Application and prospect of information technology in personalized clothing customization
With the development of economy and the improvement of information technology,more and more consumers begin to pursue high-quality clothing,seeking to improve their wearing experience and meet the needs of individuality and fashion through customizing their clothes.As a result,personalized customization of clothing has become one of the fashion trends.China Textile Industry Development Plan(2016-2020)proposes to position the development of a mass customization as the key development direction,rely on the e-commerce platform,and use information technology,intelligent design,flexible manufacturing and intelligent logistics and other technologies to achieve the speed and cost of mass production to explore a mass customization production mode featuring small batches and multiple varieties.Additionally,the plan emphasizes the need to accelerate the construction of industrial automation and digitization.However,the application of information technology in traditional clothing production is currently fragmented,with a lack of integration of information technology applications according to the personalized customization mode of clothing.This paper aimed to integrate interdisciplinary research results in order to promote the precise integration of information technology and the personalized clothing customization mode.First,it summarized the research progress of information technology in the clothing industry and expounded on the application of new generation information technology in the clothing industry.Then,it analyzed the current application status of information technology in the field of personalized clothing customization,with focus on the development status of personalized clothing customization and the application of information technology in each link.The research was divided into the modules of user demand acquisition and management,intelligent energy body,personalized clothing design and recommendation,intelligent procurement,and intelligent production.The advantages and disadvantages of information technology in improving production efficiency,reducing costs and meeting user needs were summarized.The first issue identified is the lack of information about consumers'educational background,working environment and income level in the process of user demand mining.Additionally,there is a lack of data sets for users'personalized customization needs.In the human body measurement link,the accuracy and personalization of remote body measurement do not meet the fit requirements for clothing customization.The recommendation algorithm used in the clothing recommendation system faces problems such as cold start and data sparsity and fails to adjust to complex and changeable popular trends in a timely manner.Furthermore,due to the lack of accurate acquisition of user needs,the recommendation results are inaccurate.In the intelligent procurement module,the existing supply chain system is still dominated by fixed suppliers,hindering the realization of personalized supply coordination.The intelligent production module lacks research and application of collaborative production for customized products,resulting in the inability to adjust according to changing user needs.Based on these findings,the study comprehensively examined the personalized customization process from a global perspective,emphasizing the importance of collaboration in all aspects.It reveals that while different degrees of digital upgrading have been achieved in each link of clothing personalized customization,overall information sharing and synergy between modules are low.To address these issues,the paper proposes improving the modeling technology of each link of personalized clothing customization using an industry 4.0 architecture.This approach aims to reconstruct the personalized customization process,realize data sharing and optimal control between modules,and enhance productivity,speed,accuracy,flexibility and competitiveness.
garment industryinformation technologypersonalized customizationcustomer requirementspersonalized design and recommendationintelligent production
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