A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry
Jute is a bio-degradable, agro-renewable, and widely available lingo cellulosic fiber having high tensile strength and initial modulus, moisture regain, good sound, and heat insulation properties. For these unique properties and eco-friendly nature of jute fibers, jute-based products are now widely...
| Main Authors: | , , , , , , , |
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| Format: | Article |
| Language: | English |
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Multidisciplinary Digital Publishing Institute (MDPI)
2022
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| Online Access: | http://umpir.ump.edu.my/id/eprint/42709/ http://umpir.ump.edu.my/id/eprint/42709/1/A%20prognostic%20based%20fuzzy%20logic%20method%20to%20speculate%20yarn%20quality%20ratio%20in%20jute%20spinning%20industry.pdf |
| _version_ | 1848826682331365376 |
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| author | Paul, Tamal Krishna Jalil, Tazin Ibna Parvez, Md. Shohan Repon, Md Reazuddin Hossain, Ismail Alim, Md Abdul Islam, Tarikul Jalil, Mohammad Abdul |
| author_facet | Paul, Tamal Krishna Jalil, Tazin Ibna Parvez, Md. Shohan Repon, Md Reazuddin Hossain, Ismail Alim, Md Abdul Islam, Tarikul Jalil, Mohammad Abdul |
| author_sort | Paul, Tamal Krishna |
| building | UMP Institutional Repository |
| collection | Online Access |
| description | Jute is a bio-degradable, agro-renewable, and widely available lingo cellulosic fiber having high tensile strength and initial modulus, moisture regain, good sound, and heat insulation properties. For these unique properties and eco-friendly nature of jute fibers, jute-based products are now widely used in many sectors such as packaging, home textiles, agro textiles, build textiles, and so forth. The diversified applications of jute products create an excellent opportunity to mitigate the negative environmental effect of petroleum-based products. For producing the best quality jute products, the main prerequisite is to ensure the jute yarn quality that can be defined by the load at break (L.B), strain at break (S.B), tenacity at break (T.B), and tensile modulus (T.M). However, good quality yarn production by considering these parameters is quite difficult because these parameters follow a non-linear relationship. Therefore, it is essential to build up a model that can cover this entire inconsistent pattern and forecast the yarn quality accurately. That is why, in this study, a laboratory-based research work was performed to develop a fuzzy model to predict the quality of jute yarn considering L.B, S.B, T.B, and T.M as input parameters. For this purpose, 173 tex (5 lb/spindle) and 241 tex (7 lb/spindle) were produced, and then L.B, S.B, T.B and T.M values were measured. Using this measured value, a fuzzy model was developed to determine the optimum L.B, S.B, T.B, and T.M to produce the best quality jute yarn. In our proposed fuzzy model, for 173 tex and 241 tex yarn count, the mean relative error was found to be 1.46% (Triangular membership) and 1.48% (Gaussian membership), respectively, and the correlation coefficient was 0.93 for both triangular and gaussian membership function. This result validated the effectiveness of the proposed fuzzy model for an industrial application. The developed fuzzy model may help a spinner to produce the best quality jute yarn. |
| first_indexed | 2025-11-15T03:48:42Z |
| format | Article |
| id | ump-42709 |
| institution | Universiti Malaysia Pahang |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-15T03:48:42Z |
| publishDate | 2022 |
| publisher | Multidisciplinary Digital Publishing Institute (MDPI) |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | ump-427092025-01-07T03:53:40Z http://umpir.ump.edu.my/id/eprint/42709/ A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry Paul, Tamal Krishna Jalil, Tazin Ibna Parvez, Md. Shohan Repon, Md Reazuddin Hossain, Ismail Alim, Md Abdul Islam, Tarikul Jalil, Mohammad Abdul HD Industries. Land use. Labor Q Science (General) T Technology (General) Jute is a bio-degradable, agro-renewable, and widely available lingo cellulosic fiber having high tensile strength and initial modulus, moisture regain, good sound, and heat insulation properties. For these unique properties and eco-friendly nature of jute fibers, jute-based products are now widely used in many sectors such as packaging, home textiles, agro textiles, build textiles, and so forth. The diversified applications of jute products create an excellent opportunity to mitigate the negative environmental effect of petroleum-based products. For producing the best quality jute products, the main prerequisite is to ensure the jute yarn quality that can be defined by the load at break (L.B), strain at break (S.B), tenacity at break (T.B), and tensile modulus (T.M). However, good quality yarn production by considering these parameters is quite difficult because these parameters follow a non-linear relationship. Therefore, it is essential to build up a model that can cover this entire inconsistent pattern and forecast the yarn quality accurately. That is why, in this study, a laboratory-based research work was performed to develop a fuzzy model to predict the quality of jute yarn considering L.B, S.B, T.B, and T.M as input parameters. For this purpose, 173 tex (5 lb/spindle) and 241 tex (7 lb/spindle) were produced, and then L.B, S.B, T.B and T.M values were measured. Using this measured value, a fuzzy model was developed to determine the optimum L.B, S.B, T.B, and T.M to produce the best quality jute yarn. In our proposed fuzzy model, for 173 tex and 241 tex yarn count, the mean relative error was found to be 1.46% (Triangular membership) and 1.48% (Gaussian membership), respectively, and the correlation coefficient was 0.93 for both triangular and gaussian membership function. This result validated the effectiveness of the proposed fuzzy model for an industrial application. The developed fuzzy model may help a spinner to produce the best quality jute yarn. Multidisciplinary Digital Publishing Institute (MDPI) 2022-09 Article PeerReviewed pdf en cc_by_4 http://umpir.ump.edu.my/id/eprint/42709/1/A%20prognostic%20based%20fuzzy%20logic%20method%20to%20speculate%20yarn%20quality%20ratio%20in%20jute%20spinning%20industry.pdf Paul, Tamal Krishna and Jalil, Tazin Ibna and Parvez, Md. Shohan and Repon, Md Reazuddin and Hossain, Ismail and Alim, Md Abdul and Islam, Tarikul and Jalil, Mohammad Abdul (2022) A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry. Textiles, 2 (3). pp. 422-435. ISSN 2673-7248. (Published) https://doi.org/10.3390/textiles2030023 https://doi.org/10.3390/textiles2030023 |
| spellingShingle | HD Industries. Land use. Labor Q Science (General) T Technology (General) Paul, Tamal Krishna Jalil, Tazin Ibna Parvez, Md. Shohan Repon, Md Reazuddin Hossain, Ismail Alim, Md Abdul Islam, Tarikul Jalil, Mohammad Abdul A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title | A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title_full | A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title_fullStr | A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title_full_unstemmed | A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title_short | A prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| title_sort | prognostic based fuzzy logic method to speculate yarn quality ratio in jute spinning industry |
| topic | HD Industries. Land use. Labor Q Science (General) T Technology (General) |
| url | http://umpir.ump.edu.my/id/eprint/42709/ http://umpir.ump.edu.my/id/eprint/42709/ http://umpir.ump.edu.my/id/eprint/42709/ http://umpir.ump.edu.my/id/eprint/42709/1/A%20prognostic%20based%20fuzzy%20logic%20method%20to%20speculate%20yarn%20quality%20ratio%20in%20jute%20spinning%20industry.pdf |