Results 31 to 40 of about 6,536 (217)
Control Charts for Monitoring Burr Type-X Percentiles [PDF]
[[abstract]]When the sampling distribution of a parameter estimator is unknown, using normality asymptotically, the Shewhart-type chart may provide improper control limits.
Bader M. G. +12 more
core +1 more source
On Performance of Two-Parameter Gompertz-Based X¯ Control Charts
Journal of Probability and Statistics, 2020 In this paper, two methods of control chart were proposed to monitor the process based on the two-parameter Gompertz distribution. The proposed methods are the Gompertz Shewhart approach and Gompertz skewness correction method.
Johnson A. Adewara +2 more
doaj +1 more source
PETA KENDALI EWMA RESIDUAL PADA DATA BERAUTOKORELASI
E-Jurnal Matematika, 2019 Control charts with autocorrelation can be overcome by creating control chart with residuals from the best forecasting model. EWMA control chart is a alternative to the Shewhart control chart when detecting small shifts.
NI KADEK YUNI DEWIANTARI +2 more
doaj +1 more source
A CNN Approach for Simultaneous Spatiotemporal Fault Interpretation
Quality and Reliability Engineering International, EarlyView.ABSTRACT Convolutional Neural Networks (CNNs) have emerged as one of the most effective tools for image analysis. In this study, we propose a custom‐designed CNN architecture to construct a process control scheme based on image data. The product image is partitioned into equal‐sized grids, each comprising three channels: (i) reference image, (ii ...
Hamed Sabahno
wiley +1 more source
A Two Control Limits Double Sampling Control Chart by Optimizing Producer and Customer Risks [PDF]
ITB Journal of Engineering Science, 2010 Standard Shewhart process control chart has been widely used, but it is not sensitive in detecting small shift. A number of alternatives have been proposed to improve the capability of control chart.
Dradjat Irianto & Ani Juliani
doaj +1 more source
Phase I Multivariate Coefficient of Variation Control Charts for High‐Dimensional Processes
Quality and Reliability Engineering International, EarlyView.ABSTRACT Multivariate control charts have traditionally focused on monitoring the process mean vector and/or covariance matrix. Recent studies have extended this framework to Phase II monitoring of the multivariate coefficient of variation (MCV); yet very limited work has examined MCV‐based monitoring in Phase I.
O. A. Oyegoke +2 more
wiley +1 more source
Information Systems Journal, Volume 36, Issue 3, Page 315-339, May 2026.ABSTRACT Artificial intelligence (AI) brings great potential for manufacturers, but clashes with the established culture due to the unexplainable and opaque nature of the solutions it provides. Having little experience in AI and machine learning (ML), most manufacturing leaders experience barriers implementing AI.
Benjamin van Giffen +5 more
wiley +1 more source
Non-Parametric Vertical Box Control Chart For Monitoring The Mean [PDF]
, 2004 A new class of non-parametric control charts for detecting the change in the process mean is examined. The method, called a Vertical Box Control Chart (V-Box Chart), offers a simple and quick detection of the mean change in an observed process.
Pawlak, Miroslaw +2 more
core +2 more sources
Univariate and multivariate control charts for monitoring sugar production process [PDF]
, 2015 Quality control is a system to maintain quality of product or service to achieve specification standard of product. One of the most powerful tools is through graphical method which is control chart.
Mohamad, Ismail, Sutirman, Zetty Azrah
core
IEEE Access, 2019 An X-bar control chart using the multiple dependent state (MDS) sampling under indeterminacy is presented in this paper. The MDS sampling utilizes the previous subgroup information if in-decision on the first sample. The use of MDS increases the power of
Muhammad Aslam +2 more
doaj +1 more source
