Reduction of energy and fuel consumption in the hot-rolling steel sector
Furnace oil consumption, electric energy consumption, waste owing to mill scale, and process scrap due to cropping length are essential production indicators that must be monitored for economical production with minimal environmental impact.The study examined the effect of mill setting schedules or...
| Main Authors: | , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2023-12-01
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| Series: | Cleaner Engineering and Technology |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2666790823000940 |
| _version_ | 1797386770740936704 |
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| author | Gulvir Singh Pradeep K. Singh |
| author_facet | Gulvir Singh Pradeep K. Singh |
| author_sort | Gulvir Singh |
| collection | DOAJ |
| description | Furnace oil consumption, electric energy consumption, waste owing to mill scale, and process scrap due to cropping length are essential production indicators that must be monitored for economical production with minimal environmental impact.The study examined the effect of mill setting schedules or roll pass designs on furnace oil consumption, electricity consumption, mill scale generation and end cropping loss in a steel bar hot rolling plant. Rolling experiments were performed in a hot rolling steel plant. The results obtained from the rolling plant experiments were compared with the results obtained with the help of computer simulation.A t-test is an inferential statistic used to determine if there is a significant difference between the means of two groups. The results of plant experimentation and simulation were compared by performing t-test. The simulations results were found to be comparable to experimental results. After validation, simulation experiments were performed for the mill setting process parameters beyond the range possible in the rolling plant. Regression equations linking input process parameters with response parameters were created with the help of statistical analysis.The optimum mill setting parameters for minimum consumption of fuel oil, electrical energy, minimum generation of mill scale and end cropping loss have been attained. |
| first_indexed | 2024-03-08T22:14:09Z |
| format | Article |
| id | doaj.art-599a85af598b4d1cbeaf9b9c8e00124f |
| institution | Directory Open Access Journal |
| issn | 2666-7908 |
| language | English |
| last_indexed | 2024-03-08T22:14:09Z |
| publishDate | 2023-12-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cleaner Engineering and Technology |
| spelling | doaj.art-599a85af598b4d1cbeaf9b9c8e00124f2023-12-19T04:17:35ZengElsevierCleaner Engineering and Technology2666-79082023-12-0117100689Reduction of energy and fuel consumption in the hot-rolling steel sectorGulvir Singh0Pradeep K. Singh1Department of Mechanical Engineering, Guru Nanak Dev Engineering College, Ludhiana, 141006, IndiaDepartment of Mechanical Engineering, Sant Longowal Institute of Engineering & Technology, Longowal, 148106, India; Corresponding author.Furnace oil consumption, electric energy consumption, waste owing to mill scale, and process scrap due to cropping length are essential production indicators that must be monitored for economical production with minimal environmental impact.The study examined the effect of mill setting schedules or roll pass designs on furnace oil consumption, electricity consumption, mill scale generation and end cropping loss in a steel bar hot rolling plant. Rolling experiments were performed in a hot rolling steel plant. The results obtained from the rolling plant experiments were compared with the results obtained with the help of computer simulation.A t-test is an inferential statistic used to determine if there is a significant difference between the means of two groups. The results of plant experimentation and simulation were compared by performing t-test. The simulations results were found to be comparable to experimental results. After validation, simulation experiments were performed for the mill setting process parameters beyond the range possible in the rolling plant. Regression equations linking input process parameters with response parameters were created with the help of statistical analysis.The optimum mill setting parameters for minimum consumption of fuel oil, electrical energy, minimum generation of mill scale and end cropping loss have been attained.http://www.sciencedirect.com/science/article/pii/S2666790823000940Furnace oil consumptionElectric energy consumptionMill scaleSteel hot rollingCropping loss |
| spellingShingle | Gulvir Singh Pradeep K. Singh Reduction of energy and fuel consumption in the hot-rolling steel sector Cleaner Engineering and Technology Furnace oil consumption Electric energy consumption Mill scale Steel hot rolling Cropping loss |
| title | Reduction of energy and fuel consumption in the hot-rolling steel sector |
| title_full | Reduction of energy and fuel consumption in the hot-rolling steel sector |
| title_fullStr | Reduction of energy and fuel consumption in the hot-rolling steel sector |
| title_full_unstemmed | Reduction of energy and fuel consumption in the hot-rolling steel sector |
| title_short | Reduction of energy and fuel consumption in the hot-rolling steel sector |
| title_sort | reduction of energy and fuel consumption in the hot rolling steel sector |
| topic | Furnace oil consumption Electric energy consumption Mill scale Steel hot rolling Cropping loss |
| url | http://www.sciencedirect.com/science/article/pii/S2666790823000940 |
| work_keys_str_mv | AT gulvirsingh reductionofenergyandfuelconsumptioninthehotrollingsteelsector AT pradeepksingh reductionofenergyandfuelconsumptioninthehotrollingsteelsector |