dust insufflation into the rotary kiln flame |
| topic | Nickel laterite Calcination Reduction Agglomeration Machine learning Data handling |
| url | http://www.sciencedirect.com/science/article/pii/S1110016821005512 |
| work_keys_str_mv | AT johannamromero improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT yuleisyspardo improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT maricelparra improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT andydejcastillo improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT heribertomaury improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT lesmecorredor improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT ivansanchez improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT bernardorueda improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame AT arturogonzalezquiroga improvingtherotarykilnelectricfurnaceprocessforferronickelproductiondataanalyticsbasedassessmentofdustinsufflationintotherotarykilnflame |