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Metadata Conformance Analyzer (MCA)
The Metadata Conformance Analyzer is a software tool that will import and evaluate equipment-provided self-description data (metadata) for conformance to applicable SEMI requirements and ISMI guidelines.
Semiconductor factories face increasing manufacturing challenges due to continued feature shrink and cost pressures in the marketplace. The next generation factories are expected to reduce significantly both cost and cycle-time, perhaps by as much as 30% and 50% respectively. Achieving these goals require high quality data to provide fast and accurate knowledge allowing rapid detection, analysis, and resolution of system problems during the semiconductor manufacturing process. SEMI Equipment Data Acquisition (EDA) standards provide an improved data collection mechanism for the industry. EDA uses modern, mainstream network communications. An important part of EDA is the equipment self-description or metadata. The equipment metadata provides the user with a full description of the equipment's behavior and the data available for collection. It can turn a weeks-long process of configuring data collection involving significant IT resources into a matter of minutes involving only the manufacturing engineer.
Equipment manufacturers are challenged to produce high quality metadata. A way to evaluate and improve the equipment metadata was needed. In order to assure compliance quickly, NIST and ISMI joined forces to develop an automated tool to evaluate equipment metadata against the EDA standards and against International SEMATECH Manufacturing Initiative (ISMI) developed industry guidelines. This tool, the Metadata Conformance Analyzer (MCA), is now publicly available.
The goal of the ISMI - NIST project is to research and develop strategies for automated validation of equipment data quality based on EDA standard requirements and industry guidelines. The choice of underlying development tools was driven by the anticipated eventual need to pass this application on to the semiconductor industry for further extension and optimization.
The MCA tool is based upon Java and uses a freely available rule-engine, JBoss Drools. Drools utilizes the Rete algorithm to optimize handling of large data sets as well as ease of coding to accommodate additions / changes of the rules.
The MCA tool detects and reports metadata errors, including conflicts with the schema as well as violations of SEMI standards and ISMI guideline requirements. It also provides warnings of some ambiguous results to assist the user analysis of requirements that cannot be fully analyzed programmatically. The results are designed to help the implementer identify and correct issues with their metadata.
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