Artificial Intelligence-Driven Customized Manufacturing Factory: Key
Technologies, Applications, and Challenges
- URL: http://arxiv.org/abs/2108.03383v2
- Date: Fri, 14 Apr 2023 01:26:16 GMT
- Title: Artificial Intelligence-Driven Customized Manufacturing Factory: Key
Technologies, Applications, and Challenges
- Authors: Jiafu Wan, Xiaomin Li, Hong-Ning Dai, Andrew Kusiak, Miguel
Mart\'inez-Garc\'ia, Di Li
- Abstract summary: This paper focuses on the implementation of AI in customized manufacturing (CM)
Details of intelligent manufacturing devices, intelligent information interaction, and the construction of a flexible manufacturing line are showcased.
The AI-enabled technologies in a customized smart factory are validated with a case study of customized packaging.
- Score: 6.730602129752864
- License: http://creativecommons.org/licenses/by-nc-sa/4.0/
- Abstract: 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.
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