Predictive condition monitoring of industrial systems for improved maintenance and operation [PDF]
, 2014 Maintenance strategies based on condition monitoring of the different machines and devices in an industrial process can minimize downtime, increase the safety of plant operations and help in the process of decision-taking for control and maintenance ...
Ruiz Cárcel, Cristóbal
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Quality-Related Process Monitoring Based on Improved Kernel Principal Component Regression
IEEE Access, 2021 To date, quality-related multivariate statistical methods are extensively used in process monitoring and have achieved admirable effects. However, most of them contain recursive processes, which result in higher time complexity and are not suitable for ...
Li Qi +4 more
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A Review and Perspective on Neutrosophic Statistical Process Monitoring Methods
IEEE Access, 2022 We review the literature on statistical process monitoring methods based on neutrosophic principles. We question some of the underlying assumptions and raise important questions about these and other neutrosophic statistical methods that need to be ...
William H. Woodall +2 more
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Statistical Process Control in Monitoring Radiotherapy Quality Assurance Program: An Institutional Experience. [PDF]
Iranian Journal of Medical Physics, 2022 Introduction: Statistical process control (SPC) is a handy and powerful tool for monitoring quality assurance (QA) programs in radiotherapy. This study explains the institutional experience in monitoring weekly output constancy QA and patient-specific ...
Vysakh R +3 more
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Phase I Monitoring of Multivariate Ordinal Based Processes: The MR and LRT Approaches (A Real Case Study in Drug Dissolution Process) [PDF]
International Journal of Industrial Engineering and Production Research, 2022 In some statistical processes monitoring (SPM) applications, relationship between two or more ordinal factors is shown by an ordinal contingency table (OCT) and it is described by the ordinal Log-linear model (OLLM). Newton-Raphson algorithm methods have
Ahmad Hakimi +3 more
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Monitoring the Zero-Inflated Time Series Model of Counts with Random Coefficient
Entropy, 2021 In this research, we consider monitoring mean and correlation changes from zero-inflated autocorrelated count data based on the integer-valued time series model with random survival rate.
Cong Li, Shuai Cui, Dehui Wang
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A Combined Runs Rules Scheme for Monitoring General Inflated Poisson Processes
Mathematics, 2023 In this work, a control chart with multiple runs rules is proposed and studied in the case of monitoring inflated processes. Usually, Shewhart-type control charts for attributes do not have a lower control limit, especially when the in-control process ...
Eftychia Mamzeridou +1 more
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Nonstationary Process Monitoring Based on Cointegration Theory and Multiple Order Moments
, 2022 In industrial processes, process data often exhibit complex characteristics, such as nonstationarity and nonlinearity, which brings challenges to process monitoring.
Yang Li +3 more
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Vehicle Driver Monitoring through the Statistical Process Control
Sensors, 2019 This paper proposes the use of the Statistical Process Control (SPC), more specifically, the Exponentially Weighted Moving Average method, for the monitoring of drivers using approaches based on the vehicle and the driver’s behavior. Based on the SPC, we
Arthur N. Assuncao +4 more
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State-space independent component analysis for nonlinear dynamic process monitoring [PDF]
, 2010 The cost effective benefits of process monitoring will never be over emphasised. Amongst monitoring techniques, the Independent Component Analysis (ICA) is an efficient tool to reveal hidden factors from process measurements, which follow non-Gaussian
Odiowei, P. P., Cao, Yi
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