Artificial-Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges

Jiafu Wan; Xiaomin Li; Hong-Ning Dai; Andrew Kusiak; Miguel Martinez-Garcia; Di Li

doi:10.1109/JPROC.2020.3034808

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Journal article

Artificial-Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges

Jiafu Wan, Xiaomin Li, Hong-Ning Dai, Andrew Kusiak, Miguel Martinez-Garcia and Di Li

Proceedings of the IEEE, Vol.109(4), pp.377-398

04/2021

DOI: 10.1109/JPROC.2020.3034808

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https://arxiv.org/pdf/2108.03383View

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Abstract

The traditional production paradigm of large batch production does not offer flexibility toward satisfying the requirements of individual customers. A new generation of smart factories is expected to support new multivariety and small-batch customized production modes. For this, 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: self-perception, operations optimization, dynamic reconfiguration, and intelligent decision-making. The AI technologies will allow manufacturing systems to perceive the environment, adapt to the external needs, and extract the process knowledge, including business models, such as intelligent production, networked collaboration, and extended service models. This article 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 construction of a flexible manufacturing line are showcased. The state-of-the-art AI technologies of potential use in CM, that is, machine learning, multiagent 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.

Adaptation models

Artificial intelligence

Artificial intelligence (AI)

Collaboration

Computational modeling

customized manufacturing (CM)

Decision making

Heuristic algorithms

Industry 4.0

Machine learning

Manufacturing

Multi-agent systems

Production facilities

smart factory

Smart manufacturing

Software defined networking

software-defined network

Details

Title: Subtitle: Artificial-Intelligence-Driven Customized Manufacturing Factory: Key Technologies, Applications, and Challenges
Creators: Jiafu Wan - South China University of Technology
Xiaomin Li - South China University of Technology
Hong-Ning Dai - University of Science and Technology
Andrew Kusiak - University of Iowa
Miguel Martinez-Garcia - Loughborough University
Di Li - Loughborough University
Resource Type: Journal article
Publication Details: Proceedings of the IEEE, Vol.109(4), pp.377-398
DOI: 10.1109/JPROC.2020.3034808
ISSN: 0018-9219
eISSN: 1558-2256
Publisher: IEEE
Grant note: 0025/2019/AKP / Macao Science and Technology Development Fund through the Macao Funding Scheme for Key Research and Development Projects 2018YFB1700500 / National Key Research and Development Program of China (10.13039/501100012166) U1801264 / Joint Fund of the National Natural Science Foundation of China and Guangdong Province (10.13039/501100001809)
Language: English
Date published: 04/2021
Academic Unit: Industrial and Systems Engineering; Nursing
Record Identifier: 9984186978702771

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