Results 71 to 80 of about 5,815 (232)

Run Rules-Based EWMA Charts for Efficient Monitoring of Profile Parameters [PDF]

, 2021
Ali Yeganeh, Alireza Shadman, Ioannis S. Triantafyllou, Sandile Charles Shongwe, Saddam Akber Abbasi   +4 more
openalex   +1 more source

Review on Information Fusion‐Based Data Mining for Improving Complex Anomaly Detection

WIREs Data Mining and Knowledge Discovery, Volume 15, Issue 2, June 2025.
The performance of information fusion techniques within the framework of various anomaly detection methods applied in sensor data mining. ABSTRACT Anomaly predicated upon multiple distributed hybrid sensors frequently uses hybrid approaches, integrating techniques derived from statistical analysis, probability, data mining, machine learning, deep ...
Sorin‐Claudiu Moldovan, Laszlo Barna Iantovics   +1 more
wiley   +1 more source

Tensor‐based process control and monitoring for semiconductor manufacturing with unstable disturbances

Naval Research Logistics (NRL), Volume 72, Issue 3, Page 356-371, April 2025.
Abstract With the development and popularity of sensors installed in manufacturing systems, complex data are collected during manufacturing processes, which brings challenges for traditional process control methods. This paper proposes a novel process control and monitoring method for the complex structure of high‐dimensional image‐based overlay errors
Yanrong Li, Juan Du, Fugee Tsung, Wei Jiang   +3 more
wiley   +1 more source

THE MIXED UNIVARIATE CONTROL CHART EWMA AND CUSUM FOR FLAVOUR PRODUCTION QUALITY PROCESS MONITORING

Jurnal Matematika UNAND
A control chart is an important statistical technique used to monitor the average quality of a process or dispersion. Shewhart control chart is used to detect larger disturbances in process parameters.
Surya Puspita Sari, Maiyastri Maiyastri, Dodi Devianto   +2 more
doaj   +1 more source

Robust point location estimators for the EWMA control chart [PDF]

Quality Technology & Quantitative Management, 2016
In practice, the EWMA control chart for process monitoring is based on parameters estimated from a retrospective data set representing the process characteristic under study. This data set may contain contaminated observations, which in turn can affect the estimates and hence the control chart’s performance.
Zwetsloot, I.M., Schoonhoven, M., Does, R.J.M.M.   +2 more
openaire   +2 more sources

Is There a Future for Stochastic Modeling in Business and Industry in the Era of Machine Learning and Artificial Intelligence?

Applied Stochastic Models in Business and Industry, Volume 41, Issue 2, March/April 2025.
ABSTRACT The paper arises from the experience of Applied Stochastic Models in Business and Industry which has seen, over the years, more and more contributions related to Machine Learning rather than to what was intended as a stochastic model. The very notion of a stochastic model (e.g., a Gaussian process or a Dynamic Linear Model) can be subject to ...
Fabrizio Ruggeri, David Banks, William S. Cleveland, Nicholas I. Fisher, Marcos Escobar‐Anel, Paolo Giudici, Emanuela Raffinetti, Roger W. Hoerl, Dennis K. J. Lin, Ron S. Kenett, Wai Keung Li, Philip L. H. Yu, Jean‐Michel Poggi, Marco S. Reis, Gilbert Saporta, Piercesare Secchi, Rituparna Sen, Ansgar Steland, Zhanpan Zhang   +18 more
wiley   +1 more source

Using The Exponentially Weighted Moving Average Mean Chart For Change Point Analysis [PDF]

, 2023
The exponentially weighted moving average (EWMA) chart X for monitoring a pro-cess mean was introduced by Roberts (1959)[1]. Various authors have studied thischart.
Jones, Clifford N
core   +1 more source

Design of adaptive EWMA control charts using the conditional false alarm rate [PDF]

, 2023
Burcu Aytaçoğlu, Anne R. Driscoll, William H. Woodall   +2 more
openalex   +1 more source

Prediction of stock prices with automated reinforced learning algorithms

Expert Systems, Volume 42, Issue 2, February 2025.
Abstract Predicting stock price movements remains a major challenge in time series analysis. Despite extensive research on various machine learning techniques, few models have consistently achieved success in automated stock trading. One of the main challenges in stock price forecasting is that the optimal model changes over time due to market dynamics.
Said Yasin, Adrian Paschke, Jamal Al Qundus   +2 more
wiley   +1 more source

Triple exponentially weighted moving average control chart with measurement error

Scientific Reports, 2023
Measurement error (M.E) can have a substantial impact on quality control applications, diminishing the sensitivity to detect changes in the mean or variance of quality characteristics.
Jing Wang, Muhammad Arslan, Afshan Riaz, Showkat Ahmad Lone, Nevine M. Gunaime   +4 more
doaj   +1 more source