[go: up one dir, main page]

Arif et al., 2013 - Google Patents

A data mining approach for developing quality prediction model in multi-stage manufacturing

Arif et al., 2013

View PDF
Document ID
5486014771852515660
Author
Arif F
Suryana N
Hussin B
Publication year
Publication venue
International Journal of Computer Applications

External Links

Snippet

Quality prediction model has been developed in various industries to realize the faultless manufacturing. However, most of quality prediction model is developed in single-stage manufacturing. Previous studies show that single-stage quality system cannot solve quality …
Continue reading at www.academia.edu (PDF) (other versions)

Classifications

    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/50Computer-aided design
    • G06F17/5009Computer-aided design using simulation
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B19/00Programme-control systems
    • G05B19/02Programme-control systems electric
    • G05B19/418Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
    • G05B19/41875Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by quality surveillance of production
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/30Nc systems
    • G05B2219/45Nc applications
    • G05B2219/45031Manufacturing semiconductor wafers
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B2219/00Program-control systems
    • G05B2219/30Nc systems
    • G05B2219/32Operator till task planning
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F17/00Digital computing or data processing equipment or methods, specially adapted for specific functions
    • G06F17/30Information retrieval; Database structures therefor; File system structures therefor
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B15/00Systems controlled by a computer
    • G05B15/02Systems controlled by a computer electric
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N99/00Subject matter not provided for in other groups of this subclass
    • GPHYSICS
    • G05CONTROLLING; REGULATING
    • G05BCONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
    • G05B23/00Testing or monitoring of control systems or parts thereof
    • G05B23/02Electric testing or monitoring
    • G05B23/0205Electric testing or monitoring by means of a monitoring system capable of detecting and responding to faults
    • G05B23/0218Electric 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
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06NCOMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N5/00Computer systems utilising knowledge based models
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06FELECTRICAL DIGITAL DATA PROCESSING
    • G06F7/00Methods or arrangements for processing data by operating upon the order or content of the data handled
    • GPHYSICS
    • G06COMPUTING; CALCULATING; COUNTING
    • G06QDATA 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
    • G06Q10/00Administration; Management

Similar Documents

Publication Publication Date Title
Arif et al. A data mining approach for developing quality prediction model in multi-stage manufacturing
Arif et al. Cascade quality prediction method using multiple PCA+ ID3 for multi-stage manufacturing system
Stojanovic et al. Big-data-driven anomaly detection in industry (4.0): An approach and a case study
Zeng et al. Virtual metrology modeling for plasma etch operations
Zhang et al. Fault detection strategy based on weighted distance of $ k $ nearest neighbors for semiconductor manufacturing processes
Niaki et al. Designing a multivariate–multistage quality control system using artificial neural networks
Zhong et al. Multimode non‐Gaussian process monitoring based on local entropy independent component analysis
Shu et al. A distribution‐free control chart for monitoring high‐dimensional processes based on interpoint distances
Susto et al. A virtual metrology system based on least angle regression and statistical clustering
Zhengcai et al. Bottleneck prediction method based on improved adaptive network-based fuzzy inference system (ANFIS) in semiconductor manufacturing system
US6618632B1 (en) Process for monitoring processing plants
Lee et al. Statistical comparison of fault detection models for semiconductor manufacturing processes
Vicentin et al. Monitoring process control chart with finite mixture probability distribution: An application in manufacture industry
Xu et al. A Copula network deconvolution-based direct correlation disentangling framework for explainable fault detection in semiconductor wafer fabrication
Ciupke Multivariate process capability vector based on one‐sided model
Ghiasabadi et al. Identifying change point of a non-random pattern on control chart using artificial neural networks
Susto et al. An information-theory and virtual metrology-based approach to run-to-run semiconductor manufacturing control
Chen et al. Condition-driven soft transition modeling and monitoring strategy for complex nonstationary process
Dudas et al. Post-analysis of multi-objective optimization solutions using decision trees
JP5457737B2 (en) Plant control information generating apparatus and method, and computer program therefor
US20130030760A1 (en) Architecture for analysis and prediction of integrated tool-related and material-related data and methods therefor
Özgün et al. Malfunction detection on production line using machine learning: case study in wood industry
Bártová et al. Early defect detection using clustering algorithms
Pushphavathi An approach for software defect prediction by combined soft computing
Zhu et al. Modern big data analytics for “old-fashioned” semiconductor industry applications