Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant
Polypropylene is a multi-reason thermoplastic resin with ample of scope for engineering applications. This article presents a very distinct and new methodology called linguistic Response Surface Methodology (RSM) for predicting the quality of polypropylene used in petrochemical industries. This mode...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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Elsevier
2022-06-01
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| Series: | Cleaner Chemical Engineering |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S2772782322000109 |
| _version_ | 1797820521632497664 |
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| author | Dipak Kumar Jana Sudipta Roy Priyanka Dey Barnali Bej |
| author_facet | Dipak Kumar Jana Sudipta Roy Priyanka Dey Barnali Bej |
| author_sort | Dipak Kumar Jana |
| collection | DOAJ |
| description | Polypropylene is a multi-reason thermoplastic resin with ample of scope for engineering applications. This article presents a very distinct and new methodology called linguistic Response Surface Methodology (RSM) for predicting the quality of polypropylene used in petrochemical industries. This model is framed on the basis of a huge quantity of data obtained from well-known Indian chemical factories. The quality of polypropylene depends on factors such as melt flow index and solubility of the product in xylene. The parameters controlling both the factors are the hydrogen flow, the donor flow, and, the pressure and temperature of the polymerization reactor. Using these four input and output parameters, a response surface method based on the different features of the variable is created. Then the simulation results are compared with the collected plant information and the most appropriate model is selected through a series of fact-finding. This linguistic surface response method, when compared with Type 1, and Type 2 fuzzy logic, was found to provide the maximum value of R. An ANNOVA analysis of the experimental data was done to determine the reliability, the repetition, and the efficiency of the constructed regression models. This method will not only save the expenses but also the time, generally being taken by the other models. |
| first_indexed | 2024-03-13T09:40:35Z |
| format | Article |
| id | doaj.art-8136724f980545cfacac4818734baa16 |
| institution | Directory Open Access Journal |
| issn | 2772-7823 |
| language | English |
| last_indexed | 2024-03-13T09:40:35Z |
| publishDate | 2022-06-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Cleaner Chemical Engineering |
| spelling | doaj.art-8136724f980545cfacac4818734baa162023-05-25T04:25:33ZengElsevierCleaner Chemical Engineering2772-78232022-06-012100010Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plantDipak Kumar Jana0Sudipta Roy1Priyanka Dey2Barnali Bej3Corresponding author.; School of Applied Science & Humanities, Haldia Institute of Technology, Haldia, Purba Midnapur, West Bengal 721657, IndiaSchool of Applied Science & Humanities, Haldia Institute of Technology, Haldia, Purba Midnapur, West Bengal 721657, IndiaSchool of Applied Science & Humanities, Haldia Institute of Technology, Haldia, Purba Midnapur, West Bengal 721657, IndiaDepartment of Chemical Engineering, Haldia Institute of Technology Haldia, Purba Midnapur, West Bengal 721657, IndiaPolypropylene is a multi-reason thermoplastic resin with ample of scope for engineering applications. This article presents a very distinct and new methodology called linguistic Response Surface Methodology (RSM) for predicting the quality of polypropylene used in petrochemical industries. This model is framed on the basis of a huge quantity of data obtained from well-known Indian chemical factories. The quality of polypropylene depends on factors such as melt flow index and solubility of the product in xylene. The parameters controlling both the factors are the hydrogen flow, the donor flow, and, the pressure and temperature of the polymerization reactor. Using these four input and output parameters, a response surface method based on the different features of the variable is created. Then the simulation results are compared with the collected plant information and the most appropriate model is selected through a series of fact-finding. This linguistic surface response method, when compared with Type 1, and Type 2 fuzzy logic, was found to provide the maximum value of R. An ANNOVA analysis of the experimental data was done to determine the reliability, the repetition, and the efficiency of the constructed regression models. This method will not only save the expenses but also the time, generally being taken by the other models.http://www.sciencedirect.com/science/article/pii/S2772782322000109PolypropyleneProduct qualityLinguistic response surface methodologyANNOVA Analysis |
| spellingShingle | Dipak Kumar Jana Sudipta Roy Priyanka Dey Barnali Bej Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant Cleaner Chemical Engineering Polypropylene Product quality Linguistic response surface methodology ANNOVA Analysis |
| title | Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant |
| title_full | Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant |
| title_fullStr | Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant |
| title_full_unstemmed | Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant |
| title_short | Utilization of a linguistic response surface methodology to the business strategy of polypropylene in an Indian petrochemical plant |
| title_sort | utilization of a linguistic response surface methodology to the business strategy of polypropylene in an indian petrochemical plant |
| topic | Polypropylene Product quality Linguistic response surface methodology ANNOVA Analysis |
| url | http://www.sciencedirect.com/science/article/pii/S2772782322000109 |
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