设计师 Aiit Peking University 的作品 Xfun 包装设计平台荣获了极具声望的 2026 A' Design Award 银奖，竞赛类别为数字产品设计。

银数字产品· 2026

Xfun 包装设计平台

设计师： Aiit Peking University

客户: Advanced Institute of Information Technology, Peking University

数字产品类别A' Design Award 银奖获奖者

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色彩

设计作品

关于 Xfun 包装设计平台

Xfun 是一款由人工智能驱动的包装设计平台。该平台将概念生成、在线编辑与可直接付印的输出整合于同一工作流程之中,使品牌方、设计师与印刷厂能够从最初的设计简报协同工作至最终生产环节。平台内置的知识库涵盖纸板盒、软包装与标签等品类,同时通过 CMYK 色彩管理与材质纹理模拟,确保成品效果始终符合实际生产标准。模块化界面将生成、参数设置与材料库有机整合,有效缩短设计周期并降低成本。

荣誉认可

关于A' Design Award 银奖

Xfun 包装设计平台是 A' Design Award 银奖得主，这是授予顶级、华美而令人印象深刻的设计的极为崇高的认可。银奖得主是极其卓越、极具创造力的作品，展现出其设计师杰出的专业技能、才华与敏锐。预计Xfun 包装设计平台将成为一件出色的典范之作，兼具非凡的专业性与深刻的创新性。这件赢得 A' Design Award 银奖的设计是一项备受瞩目、令人钦佩的发明，造福并拓展艺术、科学、设计和技术的边界。Xfun 包装设计平台是一件令人羡慕的创作，它唤起渴望，带来积极的情感，并激发惊叹与赞叹。

设计幕后

媒体资料包

由设计师提供的致谢、团队成员及技术详情。

独特属性: Xfun, an AI powered platform for the packaging design industry, addresses the lengthy cycles, high costs, and cumbersome revision processes common in traditional workflows. By integrating creative conception, online editing, and print ready output, it enables efficient collaboration among small and medium sized brands, designers, and packaging printers. Through a structured layout and professional tools, the platform ensures a smooth, controllable journey from initial brief to final production.
标签: Intelligent Packaging Design Platform, AI Powered Packaging Concept Generation, Online Editing, Print Ready Output, Modular Interface, Efficient Delivery, Diverse Material Options, Human Computer Collaboration
生产技术: Xfun deeply integrates knowledge bases of materials and production processes specific to the packaging industry, covering structural specifications and print compatibility requirements for mainstream formats including paperboard boxes, flexible packaging, and labels. It also supports CMYK color management and material texture simulation, ensuring that AI generated designs adhere rigorously to real world production standards.
设计挑战: The challenge was merging packaging industry knowledge with AI. To address this, the team has built knowledge bases and developed AI models, ensuring results are creatively compelling and compliant with printing and manufacturing standards. Moreover, Xfun actively bridges the data pipeline between design and production, creating a closed loop system from creative conception to print delivery. This resolves core issues around output controllability, cost efficiency, and real world implementation.
研究: With the rise of new consumer brands and agricultural product electronic commerce, the demand for fast, low cost, and high quality packaging design has surged. Yet traditional workflows rely on repetitive manual communication and prototyping, failing to meet the need for rapid market entry. Xfun leverages intelligent methods to optimize the design workflow, which bridges the gap between creative conception and production, helping small and medium sized brands improve their competitiveness.
灵感: Xfun upholds a design philosophy that equally prioritizes professional tools and exceptional user interaction. The interface embraces minimalism, where purple as the main color, accented with black and gray for key buttons and interactive elements, provides intuitive visual guidance to assist users in focused, efficient operation. Moreover, micro interactions, gradient light and shadow, and linear icons convey technological sophistication and reliability without compromising on practicality.
项目周期: The project started in March 2024.
操作流程: A modular interface clearly displays functional zones such as AI generation, parameter setting and material library. An optimized information hierarchy highlights primary buttons, naturally guiding users through the core workflow of requirement input, parameter adjustment, and result generation. Linear icons like custom cursors and loading animations present a clean, modern aesthetic, spicing up the clear, organized interface. Smooth interaction embodies professionalism and practicality.
团队成员: Advanced Institute Of Information Technology Peking University
Lei Shao, Wei Zhang, Sen Peng, Yi Zhang, Xiaoqing Zhang, Yi Li, Handong Zhang, Shuai Pan, Jiahong Tu, Yuhan Wu, Jiajie Yuan