Data-driven methods for batch data analysis–A critical overview and mapping on the complexity scale
More than two decades have passed since the first holistic data-driven approaches for batch
data analysis (BDA) were published. The emphasis was on multivariate statistical process …
data analysis (BDA) were published. The emphasis was on multivariate statistical process …
Industrial process monitoring in the big data/industry 4.0 era: From detection, to diagnosis, to prognosis
MS Reis, G Gins - Processes, 2017 - mdpi.com
We provide a critical outlook of the evolution of Industrial Process Monitoring (IPM) since its
introduction almost 100 years ago. Several evolution trends that have been structuring IPM …
introduction almost 100 years ago. Several evolution trends that have been structuring IPM …
Multiple time-series convolutional neural network for fault detection and diagnosis and empirical study in semiconductor manufacturing
CY Hsu, WC Liu - Journal of Intelligent Manufacturing, 2021 - Springer
The development of information technology and process technology have been enhanced
the rapid changes in high-tech products and smart manufacturing, specifications become …
the rapid changes in high-tech products and smart manufacturing, specifications become …
Clustering application for condition-based maintenance in time-varying processes: A review using latent dirichlet allocation
In the field of industrial process monitoring, scholars and practitioners are increasing interest
in time-varying processes, where different phases are implemented within an unknown time …
in time-varying processes, where different phases are implemented within an unknown time …
Defective wafer detection using a denoising autoencoder for semiconductor manufacturing processes
SKS Fan, CY Hsu, CH Jen, KL Chen, LT Juan - Advanced Engineering …, 2020 - Elsevier
Defective wafer detection is essential to avoid loss of yield due to process abnormalities in
semiconductor manufacturing. For most complex processes in semiconductor …
semiconductor manufacturing. For most complex processes in semiconductor …
Fault detection and diagnosis using self-attentive convolutional neural networks for variable-length sensor data in semiconductor manufacturing
Nowadays, more attention has been placed on cost reductions and yield enhancement in
the semiconductor industry. During the manufacturing process, a considerable amount of …
the semiconductor industry. During the manufacturing process, a considerable amount of …
Data-driven two-dimensional deep correlated representation learning for nonlinear batch process monitoring
Dynamics and nonlinearity may exist in the time and batch directions for batch processes,
thereby complicating the monitoring of these processes. In this article, we propose a two …
thereby complicating the monitoring of these processes. In this article, we propose a two …
Multiobjective differential evolution algorithm for solving robotic cell scheduling problem with batch-processing machines
X Wu, Q Yuan, L Wang - IEEE transactions on automation …, 2020 - ieeexplore.ieee.org
Robotic cell scheduling problem with batch-processing machines (RCSP-BMs) needs to
determine the processing sequence and the transferring sequence simultaneously. The …
determine the processing sequence and the transferring sequence simultaneously. The …
Bayesian network for integrated circuit testing probe card fault diagnosis and troubleshooting to empower Industry 3.5 smart production and an empirical study
Probe card that serves as the carrier of die and the transmitter of information is an
indispensable test interface for integrated circuit testing. The probe card extracts the …
indispensable test interface for integrated circuit testing. The probe card extracts the …
An improved mixture of probabilistic PCA for nonlinear data-driven process monitoring
J Zhang, H Chen, S Chen… - IEEE transactions on …, 2017 - ieeexplore.ieee.org
An improved mixture of probabilistic principal component analysis (PPCA) has been
introduced for nonlinear data-driven process monitoring in this paper. To realize this …
introduced for nonlinear data-driven process monitoring in this paper. To realize this …