| 1. |
- Agrawal, Tarun Kumar, et al.
(författare)
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Blockchain-based Framework for Supply Chain Traceability : A Case Example of Textile and Clothing Industry
- 2021
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Ingår i: Computers & industrial engineering. - : Elsevier BV. - 0360-8352 .- 1879-0550.
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Tidskriftsartikel (refereegranskat)abstract
- Traceability has emerged as a prime requirement for a multi-tier and multi-site production. It enables visibility and caters to the consumer requirements of transparency and quality assurance. Textile and clothing industry is one such example that requires traceability implementation to address prevailing problems of information asymmetry and low visibility. Customers find it difficult to access product data that can facilitate ethical buying practices or assure product authenticity. Besides, it is challenging for stakeholders to share crucial information in an insecure environment with risk of data manipulations and fear of losing information advantage. In this context, this study investigates and proposes a blockchain-based traceability framework for traceability in multi-tier textile and clothing supply chain. It conceptualizes the interaction of supply chain partners, and related network architecture at the organizational level and smart contract and transaction validation rules at the operational level. To illustrate the application of the proposed framework, the study presents an example of organic cotton supply chain using blockchain with customized smart contract and transaction rules. It finally demonstrates the applicability of the developed blockchain by testing it under two parameters. The proposed system can build a technology-based trust among the supply chain partners, where the distributed ledger can be used to store and authenticate supply chain transactions. Further, the blockchain-based traceability system would provide a unique opportunity, flexibility, and authority to all partners to trace-back their supply network and create transparent and sustainable supply chain.
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| 2. |
- Eutionnat-Diffo, Prisca, 1992-, et al.
(författare)
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Correlation between heat transfer of polyester textiles and its adhesion with 3D-printed extruded thermoplastic filaments
- 2018
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Ingår i: 18th AUTEX World Textile Conference, June 20-22, 2018, Istanbul, Turkey. ; , s. 118-121
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Konferensbidrag (refereegranskat)abstract
- FDM technology used for printing functionalized layers on textiles brought new challenges such as the understanding and the improvement of the adhesion performance of the thermoplastic filaments on synthetic textile materials. In addition to the impact of printing parameters, the correlation between the heat transfer and structure of the textile material and the adhesion performance after varying printer platform temperature was an important parameter considered in this paper. A factorial design, using material density, direction, and structure and platform temperature as factors, was followed. 3D-printed materials made of PLA filaments deposited on polyester woven and knit materials were manufactured on a dual-head printer and their adhesion was measured according to DIN EN ISO 13937-2 and ISO 11339 and the heat transfer of the fabrics according to ASTM D4966-98, ISO 6330 and ISO 22007-2. The findings showed that the heat transfer and structure of textile materials affect the adhesion properties of the 3D-printed material.
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| 3. |
- Eutionnat-Diffo, Prisca, 1992-, et al.
(författare)
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Optimization of adhesion of poly lactic acid 3D printed onto polyethylene terephthalate wovenfabrics through modelling using textile properties
- 2019
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Ingår i: Rapid prototyping journal. - 1355-2546 .- 1758-7670.
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Tidskriftsartikel (refereegranskat)abstract
- PurposeThis paper aims to evaluate and simulate the impact of the build platform temperature of the three-dimensional (3D) printer, the structure and heat transfer of textiles on the adhesion and durability after washing properties of 3D printed polymer onto textile materials using thin layers of conductive and non-conductive extruded poly lactic acid monofilaments (PLA) deposited on polyethylene terephthalate (PET) woven fabrics through fused deposition modeling (FDM) process.Design/methodology/approachPrior to FDM process, thermal conductivity, surface roughness and mean pore size of PET woven fabrics were assessed using the “hot disk,” the profilometer and the capillary flow porometry methods, respectively. After the FDM process, the adhesion and durability after the washing process properties of the materials were determined and optimized based on reliable statistical models connecting those properties to the textile substrate properties such as surface roughness, mean pore size and thermal conductivity.FindingsThe main findings point out that higher roughness coefficient and mean pore size and lower thermal conductivity of polyester woven textile materials improve the adhesion properties and the build platform presents a quadratic effect. Additionally, the adhesion strength decreases by half after the washing process and rougher and more porous textile structures demonstrate better durability. These results are explained by the surface topography of textile materials that define the anchorage areas between the printed layer and the textiles.Originality/valueThis study is for great importance in the development of smart textiles using FDM process as it presents unique and reliable models used to optimize adhesion resistance of 3D printed PLA primary layer onto PET textiles.
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| 4. |
- Eutionnat-Diffo, Prisca, 1992-, et al.
(författare)
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Stress, strain and deformation of poly-lactic acid filament deposited onto polyethylene terephthalate woven fabric through 3D printing process
- 2019
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Ingår i: Scientific Reports. - : Springer Science and Business Media LLC. - 2045-2322. ; 9
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Tidskriftsartikel (refereegranskat)abstract
- Although direct deposition of polymeric materials onto textiles through 3D printing is a great technique used more and more to develop smart textiles, one of the main challenges is to demonstrate equal or better mechanical resistance, durability and comfort than those of the textile substrates before deposition process. This article focuses on studying the impact of the textile properties and printing platform temperature on the tensile and deformations of non-conductive and conductive poly lactic acid (PLA) filaments deposited onto polyethylene terephthalate (PET) textiles through 3D printing process and optimizing them using theoretical and statistical models. The results demonstrate that the deposition process affects the tensile properties of the printed textile in comparison with the ones of the textiles. The stress and strain at rupture of the first 3D printed PLA layer deposited onto PET textile material reveal to be a combination of those of the printed layer and the PET fabric due to the lower flexibility and diffusion of the polymeric printed track through the textile fabric leading to a weak adhesion at the polymer/textile interface. Besides, printing platform temperature and textile properties influence the tensile and deformation properties of the 3D printed PLA on PET textile significantly. Both, the washing process and the incorporation of conductive fillers into the PLA do not affect the tensile properties of the extruded polymeric materials. The elastic, total and permanent deformations of the 3D-printed PLA on PET fabrics are lower than the ones of the fabric before polymer deposition which demonstrates a better dimensional stability, higher stiffness and lower flexibility of these materials.
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| 5. |
- Eutionnat-Diffo, Prisca, 1992-, et al.
(författare)
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Study of the electrical resistance of conductive PLA deposited onto fabrics through 3D printing
- 2019
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Konferensbidrag (refereegranskat)abstract
- In this study, conductive tracks are integrated onto textiles through Fused Deposition Modelling (FDM) process and the correlation between the FDM process parameters, the textile properties (the porosity and the structure for instance) and the electrical resistance of the composites is investigated. Many researchers have studied the electrical conductivity of polymers composites using incorporation of conductive fillers such as carbon black or carbon nanotube–polymer composites and the effect of the 3D printing process parameters, such as extruder temperature, on the electrical properties [1–7]. However, in this paper, in addition to study and understand the electrical properties of these conductive materials deposited onto textiles, they are maximized to guarantee the use of the textile composites in smart textiles field.Findings are very promising and important in the development of functionalized textiles as they demonstrate the feasibility of enhancing the electrical conductivity of textile composite materials through theoretical models based on the experimental data.
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| 6. |
- Eutionnat-Diffo, Prisca, 1992-, et al.
(författare)
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Study of the Wear Resistance of Conductive Poly Lactic Acid Monofilament 3D Printed onto Polyethylene Terephthalate Woven Materials
- 2020
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Ingår i: Materials. - : MDPI AG. - 1996-1944. ; 10:13
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Tidskriftsartikel (refereegranskat)abstract
- Wear resistance of conductive Poly Lactic Acid monofilament 3D printed onto textiles, through Fused Deposition Modeling (FDM) process and their electrical conductivity after abrasion are important to consider in the development of smart textiles with preserved mechanical and electrical properties. The study aims at investigating the weight loss after abrasion and end point of such materials, understanding the influence of the textile properties and 3D printing process parameters and studying the impact of the abrasion process on the electrical conductivity property of the 3D printed conductive polymers onto textiles. The effects of the 3D printing process and the printing parameters on the structural properties of textiles, such as the thickness of the conductive Poly Lactic Acid (PLA) 3D printed onto polyethylene terephthalate (PET) textile and the average pore sizes of its surface are also investigated. Findings demonstrate that the textile properties, such as the pattern and the process settings, for instance, the printing bed temperature, impact significantly the abrasion resistance of 3D printed conductive Poly Lactic Acid (PLA) onto PET woven textiles. Due to the higher capacity of the surface structure and stronger fiber-to-fiber cohesion, the 3D printed conductive polymer deposited onto textiles through Fused Deposition Modeling process have a higher abrasion resistance and lower weight loss after abrasion compared to the original fabrics. After printing the mean pore size, localized at the surface of the 3D-printed PLA onto PET textiles, is five to eight times smaller than the one of the pores localized at the surface of the PET fabrics prior to 3D printing. Finally, the abrasion process did considerably impact the electrical conductivity of 3D printed conductive PLA onto PET fabric.
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| 7. |
- Giri, Chandadevi, et al.
(författare)
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Deep Learning for Demand Forecasting in the Fashion and Apparel Retail Industry
- 2022
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Ingår i: Forecasting. - : MDPI. - 2571-9394. ; 4:2, s. 565-581
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Tidskriftsartikel (refereegranskat)abstract
- Compared to other industries, fashion apparel retail faces many challenges in predicting future demand for its products with a high degree of precision. Fashion products’ short life cycle, insufficient historical information, highly uncertain market demand, and periodic seasonal trends necessitate the use of models that can contribute to the efficient forecasting of products’ sales and demand. Many researchers have tried to address this problem using conventional forecasting models that predict future demands using historical sales information. While these models predict product demand with fair to moderate accuracy based on previously sold stock, they cannot fully be used for predicting future demands due to the transient behaviour of the fashion industry. This paper proposes an intelligent forecasting system that combines image feature attributes of clothes along with its sales data to predict future demands. The data used for this empirical study is from a European fashion retailer, and it mainly contains sales information on apparel items and their images. The proposed forecast model is built using machine learning and deep learning techniques, which extract essential features of the product images. The model predicts weekly sales of new fashion apparel by finding its best match in the clusters of products that we created using machine learning clustering based on products’ sales profiles and image similarity. The results demonstrated that the performance of our proposed forecast model on the tested or test items is promising, and this model could be effectively used to solve forecasting problems.
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| 8. |
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| 9. |
- Kulinska, Maria, et al.
(författare)
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How virtual fitting leads to sustainable fashion
- 2016
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Ingår i: Proceedings. - 9789892070537
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Konferensbidrag (refereegranskat)abstract
- Especially in the fast fashion segment of the global clothing industry, ill-fitting garments degenerate into waste as they return to store, are left unsold or unused, or otherwise outdate. To address these problems of ill-fit, we accessed from databanks the 3D morphological measurements of 478 French female consumers. We extracted virtual mannequins representative of three dominant bodylines types. Clinical evidence suggests that, among body lines for good fit between a particular consumer and a particular grade of garment, the neck and armholes are pivotal. Cross-tabulating across the above matrix of design requirements, our simulation reveals how virtual fitting for draping and ease allowance on a particular virtual mannequin improves fit and thus reduces garment waste. Given that 3D parametrization holds promise to improve sustainability in fast fashion, we call for clinical trials, as well as for replication or trials in other segments of the fashion industry, other products than garments, and/or other industries.
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| 10. |
- Kumar, Vijay, 1989-, et al.
(författare)
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Contribution of traceability towards attaining sustainability in the textile sector
- 2017
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Ingår i: Textiles and Clothing Sustainability. - : Springer Science and Business Media LLC. - 2197-9936. ; 3:5
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Tidskriftsartikel (refereegranskat)abstract
- Sustainability is a widely recognized concern and priority for healthy growth of the society and for preservation of the planet. Concerning this, textile sector has seen an unprecedented demand for sustainable products from the consumers, responding to which organizations have undertaken different initiatives. One of the major concerns in the textile sector is its complex supply chain networks and the involvement of numerous actors dealing with diverse raw materials and operations. The effective implementation of sustainability at the industrial scale would require the participation of all supply chain actors, along with an efficient traceability system to monitor and analyze different sustainability aspects. Furthermore, traceability is an integral part of the recycling process which contributes towards the sustainability. Therefore, the present article focuses on the contribution of traceable information towards attaining the sustainability in the textile sector. The three pillars of sustainability, namely, ecological, societal, and economic, are discussed for their relation and dependency on the traceability followed by an overview of the challenges in successful implementation of the traceability system, which is anticipated to shape the future research questions.
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