Zero defect manufacturing: state-of-the-art review, shortcomings and future directions in research

F Psarommatis, G May, PA Dreyfus… - International journal of …, 2020 - Taylor & Francis
This paper provides a literature review on zero defect manufacturing based on the content
analysis performed for 280 research articles published from 1987 to 2018 in a variety of …

Virtual metrology as an approach for product quality estimation in Industry 4.0: a systematic review and integrative conceptual framework

PA Dreyfus, F Psarommatis, G May… - International Journal of …, 2022 - Taylor & Francis
Virtual metrology (VM) involves estimating a product's quality directly from production
process data without physically measuring it. This enables the product quality of each unit of …

Machine learning for predictive maintenance: A multiple classifier approach

GA Susto, A Schirru, S Pampuri… - IEEE transactions on …, 2014 - ieeexplore.ieee.org
In this paper, a multiple classifier machine learning (ML) methodology for predictive
maintenance (PdM) is presented. PdM is a prominent strategy for dealing with maintenance …

SOPHIA: An event-based IoT and machine learning architecture for predictive maintenance in industry 4.0

M Calabrese, M Cimmino, F Fiume, M Manfrin… - Information, 2020 - mdpi.com
Predictive Maintenance (PdM) is a prominent strategy comprising all the operational
techniques and actions required to ensure machine availability and to prevent a machine …

[HTML][HTML] A global survey on the current state of practice in Zero Defect Manufacturing and its impact on production performance

G Fragapane, R Eleftheriadis, D Powell, J Antony - Computers in Industry, 2023 - Elsevier
To be competitive in dynamic and global markets, manufacturing companies are
continuously seeking to apply innovative production strategies and methods combined with …

Possible applications of edge computing in the manufacturing industry—systematic literature review

K Kubiak, G Dec, D Stadnicka - Sensors, 2022 - mdpi.com
This article presents the results of research with the main goal of identifying possible
applications of edge computing (EC) in industry. This study used the methodology of …

Application of Artificial Intelligence in the Oil and Gas Industry

M Hussain, A Alamri, T Zhang, I Jamil - Engineering Applications of …, 2024 - Springer
The oil and gas industry substantially influences global energy production due to its
complexity and faces different challenges. In various industries, including the oil and gas …

Decision-based virtual metrology for advanced process control to empower smart production and an empirical study for semiconductor manufacturing

CF Chien, WT Hung, CW Pan… - Computers & Industrial …, 2022 - Elsevier
Virtual metrology (VM) has been employed to improve the performance of advanced process
control for semiconductor manufacturing. A number of VM models have been proposed to …

A data-driven approach to selection of critical process steps in the semiconductor manufacturing process considering missing and imbalanced data

DH Lee, JK Yang, CH Lee, KJ Kim - Journal of Manufacturing Systems, 2019 - Elsevier
Semiconductor wafers are fabricated through sequential process steps. Some process steps
have a strong relationship with wafer yield, and these are called critical process steps …

Generative ai and process systems engineering: The next frontier

B Decardi-Nelson, AS Alshehri, A Ajagekar… - Computers & Chemical …, 2024 - Elsevier
This review article explores how emerging generative artificial intelligence (GenAI) models,
such as large language models (LLMs), can enhance solution methodologies within process …