CALSYS for metering
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Catalog excerpts

CALSYS for metering - 1

CALSYS FOR METERING Instrument validation • Instrument accuracy evaluation • Integrated with Metering System • SQL Server and OPC support • Standard Procedures and Reports • Flow computer integrity check • On-line reference and samples • Overall metering system

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CALSYS for metering - 2

The solution to verify the overall metering uncertainty The main purpose of any flow metering system is to determine the amount of fluid that is transferred from a supplier to a customer within a given period. It is crucially importance that the uncertainty of this measurement is within the limits agreed between the two parties and, in case of fiscal metering, as required by the authorities. CALSYSTM for Metering software allows you to check and prove that your flow metering system is performing within its uncertainty limits in a traceable, objective and automated manner. The software runs on...

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CALSYS for metering - 3

Reduce maintenance costs Validation sessions For validation procedures that require human intervention dialogues are used to guide the user step by step. Validation methods An important feature of CALSYS for Metering is the Session Manager, which organises individual validations into validation sessions. A validation session is a pre-defined set of validation procedures that are required to verify a complete metering system. The Session Manager assists the operators such that the procedures are executed in a pre-defined order and within a limited period of time. During the session the persons...

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CALSYS for metering - 4

Statistical Control and Evaluation Key features • Automates instrument validation to the highest extent The most straightforward way to check the performance of an instrument is to check if the current deviation in measurement from the latest validation, is within the required limits. A more sophisticated verification method is to use Control Charts in combination with Decision Rules. This will not only consider the latest result but also the previous results in order to detect any non-random behaviour of the measurement, like a trend, an oscillation and a systematic offset. Furthermore,...

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