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:传统的大批量生产模式无法满足个性化客户需求的灵活性。新一代的智能工厂可支持新的多样性和小批量自定义生产模式。为此,人工智能(AI)加速了制造和信息通信技术(包括计算机、通信和控制)的融合,以实现更高附加值的制造业。定制智能工厂的特点是自我感知、操作优化、动态重构和智能决策。AI技术将允许制造系统感知环境,适应外部需求,并提取处理的知识,包括智能生产、网络协作和延伸服务模型等业务模型。本文着重介绍在定制化制造(CM)领域中实现AI的情况。展示了智能工厂的AI驱动的体系结构,智能制造设备的细节、智能信息交互以及柔性制造线的构建。回顾了CM潜在应用的最新AI技术,包括机器学习、多智能体系统、物联网、大数据和云边计算。使用定制包装的案例研究验证了AI可实现的技术在定制智能工厂中的应用。实验结果表明,AI辅助的CM提供了更高的生产灵活性和生产效率。本文还讨论了AI在CM中的挑战与解决方案。