Understanding Data Correlations in Continuous Casting Systems for Autonomous Fixed Weight Cutting

Ping, Haodi; Wang, Yongcai; Feng, Hua; Qiao, Lifeng; Chen, Wenping; Li, Deying

doi:10.1145/3373419.3373427

Cited by 1 publication

(2 citation statements)

References 13 publications

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“…We have summarized 41 articles that do not specify specific industries in the discussion. While the rest of the articles defined specific industries, and this review categorized them into 14 types of industries, such as aero-engine [43], automotive [32], [33], electronics [23], [39], [77], fast-moving consumer goods [69], garment [30], machining [62], [67], [68], [76], [80], [82], metallurgies [78], [79], [63], milling [26], [59] and gas [50], semiconductor [49], water treatment plant [73], tobacco [86], transportation [54], small-medium enterprises [52]. The correlation between IoT and AI technologies with the categorized industries type is shown in Figure 5.…”

Section: Answering Rq4: Type Of Manufacturing System Decision-making ...mentioning

confidence: 99%

“…ML techniques are categorized into several classes depending on how they are learned and what they are used for. UL, a branch of ML where a model learns patterns and structures in data without any explicit labeling or guidance from a predefined set of output labels, is considered in [27], [33], [46], [57], [59], [62], [78], [82]. UL in hardware/sensor networks and cloud/fog/edge architecture of IoT domain improves manufacturing analytics in operations management processes, especially to obtain better detection for condition monitoring of sensor-node [27], [57], machine anomalies [33], and alteration of transmitted manufacturing data [82].…”

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confidence: 99%

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Artificial intelligence and internet of things in manufacturing decision processes

Wijaya,

Hermanto Rudy,

Debora

et al. 2024

IJ-AI

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This paper explores the influence of the internet of things (IoT) and artificial intelligence (AI) on the decision-making processes of modern manufacturing systems. With the proliferation of IoT devices and the development of AI technologies, manufacturing companies increasingly leverage these technologies to improve their decision-making abilities. This study aims to investigate the potential benefits, difficulties, and ramifications of integrating IoT and AI in manufacturing systems. The review employs the preferred reporting items for systematic reviews and meta-analyses (PRISMA) method with a systematic mapping process with four research questions. A total of 1282 articles were collected between 2017 and 2023, reviewed in accordance with the inclusion and exclusion criteria, and 66 articles were chosen. The research on IoT and AI technologies influentially affects other research in the production control layer manufacturing area based on the top-ten cited articles. In contrast, the research in this area focused on the operations management layer, specifically manufacturing analytics processes. This paper’s findings contribute to a greater understanding of the impact of IoT and AI on decision-making in modern multi-domain manufacturing systems and provide direction for future research in this field.

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Section: Answering Rq4: Type Of Manufacturing System Decision-making ...mentioning

confidence: 99%

mentioning

confidence: 99%

Artificial intelligence and internet of things in manufacturing decision processes

Wijaya,

Hermanto Rudy,

Debora

et al. 2024

IJ-AI

View full text Add to dashboard Cite

show abstract

Understanding Data Correlations in Continuous Casting Systems for Autonomous Fixed Weight Cutting

Cited by 1 publication

References 13 publications

Artificial intelligence and internet of things in manufacturing decision processes

Artificial intelligence and internet of things in manufacturing decision processes

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