Yeong et al., 2015 - Google Patents
Economic‐statistical design of the synthetic chart with estimated process parametersYeong et al., 2015
- Document ID
- 8477357947124168917
- Author
- Yeong W
- Khoo M
- Yanjing O
- Castagliola P
- Publication year
- Publication venue
- Quality and Reliability Engineering International
External Links
Snippet
In this paper, the effects of process parameter estimation on the cost of the synthetic chart are studied. We study the increase in cost when the optimal chart's parameters corresponding to the known process parameters case are used to estimate the cost when …
- 238000000034 method 0 title abstract description 175
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06Q—DATA PROCESSING SYSTEMS OR METHODS, SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL, SUPERVISORY OR FORECASTING PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management, e.g. organising, planning, scheduling or allocating time, human or machine resources; Enterprise planning; Organisational models
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0218—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterised by the fault detection method dealing with either existing or incipient faults
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F17/00—Digital computing or data processing equipment or methods, specially adapted for specific functions
-
- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B23/00—Testing or monitoring of control systems or parts thereof
- G05B23/02—Electric testing or monitoring
- G05B23/0205—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
- G05B23/0259—Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults characterized by the response to fault detection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N99/00—Subject matter not provided for in other groups of this subclass
- G06N99/005—Learning machines, i.e. computer in which a programme is changed according to experience gained by the machine itself during a complete run
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F11/00—Error detection; Error correction; Monitoring
- G06F11/07—Error detection; Error correction; Monitoring responding to the occurence of a fault, e.g. fault tolerance
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F21/00—Security arrangements for protecting computers, components thereof, programs or data against unauthorised activity
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06F—ELECTRICAL DIGITAL DATA PROCESSING
- G06F1/00—Details of data-processing equipment not covered by groups G06F3/00 - G06F13/00, e.g. cooling, packaging or power supply specially adapted for computer application
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N7/00—Computer systems based on specific mathematical models
- G06N7/005—Probabilistic networks
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING; COUNTING
- G06N—COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
- G06N5/00—Computer systems utilising knowledge based models
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Yeong et al. | Economic‐statistical design of the synthetic chart with estimated process parameters | |
| Xu et al. | Nonlinear general path models for degradation data with dynamic covariates | |
| Zhang et al. | The variable sampling interval X chart with estimated parameters | |
| Castagliola et al. | The variable sample size chart with estimated parameters | |
| Tran et al. | On the performance of Shewhart median chart in the presence of measurement errors | |
| Khilare et al. | Nonparametric synthetic control charts for process variation | |
| Ou et al. | A comparison study on effectiveness and robustness of control charts for monitoring process mean and variance | |
| You et al. | Monitoring the coefficient of variation using the side sensitive group runs chart | |
| Saghir et al. | A flexible and generalized exponentially weighted moving average control chart for count data | |
| Li et al. | Multiple attribute control charts with false discovery rate control | |
| Wu et al. | A review of the extensions of the geometric process, applications, and challenges | |
| D′ Amico et al. | Reliability Measures of Second‐Order Semi‐Markov Chain Applied to Wind Energy Production | |
| Rajmanya et al. | A synthetic control chart for monitoring process variability | |
| Guo et al. | The design of the ARL‐unbiased S2 chart when the in‐control variance is estimated | |
| Huang et al. | A generalized likelihood ratio chart for monitoring Bernoulli processes | |
| Lupo | A multi‐objective design approach for the c chart considering Taguchi loss function | |
| Ou et al. | An adaptive CUSUM chart with single sample size for monitoring process mean and variance | |
| Niaki et al. | A parameter-tuned genetic algorithm for economic-statistical design of variable sampling interval X-bar control charts for non-normal correlated samples | |
| Tian et al. | Process fault prognosis using a fuzzy‐adaptive unscented Kalman predictor | |
| Li et al. | On the performance of two‐sided control charts for short production runs | |
| Yun et al. | An optimal reliability and maintainability design of a searching system | |
| Chen et al. | Performance analysis of queue length monitoring of M/G/1 systems | |
| Kazemi et al. | Estimating the drift time for processes subject to linear trend disturbance using fuzzy statistical clustering | |
| Lupo | Comparing the economic effectiveness of various adaptive schemes for the c chart | |
| Darkhovsky et al. | Model‐free offline change‐point detection in multidimensional time series of arbitrary nature via ϵ‐complexity: Simulations and applications |