Abstract: A computer implemented method integrates data from remote disparate data sources by processing a non-transitory media. The non-transitory media stores instructions for detecting data sets in different formats hosted in a plurality of heterogeneous databases that are accessible through a distributed network. The method extracts schema data from the plurality of heterogeneous databases and identifies related fields in two or more of the heterogeneous databases. The method links the related fields in the two or more of the plurality of heterogeneous databases and makes the data accessible through a virtual warehouse. As schemas change, as new data sources and analysis artifacts are created, the computer implemented method and system can act as a meta-data store, a provenance tracking device, and/or a knowledge management service.

Abstract: A computer implemented method integrates data from remote disparate data sources by processing a non-transitory media. The non-transitory media stores instructions for detecting data sets in different formats hosted in a plurality of heterogeneous databases that are accessible through a distributed network. The method extracts schema data from the plurality of heterogeneous databases and identifies related fields in two or more of the heterogeneous databases. The method links the related fields in the two or more of the plurality of heterogeneous databases and makes the data accessible through a virtual warehouse. As schemas change, as new data sources and analysis artifacts are created, the computer implemented method and system can act as a meta-data store, a provenance tracking device, and/or a knowledge management service.

Abstract: A method for indexing and retrieving manufacturing-specific digital images based on image content comprises three steps. First, at least one feature vector can be extracted from a manufacturing-specific digital image stored in an image database. In particular, each extracted feature vector corresponds to a particular characteristic of the manufacturing-specific digital image, for instance, a digital image modality and overall characteristic, a substrate/background characteristic, and an anomaly/defect characteristic. Notably, the extracting step includes generating a defect mask using a detection process. Second, using an unsupervised clustering method, each extracted feature vector can be indexed in a hierarchical search tree. Third, a manufacturing-specific digital image associated with a feature vector stored in the hierarchicial search tree can be retrieved, wherein the manufacturing-specific digital image has image content comparably related to the image content of the query image.

Abstract: A method for localizing and isolating an errant process includes the steps of retrieving from a defect image database a selection of images each image having image content similar to image content extracted from a query image depicting a defect, each image in the selection having corresponding defect characterization data. A conditional probability distribution of the defect having occurred in a particular process step is derived from the defect characterization data. A process step as a highest probable source of the defect according to the derived conditional probability distribution is then identified. A method for process step defect identification includes the steps of characterizing anomalies in a product, the anomalies detected by an imaging system. A query image of a product defect is then acquired. A particular characterized anomaly is then correlated with the query image. An errant process step is then associated with the correlated image.