AI for manufacturing efficiency and healthcare advancement

Paper Title:

AI for Manufacturing and Healthcare: a chemistry and engineering perspective

Published on:

2 May 2024

Primary Category:

Materials Science

Paper Authors:

Jihua Chen,

Yue Yuan,

Amir Koushyar Ziabari,

Xuan Xu,

Honghai Zhang,

Panagiotis Christakopoulos,

Peter V. Bonnesen,

Ilia N. Ivanov,

Panchapakesan Ganesh,

Chen Wang,

Karen Patino Jaimes,

Guang Yang,

Rajeev Kumar,

Bobby G. Sumpter,

Rigoberto Advincula

Bullets

Key Details

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Battery: AI for state of health estimation and lifetime prediction

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Flow chemistry: Multi-objective optimization for automated synthesis

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Additive manufacturing: Defect detection, design automation

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Sensors: Sensor fusion for vehicles, IoT, environment monitoring

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Machine vision: Image analysis, reconstruction, microscopy

•

Medical imaging: Detection, diagnosis, image enhancement

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Diagnosis: Disease identification from varied data sources

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Protein design: Structure prediction, directed evolution

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Drug discovery: Target identification, lead optimization

Explore the topics in this paper

ai

healthcare

manufacturing

productivity

responsible ai

AI generated summary

AI for manufacturing efficiency and healthcare advancement

This paper reviews applications of AI in manufacturing, focusing on battery management, flow chemistry, additive manufacturing, sensors, and machine vision; and in healthcare, focusing on medical imaging, diagnosis, protein design, and drug discovery. AI promises to enhance productivity, enable new capabilities, and transform industries. But realizing its potential requires addressing challenges around data, algorithms, integration, and responsible development.