Progress in the application of artificial intelligence technology in the garment industry from the perspective of product life cycle
The traditional garment industry is confronted with numerous challenges,including escalating labor costs,inadequate design innovation,and suboptimal supply chain management.These issues primarily arise from the labor-intensive characteristics of the garment sector and its significant reliance on human resources.As globalization continues to influence market dynamics,companies are increasingly pressured to maintain competitive pricing while ensuring high-quality products that meet consumer demands for sustainability and ethical production practices.Artificial intelligence(AI),a technology that emulates human cognitive functions and can substantially replace manual operations,has been extensively adopted in the apparel industry—particularly in enhancing efficiency across clothing design,production processes,sales strategies,and managing manufacturing costs.AI applications range from predictive analytics that forecast fashion trends based on consumer behavior data to automated cutting machines that optimize fabric usage during production.Furthermore,machine learning algorithms can analyze vast datasets to identify patterns in customer preferences or inventory levels,enabling businesses to make informed decisions regarding stock management.Nevertheless,a comprehensive examination of AI's application within the clothing domain remains lacking.While some studies have explored specific use cases of AI technologies such as computer vision for quality control or chatbots for customer service enhancement,there is still a gap in understanding how these innovations interconnect throughout various stages of product development.Apparel product lifecycle management(PLM)serves as an integrated management solution that encompasses design,manufacturing processes,distribution channels,and sales strategies to assist companies in tracking and overseeing their apparel product lifecycle effectively.By integrating PLM systems with AI capabilities like real-time data analysis and automation tools,organizations can streamline workflows significantly—from initial concept development through final retail delivery.Consequently,this paper aims to thoroughly investigate the specific applications of artificial intelligence at each stage of apparel product lifecycles through two lenses:application scenarios and algorithms;it will analyze both the current state and limitations of existing research with the intention of providing insights for scholars in related fields while fostering transformation and advancement within the garment industry to enhance its competitiveness.This exploration will not only highlight successful case studies but also address potential barriers such as technological adoption rates among small enterprises or concerns regarding data privacy when utilizing consumer information for algorithm training purposes.
万方数据
维普
