Machine learning and deep learning based predictive quality in manufacturing: a systematic review
With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …
data from manufacturing processes and quality measurements, there is enormous potential …
A review on deep learning in machining and tool monitoring: Methods, opportunities, and challenges
V Nasir, F Sassani - The International Journal of Advanced Manufacturing …, 2021 - Springer
Data-driven methods provided smart manufacturing with unprecedented opportunities to
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …
facilitate the transition toward Industry 4.0–based production. Machine learning and deep …
基于深度学习的表面缺陷检测方法综述
陶显， 侯伟， 徐德 - 自动化学报, 2021 - aas.net.cn
近年来, 基于深度学习的表面缺陷检测技术广泛应用在各种工业场景中. 本文对近年来基于深度
学习的表面缺陷检测方法进行了梳理, 根据数据标签的不同将其分为全监督学习模型方法 …
学习的表面缺陷检测方法进行了梳理, 根据数据标签的不同将其分为全监督学习模型方法 …
Recent advances and trends of predictive maintenance from data-driven machine prognostics perspective
In the Engineering discipline, prognostics play an essential role in improving system safety,
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
reliability and enabling predictive maintenance decision-making. Due to the adoption of …
Deep industrial image anomaly detection: A survey
The recent rapid development of deep learning has laid a milestone in industrial image
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …
anomaly detection (IAD). In this paper, we provide a comprehensive review of deep learning …
Pad: A dataset and benchmark for pose-agnostic anomaly detection
Object anomaly detection is an important problem in the field of machine vision and has
seen remarkable progress recently. However, two significant challenges hinder its research …
seen remarkable progress recently. However, two significant challenges hinder its research …
Anomaly detection for industrial quality assurance: A comparative evaluation of unsupervised deep learning models
J Zipfel, F Verworner, M Fischer, U Wieland… - Computers & Industrial …, 2023 - Elsevier
Across many industries, visual quality assurance has transitioned from a manual, labor-
intensive, and error-prone task to a fully automated and precise assessment of industrial …
intensive, and error-prone task to a fully automated and precise assessment of industrial …
Deep learning-based detection of aluminum casting defects and their types
Due to its unique properties, high-pressure aluminum die-casting parts are used quite often,
especially in the automotive industry. However, die-casting is a process which requires non …
especially in the automotive industry. However, die-casting is a process which requires non …
Deep transfer learning for industrial automation: A review and discussion of new techniques for data-driven machine learning
B Maschler, M Weyrich - IEEE Industrial Electronics Magazine, 2021 - ieeexplore.ieee.org
Deep learning has greatly increased the capabilities of" intelligent" technical systems over
the last years [1]. This includes the industrial automation sector [1]-[4], where new data …
the last years [1]. This includes the industrial automation sector [1]-[4], where new data …
Approaches for improvement of the X-ray image defect detection of automobile casting aluminum parts based on deep learning
Nondestructive testing (NDT) for casting aluminum parts is an essential quality management
procedure. In order to avoid the effects of human fatigue and improve detection accuracy …
procedure. In order to avoid the effects of human fatigue and improve detection accuracy …