The traditional production paradigm of large batch production does not offer flexibility towards satisfying the requirements of individual customers. A new generation of smart factories is expected to support new multi-variety and small-batch customized production modes. For that, Artificial Intelligence (AI) is enabling higher value-added manufacturing by accelerating the integration of manufacturing and information communication technologies, including computing, communication, and control. The characteristics of a customized smart factory are to include self-perception, operations optimization, dynamic reconfiguration, and intelligent decision-making. The AI technologies will allow manufacturing systems to perceive the environment, adapt to external needs, and extract the processed knowledge, including business models, such as intelligent production, networked collaboration, and extended service models. This paper focuses on the implementation of AI in customized manufacturing (CM). The architecture of an AI-driven customized smart factory is presented. Details of intelligent manufacturing devices, intelligent information interaction, and the construction of a flexible manufacturing line are showcased. The state-of-the-art AI technologies of potential use in CM, i.e., machine learning, multi-agent systems, Internet of Things, big data, and cloud-edge computing are surveyed. The AI-enabled technologies in a customized smart factory are validated with a case study of customized packaging. The experimental results have demonstrated that the AI-assisted CM offers the possibility of higher production flexibility and efficiency. Challenges and solutions related to AI in CM are also discussed.

翻译：传统的大批量生产范式无法灵活满足个性化客户需求。新一代智能工厂有望支持多品种、小批量的定制化生产模式。为此，人工智能技术通过加速制造与信息通信技术（包括计算、通信与控制）的融合，正在推动更高附加值的制造业发展。定制化智能工厂的特征包括自我感知、运营优化、动态重构及智能决策。人工智能技术将使制造系统具备环境感知、外部需求适应及加工知识提取能力，并涵盖智能生产、网络化协作及服务延伸等商业模式。本文聚焦人工智能在定制化制造中的实施，提出了人工智能驱动的定制化智能工厂架构，展示了智能制造设备、智能信息交互及柔性生产线构建的细节。综述了潜在应用于定制化制造的前沿人工智能技术，包括机器学习、多智能体系统、物联网、大数据及云边计算。通过定制包装案例验证了定制化智能工厂中的人工智能赋能技术，实验结果表明，人工智能辅助的定制化制造为实现更高的生产柔性和效率提供了可能。最后探讨了人工智能在定制化制造中的挑战与解决方案。