@misc{biswas_chakraborty_bhattacharjee_mohammed_2021, title={4D Printing of Shape Memory Materials for Textiles: Mechanism, Mathematical Modeling, and Challenges}, volume={31}, ISSN={["1616-3028"]}, url={https://doi.org/10.1002/adfm.202100257}, DOI={10.1002/adfm.202100257}, abstractNote={AbstractShape memory materials (SMMs) in 3D printing (3DP) technology garnered much attention due to their ability to respond to external stimuli, which direct this technology toward an emerging area of research, “4D printing (4DP) technology.” In contrast to classical 3D printed objects, the fourth dimension, time, allows printed objects to undergo significant changes in shape, size, or color when subjected to external stimuli. Highly precise and calibrated 4D materials, which can perform together to achieve robust 4D objects, are in great demand in various fields such as military applications, space suits, robotic systems, apparel, healthcare, sports, etc. This review, for the first time, to the best of the authors’ knowledge, focuses on recent advances in SMMs (e.g., polymers, metals, etc.) based wearable smart textiles and fashion goods. This review integrates the basic overview of 3DP technology, fabrication methods, the transition of 3DP to 4DP, the chemistry behind the fundamental working principles of 4D printed objects, materials selection for smart textiles and fashion goods. The central part summarizes the effect of major external stimuli on 4D textile materials followed by the major applications. Lastly, prospects and challenges are discussed, so that future researchers can continue the progress of this technology.}, number={19}, journal={ADVANCED FUNCTIONAL MATERIALS}, publisher={Wiley}, author={Biswas, Manik Chandra and Chakraborty, Samit and Bhattacharjee, Abhishek and Mohammed, Zaheeruddin}, year={2021}, month={May} }
 @article{chakraborty_moore_parrillo-chapman_2022, title={Automatic defect detection for fabric printing using a deep convolutional neural network}, volume={15}, ISSN={["1754-3274"]}, DOI={10.1080/17543266.2021.1925355}, abstractNote={ABSTRACT Defect detection is a crucial step in textile and apparel quality control. An efficient defect detection system can ensure the overall quality of the processes and products that are acceptable to consumers. Existing techniques for real-time defect detection tend to vary according to unique manufacturing processes, focal defects and computational algorithms. Although the need is high, research related to automatic printed fabric defect detection processes is not prevalent in academic literatures. This research proposes a novel methodology that demonstrates the application of convolutional neural network (CNN) to classify printing defects based on the fabric images collected from industries. The research also integrated visual geometric group (VGG), DenseNet, Inception and Xception deep learning networks to compare model performance. The results exhibit that the VGG-based models perform better compared to a simple CNN model, suggesting promise for automatic defect detection (ADD) of printed fabrics that can improve profitability in fashion supply chains.}, number={2}, journal={INTERNATIONAL JOURNAL OF FASHION DESIGN TECHNOLOGY AND EDUCATION}, author={Chakraborty, Samit and Moore, Marguerite and Parrillo-Chapman, Lisa}, year={2022}, pages={142–157} }
 @misc{chakraborty_hoque_jeem_biswas_bardhan_lobaton_2021, title={Fashion Recommendation Systems, Models and Methods: A Review}, volume={8}, ISSN={["2227-9709"]}, url={https://doi.org/10.3390/informatics8030049}, DOI={10.3390/informatics8030049}, abstractNote={In recent years, the textile and fashion industries have witnessed an enormous amount of growth in fast fashion. On e-commerce platforms, where numerous choices are available, an efficient recommendation system is required to sort, order, and efficiently convey relevant product content or information to users. Image-based fashion recommendation systems (FRSs) have attracted a huge amount of attention from fast fashion retailers as they provide a personalized shopping experience to consumers. With the technological advancements, this branch of artificial intelligence exhibits a tremendous amount of potential in image processing, parsing, classification, and segmentation. Despite its huge potential, the number of academic articles on this topic is limited. The available studies do not provide a rigorous review of fashion recommendation systems and the corresponding filtering techniques. To the best of the authors’ knowledge, this is the first scholarly article to review the state-of-the-art fashion recommendation systems and the corresponding filtering techniques. In addition, this review also explores various potential models that could be implemented to develop fashion recommendation systems in the future. This paper will help researchers, academics, and practitioners who are interested in machine learning, computer vision, and fashion retailing to understand the characteristics of the different fashion recommendation systems.}, number={3}, journal={INFORMATICS-BASEL}, publisher={MDPI AG}, author={Chakraborty, Samit and Hoque, Md Saiful and Jeem, Naimur Rahman and Biswas, Manik Chandra and Bardhan, Deepayan and Lobaton, Edgar}, year={2021}, month={Sep} }
 @article{chakraborty_biswas_2020, title={3D printing technology of polymer-fiber composites in textile and fashion industry: a potential roadmap of concept to consumer}, url={http://dx.doi.org/10.1016/j.compstruct.2020.112562}, DOI={10.1016/j.compstruct.2020.112562}, abstractNote={Three-dimensional printing (3DP) technology has gained an increased popularity in making prototypes in all types of manufacturing industries including automotive, healthcare, aerospace, sports, textile, apparel and fashion industry etc. Researchers, textile technologists, fashion designers, manufacturers and retailers have been working on adopting 3DP technology in their respective fields since the last decade. 3DP has been proved highly beneficial in reducing manufacturing time and production cost significantly regarding fiber reinforced composites fabrication. However, the application of this technology is still at niche while it comes to manufacturing everyday clothing. The purpose of this paper is to provide an integrative review of the existing literature to identify current state-of-the-art 3DP methods, materials, application in the textile and fashion industries. Further, the review considers the future of this technology with regard to sustainability, novelty, complexity in fashion related fields.}, journal={Composite Structures}, publisher={Composite Structures}, author={Chakraborty, S. and Biswas, M.C.}, year={2020}, month={Jun} }
 @article{mozumder_chakraborty_hoque_2019, title={Evaluation of personal factors of workers affecting productivity in RMG sector in Bangladesh,Vpliv značilnosti osebnih dejavnikov zaposlenih na produktivnost sektorja konfekcioniranih oblačil v Bangladešu}, volume={62}, url={http://www.scopus.com/inward/record.url?eid=2-s2.0-85073412237&partnerID=MN8TOARS}, DOI={10.14502/Tekstilec2019.62.158-165}, abstractNote={The readymade garment sector in Bangladesh is considered the backbone of earning foreign currency that includes a large number of workers and is mostly responsible for the economic growth of the country. Nevertheless, despite the remarkable growth of the RMG sector and its bright projection, impediments need to be overcome as well. Readymade garment industries in Bangladesh are currently facing some challenges to ensure fi re safety and better work environment for garment workers. Apart from several technical factors, personal factors of workers, e.g. education, age, training, work experience and motivation, might also have a substantial impact on the increase in productivity to compete in the global export market. Thus, it was vital to observe the impacts personal factors of workers have on the productivity of readymade garment industries. This study enabled an identifi cation of personal factors of workers which aff ect the productivity of readymade garment industries. The factors were examined through some critical analyses, e.g. hypothesis test, factor analysis and fi shbone diagram analysis. After the investigation of empirical data, principal factors were identifi ed and highlighted to improve the productivity in these industries.}, number={3}, journal={Tekstilec}, author={Mozumder, S. and Chakraborty, S. and Hoque, M.S.}, year={2019}, pages={158–165} }
 @article{chakraborty_biswas_2019, title={Fused Deposition Modeling 3D Printing Technology in Textile and Fashion Industry: Materials and Innovation}, volume={2}, url={https://www.researchgate.net/publication/337720802_Fused_Deposition_Modeling_3D_Printing_Technology_in_Textile_and_Fashion_Industry_Materials_and_Innovation}, number={1}, journal={Modern Concepts in Material Science}, author={Chakraborty, S. and Biswas, M.C.}, year={2019}, pages={000529} }
 @article{kabir_chakraborty_hoque_mathur_2019, title={Sustainability Assessment of Cotton-Based Textile Wet Processing}, volume={1}, ISSN={2571-8797}, url={http://dx.doi.org/10.3390/cleantechnol1010016}, DOI={10.3390/cleantechnol1010016}, abstractNote={The textile and fashion industries account for a significant part of global business. Textile wet processing (TWP) is a crucial stage in textile manufacturing. It imparts aesthetics as well as functional appeal on the textile fabric and ultimate products. Nevertheless, it is considered as one of the most polluting industries and threatens sustainability. There have been different approaches to transform this polluting industry to a sustainable industry. Many researchers have found this challenging, as sustainable, eco-friendly, green or cleaner wet processing might not be always applicable and relevant from the perspective of industrial applications. The present work helps us understand the current state of research of cotton-based textile processes including proposed sustainable approaches. It also examines the achievement of the degree of sustainability of those proposed processes with the lens of the triple bottom line (TBL) framework, identifies existing limitations, and suggests future research scopes that might pave ways for young researchers to learn and undertake new experimental and theoretical research.}, number={1}, journal={Clean Technologies}, publisher={MDPI AG}, author={Kabir, S M Fijul and Chakraborty, Samit and Hoque, S M Azizul and Mathur, Kavita}, year={2019}, month={Sep}, pages={232–246} }
 @article{knit fabric scouring with soapnut: a sustainable approach towards textile pre-treatment_2018, url={http://dx.doi.org/10.11648/j.ajep.20180701.14}, DOI={10.11648/j.ajep.20180701.14}, abstractNote={Detergent contains amphiphilic molecules which diminish the surface tension of water and are widely used for industrial purpose especially during the pretreatment of fabric. When the wastewater containing industrial detergent is discharged into different water sources, it may cause detrimental effect to the aquatic environment. This research paper focuses on the comparative study of natural detergent (soapnut/reetha) and synthetic detergent in case of 100% cotton single jersey knit fabric. Experiments were done using the different concentration of soapnut and at 10% soapnut concentration, weight loss percentage and absorbency of natural detergent scoured fabric were found almost similar to that of fabric scoured with the synthetic detergent. Moreover, bursting strength of fabric scoured with soapnut was found higher than that of synthetic detergent scoured fabric. The result derived from the experiment suggest that soapnut has remarkable detergency properties and can be used as an environment-friendly alternative to synthetic detergent.}, journal={American Journal of Environmental Protection}, year={2018} }
 @article{chakraborty_2016, title={A Detailed Study on Environmental Sustainability in Knit Composite Industries of Bangladesh}, volume={5}, url={http://dx.doi.org/10.11648/j.ajep.20160505.13}, DOI={10.11648/j.ajep.20160505.13}, abstractNote={This research paper has illustrated different forms of contemporary sustainable measures that can be applied in knitwear manufacturing industries. Apart of discussing this aspect, the paper has also reported what types of sustainable measures are being adopted by the Bangladeshi garments industries while producing knitted garments. Different ways of introducing and maintaining sustainability in garments industry have been elaborately presented in this paper. The research has also described what kinds of difficulties usually impair industrialists in adopting or executing sustainable practices in producing knitted apparels. In order to collect the information the author visited five garments industries and conducted interview with key responsible persons of those industries. A questionnaire was prepared for interviewing them. Their answers have been discussed elaborately in this paper followed by a concise conclusion.}, number={5}, journal={American Journal of Environmental Protection}, author={Chakraborty, Samit}, year={2016} }
 @article{chakraborty_sheppard_2016, title={An explanatory study on indian young consumers’ luxury consumption: The underlying relationship of interpersonal influence, brand image, brand consciousness and demographic components with luxury brand purchase decision}, volume={6}, url={https://www.researchgate.net/profile/Samit_Chakraborty2/publication/319645693_An_Explanatory_study_on_Indian_Young_Consumers'_Luxury_Consumption_The_Underlying_Relationship_of_Interpersonal_Influence_Brand_Image_Brand_Consciousness_and_Demographic_Components_with_Luxury_Brand_P/links/59b7d134458515c212b50f54/An-Explanatory-study-on-Indian-Young-Consumers-Luxury-Consumption-The-Underlying-Relationship-of-Interpersonal-Influence-Brand-Image-Brand-Consciousness-and-Demographic-Components-with-Luxury-Brand.pdf}, number={2}, journal={International Journal of Current Engineering and Technology}, author={Chakraborty, S. and Sheppard, L.}, year={2016}, pages={622–634} }