Big Data Analytics for Semiconductor Manufacturing

Chen, Toly

doi:10.1007/978-3-031-14065-5_1

Cited by 9 publications

(3 citation statements)

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“…Prediction: Prediction is one of the most critical applications of big data analytics methods (T. C. T. Chen, 2022a).…”

Section: Methodsmentioning

confidence: 99%

“…C. T. Chen, 2022a). There are many existing big data prediction methods, and different methods are suitable for different purposes, such as the dynamic factor model for predicting the diffusion index, the multi-factor augmented Bayesian shrinkage model for predicting employment, the factor augmented error correction model for predicting bilateral exchange rates, Bayesian regression model for predicting price index, an artificial neural network (ANN) for predicting household expenditure (Hassani & Silva, 2015), principal component regression for predicting job cycle time, principal component analysis (PCA)-ANN for predicting price index, etc (T. C. T. Chen, 2022b).…”

Section: Methodsmentioning

confidence: 99%

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Impact of the COVID-19 Pandemic on the Revenue of the Catering Industry: Taiwan as an Example

Wu,

Chen,

Wang

2024

Sage Open

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Due to the impact of the COVID-19 pandemic, people have reduced eating out, resulting in a severe drop in the revenue of the catering industry. Health risks have become a major factor affecting the revenue of this industry. Predicting the revenue of the catering industry during the COVID-19 pandemic will not only allow practitioners to adjust their business strategies, but also provide a reference for governments to formulate relief measures. To this end, this study proposes a fuzzy big data analytics approach in which random forests, recursive feature elimination, fuzzy c-means, and deep neural networks are jointly applied. First, random forests and recursive feature elimination are used to select the most influential factors. The data is then divided into clusters by fuzzy c-means. Subsequently, a deep neural network is built for each cluster to make predictions. The prediction results of individual clusters are then aggregated to improve prediction accuracy. The proposed methodology has been applied to forecast the revenue of the catering industry in Taiwan. The results of the experiment showed that the impact of new deaths on the revenue of the catering industry was far greater than the number of newly diagnosed COVID-19 cases.

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“…Prediction: Prediction is one of the most critical applications of big data analytics methods (T. C. T. Chen, 2022a).…”

Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Impact of the COVID-19 Pandemic on the Revenue of the Catering Industry: Taiwan as an Example

Wu,

Chen,

Wang

2024

Sage Open

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“…As far as methodologies and related software are concerned, a categorization is attempted in [ 36 ] (with a specific section for semiconductors, as in [ 37 ]), in [ 38 , 39 , 40 , 41 ] for ML particularly, and [ 42 ] for graph-based approaches.…”

Section: Introductionmentioning

confidence: 99%

Predictive Maintenance of Pins in the ECD Equipment for Cu Deposition in the Semiconductor Industry

Amato,

Antoniadis,

De Feis

et al. 2023

Sensors

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Nowadays, Predictive Maintenance is a mandatory tool to reduce the cost of production in the semiconductor industry. This paper considers as a case study a critical part of the electrochemical deposition system, namely, the four Pins that hold a wafer inside a chamber. The aim of the study is to replace the schedule of replacement of Pins presently based on fixed timing (Preventive Maintenance) with a Hardware/Software system that monitors the conditions of the Pins and signals possible conditions of failure (Predictive Maintenance). The system is composed of optical sensors endowed with an image processing methodology. The prototype built for this study includes one optical camera that simultaneously takes images of the four Pins on a roughly daily basis. Image processing includes a pre-processing phase where images taken by the camera at different times are coregistered and equalized to reduce variations in time due to movements of the system and to different lighting conditions. Then, some indicators are introduced based on statistical arguments that detect outlier conditions of each Pin. Such indicators are pixel-wise to identify small artifacts. Finally, criteria are indicated to distinguish artifacts due to normal operations in the chamber from issues prone to a failure of the Pin. An application (PINapp) with a user friendly interface has been developed that guides industry experts in monitoring the system and alerting in case of potential issues. The system has been validated on a plant at STMicroelctronics in Catania (Italy). The study allowed for understanding the mechanism that gives rise to the rupture of the Pins and to increase the time of replacement of the Pins by a factor at least 2, thus reducing downtime.

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Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

Rahman

Islam

Kundu

et al. 2023

Int J Communication

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SummaryAs an emerging technology, blockchain (BC) has been playing a promising role in today's software‐defined networking (SDN)‐enabled Internet of Things (IoT) applications. Because of the salient feature of the network function virtualization (NFV) techniques, SDN can ensure an IoT system runs efficiently and smoothly in a cloud‐driven ecosystem. When cloud‐enabled systems encounter immense security and operational challenges caused mainly by third‐party dependency, large‐scale data communication, and maintenance, BC offers effective and robust data transfer solutions without incorporating intermediaries over the distributed network. With the increased SDN‐BC convergence in the IoT domain, the underlying challenges and perspectives deserve proper attention methodically and structurally. From the motivation of addressing such issues, this study provides necessary insights to combine those for successful plug‐and‐play. Therefore, the study includes purposefully investigating current state‐of‐the‐art to extract the research trends, future directions, and perspectives in this domain. This study provides a comprehensive survey of IoT, SDN, NFV, and BC‐enabled emerging technologies. More importantly, the authors intelligently integrated the four different technologies—IoT, SDN, BC, and NFV based on characteristics, scopes, challenges, taxonomies, and tables in numerous areas. Initially, the authors introduce the SDN‐IoT ecosystem in brief and address the features and applications. We took a close look at the SDN's overall taxonomy based on security, environment, scopes, and challenges. We also briefly describe the integration of SDN‐IoT with the NFV ecosystems. Moreover, we review the prospect of BC technology from security perspectives, its extent, challenges of practical implementation, and the possible integration of IoT regarding smart applications. Finally, this study highlights several future directions based on these technologies.

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Big Data Analytics for Semiconductor Manufacturing

Cited by 9 publications

References 50 publications

Impact of the COVID-19 Pandemic on the Revenue of the Catering Industry: Taiwan as an Example

Impact of the COVID-19 Pandemic on the Revenue of the Catering Industry: Taiwan as an Example

Predictive Maintenance of Pins in the ECD Equipment for Cu Deposition in the Semiconductor Industry

Impacts of blockchain in software‐defined Internet of Things ecosystem with Network Function Virtualization for smart applications: Present perspectives and future directions

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