A review of artificial intelligence applications in manufacturing operations

Plathottam, Siby Jose; Rzonca, Arin; Lakhnori, Rishi; Iloeje, Chukwunwike O.

doi:10.1002/amp2.10159

A review of artificial intelligence applications in manufacturing operations

Journal Article · Tue May 16 04:00:00 EDT 2023 · Journal of Advanced Manufacturing and Processing

DOI:https://doi.org/10.1002/amp2.10159· OSTI ID:1973901

^[1]; Rzonca, Arin ^[1]; Lakhnori, Rishi ^[1]; ^[1]

Energy Systems and Infrastructure Analysis Division Argonne National Laboratory Lemont Illinois USA

Abstract

Artificial intelligence (AI) and machine learning (ML) can improve manufacturing efficiency, productivity, and sustainability. However, using AI in manufacturing also presents several challenges, including issues with data acquisition and management, human resources, infrastructure, as well as security risks, trust, and implementation challenges. For example, getting the data needed to train AI models can be difficult for rare events or costly for large datasets that need labeling. AI models can also pose security risks when integrated into industrial control systems. In addition, some industry players may be hesitant to use AI due to a lack of trust or understanding of how it works. Despite these challenges, AI has the potential to be extremely helpful in manufacturing, particularly in applications such as predictive maintenance, quality assurance, and process optimization. It is important to consider the specific needs and capabilities of each manufacturing scenario when deciding whether and how to use AI in manufacturing. This review identifies current developments, challenges, and future directions in AI/ML relevant to manufacturing, with the goal of improving understanding of AI/ML technologies available for solving manufacturing problems, providing decision‐support for prioritizing and selecting appropriate AI/ML technologies, and identifying areas where further research can yield transformational returns for the industry. Early experience suggests that AI/ML can have significant cost and efficiency benefits in manufacturing, especially when combined with the ability to capture enormous amounts of data from manufacturing systems.

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Sponsoring Organization:: USDOE

Grant/Contract Number:: NONE; AC02-06CH11357

OSTI ID:: 1973901

Alternate ID(s):: OSTI ID: 1973902

Journal Information:: Journal of Advanced Manufacturing and Processing, Journal Name: Journal of Advanced Manufacturing and Processing Journal Issue: 3 Vol. 5; ISSN 2637-403X

Publisher:: Wiley Blackwell (John Wiley & Sons)Copyright Statement

Country of Publication:: United States

Language:: English

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