Browsing by Author "Smriti, Shamima Akter"

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Fuzzy Modelling for Prediction of Bursting Strength of Knitted Cotton Fabric Using Bleaching Process Variables
(AATCC Journal of Research, 2019-01-01) Haque, Abu Naser Md. Ahsanul; Smriti, Shamima Akter; Farzana, Nawshin; Siddiqa, Fahmida; Islam, Md. Azharul
A fuzzy prediction model has been built based on hydrogen peroxide concentration, bleaching temperature, and time of bleaching as the input variables and knitted cotton fabric bursting strength as the output variable. Fuzzy expert systems can map efficiently in nonlinear domains with minimal experimental data. The model developed in the present study has been validated by new experimental data. The root means square, mean absolute error percentage, and coefficient of determination (R 2) between the predicted and experimental values were found to be 4.89, 0.707, and 0.965 respectively. The results confirm that the model can be applied successfully for the prediction of fabric bursting strength in textile dye houses.
Prediction of whiteness index of cotton using bleaching process variables by fuzzy inference system
(2018-02-28) Naser, Abu; Haque, Md. Ahsanul; Smriti, Shamima Akter; Hussain, Manwar; Farzana, Nawshin; Siddiqa, Fahmida; Islam, Md. Azharul
A fuzzy prediction model has been built based on hydrogen peroxide concentration, temperature and time of bleaching as the input variables and knitted fabric whiteness index as the output variable. The process parameters affecting the whiteness index of cotton knitted fabrics are very non-linear. Fuzzy inference system is a prospective modeling tool as it can map effectively in nonlinear domain with minimum investigational data. Triangular-shaped membership functions were considered for the variables and total 48 rules were created in this study. It was found that the sole effect of the concentration of hydrogen peroxide on whiteness is pretty low, but is affected by temperature noticeably even in a fixed concentration of hydrogen peroxide. The model proposed in the present study has been verified by additional experimental data set. The root mean square, mean absolute error percentage and coefficient of determination (R 2 ) between the predicted and experimental values were found to be 0.536, 0.798 and 0.959 respectively. The results validate that the model can be applied suitably for the prediction of fabric whiteness index in textile industries.
Prognosis of Dimensional Stability and Mass per Unit Area of Single Jersey Cotton Knitted Fabric with Fuzzy Inference System [Napoved Dimenzijske Stabilnosti in PloščInske Mase BombažNega Levo-Desnega Pletiva S Sistemom Mehkega Sklepanja]
(Tekstilec, University of Ljubljana, 2019-09-07) Smriti, Shamima Akter; Belal, Shah Alimuzzaman; Haque, Md. Mahbubul; Hossain, Md. Ismail; Farzana, Nawshin; Haque, Abu Naser Md Ahsanul
Endeavour has been made in this research work using experimental data for constructing a fuzzy inference model based on the Mamdani approach to prognosticate the shrinkage and mass per unit area of a single jersey cotton knitted fabric. To control the dimensional stability of the cotton knitted fabric in advance, an artifi cial intelligent system is required in the knitting industry which simulates all product and process variables and is able to give human-like decisions in advance. The most important controlling parameters of knitted fabric properties such as stitch length, yarn count and overfeed percentage in stenter were considered as input variables, and mass per unit area, lengthwise shrinkage and widthwise shrinkage as output variables. Overall, 35 experiments were conducted to construct the model, varying different parameters. The applicability of the model was validated by comparing the results from 15 newly conducted experiments. The coeffi cient of determination of predicted and actual data for mass per unit area, lengthwise shrinkage and widthwise shrinkage were 0.97, 0.99 and 0.99, respectively which validates the model relatively effectively for an industrial application. The proposed model can assist a fabric manufacturer by taking a decision in selecting knitting and fi nishing parameters prior to producing the fabric. Moreover, it can reduce the time and energy required, and waste produced in the process by skipping the sample development step before bulk production.
Textile Colouration With Natural Colourants
(Daffodil International University, 2022-05-15) Uddin, Mohammad Abbas; Rahman, Md. Mahbubor; Haque, Abu Naser Md Ahsanul; Smriti, Shamima Akter; Datta, Eshita; Farzana, Nawshin; Chowdhury, Sutapa; Haider, Julfikar; Sayem, Abu Sadat Muhammad
This paper provides an in-depth review of the natural colourants covering their classifications, sources, extraction techniques, application techniques in relation to different textile fibres and their advantages and challenges. The academic readers will find here an overview of the latest developments in extraction and application techniques of a variety of natural colourants. Almost all commercially produced natural fibres and the major synthetic fibres are found to be dyeable and printable with natural colourants. Although the production of natural colourants offers a lot of environmental benefits, their application techniques in textile colouration are not always sound for environment due to the need of synthetic mordants in colouration process. Advances in modern agriculture and biotechnology can play a key role in sorting the limitations of natural colourants and at the same time more and more investigations are still required to establish their cleaner application on textiles