2021
DOI: 10.1109/jproc.2020.3034808
|View full text |Cite
|
Sign up to set email alerts
|

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

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 characteristi… Show more

Help me understand this report
View preprint versions

Search citation statements

Order By: Relevance

Paper Sections

Select...
1
1
1
1

Citation Types

0
51
0
2

Year Published

2021
2021
2024
2024

Publication Types

Select...
6
2
1

Relationship

1
8

Authors

Journals

citations
Cited by 171 publications
(53 citation statements)
references
References 163 publications
(161 reference statements)
0
51
0
2
Order By: Relevance
“…Similarly, it is significant for manufacturing workers to adopt standards and protocols in open communication. In [ 78 ], the main focus was customer satisfaction in the manufacturing system’s production model. The integration of AI and information communication enabled the manufacturing standard to be high and customized the factory based on optimizing the operations, intelligent decision making, self-perception, etc.…”
Section: Related Workmentioning
confidence: 99%
“…Similarly, it is significant for manufacturing workers to adopt standards and protocols in open communication. In [ 78 ], the main focus was customer satisfaction in the manufacturing system’s production model. The integration of AI and information communication enabled the manufacturing standard to be high and customized the factory based on optimizing the operations, intelligent decision making, self-perception, etc.…”
Section: Related Workmentioning
confidence: 99%
“…With the advantages of being close to the equipment, good realtime performance, and strong computing capability, edge computing as a new computing paradigm has been highly used by academics, enterprises and in the agricultural field [14][15][16][17]. Caria et al [18] constructed an intelligent pasture monitoring system for monitoring livestock and pasture environment based on edge computing, where an edge computing unit was designed using the raspberry PI as a computing module.…”
Section: Application Of Edge Computing In Agriculturementioning
confidence: 99%
“…Another team of robots in is transportation robots, which is also known as autonomous guided vehicles (AGVs), that also form an important part of the MRS [4]. In Industry 4.0, the smart manufacturing tends to provide smaller batch production according to the demand of different users [40][41][42]. A wider range of technology namely artificial intelligence (AI) robotics, Industrial Internet of Things (IIoT), intelligent sensors, augmented reality (AR), cloud computing, edge computing, big data, and digital fabrication, which will facilitate smart factory that aim at the rapid production of variety of small batches products.…”
Section: Smart Factory As Wireless Networked Multi-robot Systemsmentioning
confidence: 99%
“…The traditional control systems are not capable of high-level adaptability. The robots on the production line is set up in a fixed way for a certain product for mass production and lack intelligent design to fulfill the requirement of dynamic reconfiguration [41,42]. For smart manufacturing, it is necessary to reduce configure time and cost for robots that are engaged in more frequent changes than the traditional fixed production line [40].…”
Section: Reconfigurable Production Linesmentioning
confidence: 99%