In this study, we took common Bombyx Mori as the research object, and provided different cocooning sites for single or multiple silkworms to construct common stereoscopic cocoons (“normal cocoons” ) and flat cocoons (“single-silkworm flat cocoons” and “multi-silkworm flat cocoons” ), respectively, and compared the morphological structure and basic properties of these cocoons. However, its structure and functions are often destroyed in practical application. The trained neural network was then applied to a clothing company as a guide to the success of its continuous improvement project.Ĭocoon is a kind of natural biopolymer material with reasonable structure and various functions. The developed model can then define the adequate chronology and predict success level with an accuracy of 97%. For the performance indices such as Categorical Cross Entropy (CCE), the defined loss function, accuracy, and precision have been evaluated and optimized. To evaluate the trained network, 25% of the data have been used and a tuning hyperparameter process has been designed to reinforce the model performance. Then, the dataset have been used for training, testing, and validating the neural network model. The neural network was trained for the prediction of success level rate and customizing of Lean and Six Sigma implementation chronology with the help of weights and maturity of a set of common critical success factors (CSFs). This article, based on an intelligent model, draws up a support tool to the clothing stakeholders, or otherwise aims to successfully integrate Lean and Six Sigma using Deep Learning. The result is that only 11 companies out of 1,200 Moroccan clothing companies have successfully implemented Lean and Six Sigma. In fact, despite all the advances in these methodologies and practical approaches, defining a rational implementation strategy such as the adequate chronology and the prediction of the expected success level are still a part of a fierce debate and an impediment for practitioners. However, the adoption of these approaches is very much restricted in the Textile and Clothing sector in Morocco. Implementation of Lean and Six Sigma methodologies enable companies to boost their competitiveness and their efficiency. Web of Science - Science Citation Index Expanded.Web of Science - Essential Science Indicators.Ulrich's Periodicals Directory/ulrichsweb.KESLI-NDSL (Korean National Discovery for Science Leaders).Journal Citation Reports/Science Edition.Japan Science and Technology Agency (JST).CNKI Scholar (China National Knowledge Infrastructure).Chemical Abstracts Service (CAS) - SciFinder.Chemical Abstracts Service (CAS) - CAplus.Authorized journal of AUTEX – The Association of Universities for TextilesĪUTEX Research Journal is covered by the following services:.Discounted APCs for AUTEX Association members.Open Access publication, ensuring widest possible dissemination of your research.One of the few journals dealing with textiles research at a global level.We welcome submission of original research articles and invited review articles. Ecological and Environmental Textiles, Recycling and Life Cycle Analysis.Nanotechnology, Nanotextiles, Electrospinning.Smart, Interactive and Multifunctional Textiles.Medical Textiles, Tissue Engineering, Implants.Technical Textiles, Composites and Membranes.In fact, the possibility of tuning their properties from nano to macro scale to obtain multifunctional and smart textiles is opening new opportunities to develop advanced solutions, traditional and non-traditional applications.ĪUTEX Research Journal accepts high level scientific contributions on the following topics: Due to their unique properties and behaviour, fiber-based materials, in general, have substantially enlarged their range of applications in areas like health care and well-being, aeronautics and aerospace, defence, architecture, building and sports. AUT disseminates high-quality scientific knowledge related to textile-based materials and products, including topics like fibers, fibrous structures, functionalization, design, and manufacturing. The AUTEX Research Journal ( AUT) is a leading open access, peer reviewed scientific journal dedicated to textile science and technology. AUTEX Research Journal is published by De Gruyter on behalf of the Association of Universities for Textiles (AUTEX)
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