Industrial AI Laboratory (IAI Lab)

School of Mechanical Engineering,

Chung-Ang University

중앙대학교 산업 인공지능 연구실

Industrial AI Laboratory (IAI Lab)
School of Mechanical Engineering, Chung-Ang University

중앙대학교 산업 인공지능 연구실

OUR VISION

Engineering Meets AI,

AI Meets Engineering.

Generated by diffusion model
Generated by diffusion model

The overarching objective of the IAI Lab is to pioneer AI-driven advancements by leveraging the strength of engineering background. By integrating the knowledge of diverse engineering disciplines ranging from mechanical engineering, physics, and computer science, we harness the full potential of artificial intelligence (AI) in redefining engineering processes and outcomes. We are dedicated to developing advanced AI methods based on physics-guided and data-driven insights, enabling us to model the complexities of various engineering systems well. Our strategies extend beyond conventional and existing approaches by empowering AI-aided engineering, thereby facilitating unprecedented perception, decision-making, optimization, and so on. Through this synergy of engineering and AI, the IAI Lab strives to pioneer a new wave of AI innovation, elevating the engineering landscape and further making the future industry smarter and more efficient.

RESEARCH THRUST

Towards Seamless Industrial AI

IAI Lab conducts extensive research to seamlessly integrate artificial intelligence (AI) across various industrial aspects, from physical phenomena to manufacturing processes, aiming to enhance efficiency, predictability, and intelligent functionality.

Physics-guided AI

Scientific and engineering knowledge-guided AI for generalization

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Generative AI for Engineering

Novel discovery of engineering structures and materials for desired properties

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AI for Smart Manufacturing

Data-driven approaches to unravel the relations between process parameters and outcomes

View more

Advanced System Intelligence

Innovative metrology, perception and monitoring for diverse engineering systems

View more

CORE APPLICATIONS

AI+X Impacts

NEWS

Recent News at IAI Lab

OUR VISION

Engineering Meets AI,

AI Meets Engineering.

The overarching objective of the IAI Lab is to pioneer AI-driven advancements by leveraging the strength of engineering background. By integrating the knowledge of diverse engineering disciplines ranging from mechanical engineering, physics, and computer science, we harness the full potential of artificial intelligence (AI) in redefining engineering processes and outcomes. We are dedicated to developing advanced AI methods based on physics-guided and data-driven insights, enabling us to model the complexities of various engineering systems well. Our strategies extend beyond conventional and existing approaches by empowering AI-aided engineering, thereby facilitating unprecedented perception, decision-making, optimization, and so on. Through this synergy of engineering and AI, the IAI Lab strives to pioneer a new wave of AI innovation, elevating the engineering landscape and further making the future industry smarter and more efficient.

(Generated by diffusion model)
(Generated by diffusion model)

RESEARCH THRUSTS

Towards Seamless Industrial AI

IAI Lab conducts extensive research to seamlessly integrate artificial intelligence (AI) across various industrial aspects, from physical phenomena to manufacturing processes, aiming to enhance efficiency, predictability, and intelligent functionality.

Physics-guided AI 

Scientific and engineering knowledge-guided AI for generalization

View more

AI for Smart Manufacturing

Data-driven approaches to unravel the relations between process parameters and outcomes

View more

Generative AI for Engineering

Novel discovery of engineering structures and materials for desired properties

View more

Advanced System Intelligence

Innovative metrology, perception and monitoring for diverse engineering systems

View more

CORE APPLICATIONS

AI+X Impacts

[07/25/24] AI Tutorial (한국소성가공학회 인공지능 강습회)

Title: 소성가공 분야 예시를 통한 능동 학습과 물리지식기반 인공지능 소개 (한국소성가공학회 인공지능 강습회)

Abstract: 최근 다양한 인공지능 모델을 활용하여 소재의 물성을 예측하는 연구 그리고 공정 조건을 최적화하는 연구들이 활발히 진행되고 있다. 인공지능은 기존의 실험 및 시뮬레이션 방법들의 물질적 그리고 시간적 제한을 극복하기 위해 사용되고 있으며 데이터에만 의존하지 않고 사전에 알고 있던 물리 지식들을 함께 학습에 반영할 수 있는 물리지식기반 인공지능 또한 제안되었다. 특히, 물리지식기반 인공지능은 물리적 정합성을 갖춘 예측을 가능하게 하며 데이터가 없거나 부족 한 상황에서도 활용 가능하기 때문에 그 중요성은 더욱 대두되고 있다. 본 강좌의 1부에서는 기계학습 및 딥러닝의 기초에 대해서 배우고 설명 가능한 인공지능 방법인 SHAP과 LIME의 응용 사례를 제시하고자 한다. 2부에서는 능동 학습 기반 인공지능의 기본 개념을 소개하고 이를 활용 한 단일/다중 목적성 탐색 기법에 대해 다룰 것이다. 마지막으로 3부에서는 물리지식기반 인공지능의 원리에 대해 소개하고 물리지식기반 인공지능 모델 학습에 데이터를 추가적으로 활용할 수 있는 방법을 배울 예정이다.