Page 62 - IJAMD-2-2

International Journal of AI for
Materials and Design

PERSPECTIVE ARTICLE
Rethinking industrial artificial intelligence: A

unified foundation framework

Jay Lee and Hanqi Su*
Center for Industrial Artificial Intelligence, Department of Mechanical Engineering, A. James Clark
School of Engineering, University of Maryland, College Park, Maryland, United States of America

Abstract
Recent advancements in industrial artificial intelligence (AI) are reshaping the
industry by driving smarter manufacturing, predictive maintenance, and intelligent
decision-making. However, existing approaches often focus primarily on algorithms
and models while overlooking the importance of systematically integrating domain
knowledge, data, and models to develop more comprehensive and effective AI
solutions. Therefore, the effective development and deployment of industrial AI
require a more comprehensive and systematic approach. To address this gap, this
paper reviews previous research, rethinks the role of industrial AI, and proposes a
unified industrial AI foundation framework comprising three core modules: the
knowledge module, data module, and model module. These modules help to extend
and enhance the industrial AI methodology platform, supporting various industrial
applications. In addition, a case study on rotating machinery diagnosis is presented
to demonstrate the effectiveness of the proposed framework, and several future
*Corresponding author: directions are highlighted for the development of the industrial AI foundation
Hanqi Su framework.
(hanqisu@umd.edu)
Citation: Lee J, Su H. Rethinking
industrial artificial intelligence: Keywords: Industrial artificial intelligence; Industry 4.0; Machine learning; Deep learning;
A unified foundation framework. Int Large language model; Domain knowledge
J AI Mater Design. 2025;2(2):56-68.
doi: 10.36922/IJAMD025080006
Received: February 21, 2025
1st revised: March 23, 2025 1. Introduction
2nd revised: March 28, 2025 The rapid advancement of industrial artificial intelligence (AI) is reshaping industries
worldwide. Recent breakthroughs in technologies such as deep learning, industrial
1-4
1,2
Accepted: April 2, 2025
7,8
internet of things (IIoT), large language models (LLMs), prognostics and health
5,6
Published Online: April 15, 2025 management, big data analytics, 11,12 and cyber-physical systems (CPS) 13,14 have
9,10
Copyright: © 2025 Author(s). accelerated the adoption of industrial AI, enabling industrial systems to extract actionable
This is an Open-Access article insights from vast amounts of industrial data and support intelligent decision-making.
distributed under the terms of the
Creative Commons Attribution However, current approaches often overemphasize algorithms and models while lacking
License, permitting distribution, a unified framework that systematically integrates domain knowledge, data, and models.
and reproduction in any medium, To unlock the full potential of industrial AI, a structured framework is needed – one that
provided the original work is
properly cited. integrates domain knowledge, high-quality data, and intelligent AI models to address
complex challenges in real-world industrial settings.
Publisher’s Note: AccScience
Publishing remains neutral with Recognizing this gap, this paper proposes a unified industrial AI foundation
regard to jurisdictional claims in
published maps and institutional framework composed of knowledge, data, and model modules to enhance the industrial
affiliations. AI methodology platform. The remainder of the paper is structured as follows:
Volume 2 Issue 2 (2025) 56 doi: 10.36922/IJAMD025080006