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  • Spotfire Statistica® Monitoring & Alerting Server


    Statistica Monitoring & Alerting Server (MAS) is an add-on to Statistica Server.  It centralizes and automates the monitoring of many processes and product parameters. The ongoing monitoring is an automated and efficient method for a) monitoring many critical parameters simultaneously, and b) providing status "snapshots" from the results of these monitoring activities to personnel based on their responsibilities. Process monitoring models (e.g., for control of batch maturation processes, continuous processes such as power generation, chemical manufacturing, etc.) can be deployed to MAS, to enable enterprise-wide comprehensive multivariate process monitoring.  Monitoring the quality (predictive - actual results) of models is another common use case for MAS.

    Spotfire Statistica Monitoring & Alerting Server (MAS) is an add-on to Spotfire Statistica Server

    It centralizes and automates the monitoring of many processes and product parameters. The ongoing monitoring is an automated and efficient method for a) monitoring many critical parameters simultaneously, and b) providing status "snapshots" from the results of these monitoring activities to personnel based on their responsibilities.

    Process monitoring models (e.g., for control of batch maturation processes, continuous processes such as power generation, chemical manufacturing, etc.) can be deployed to MAS, to enable enterprise-wide comprehensive multivariate process monitoring.  Monitoring the quality (predictive - actual results) of models is another common use case for MAS. 

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    The product directly integrates with your data collection systems including relational database management systems, data warehouses, data historians, process information systems, and laboratory information management systems (LIMS). Common analyses used for ongoing monitoring of characteristics include:

    • Quality Control charts
    • Process Capability
    • Multiple Linear Regression
    • Partial Least Squares Regression
    • Principal Components Analysis (PCA)
    • Neural Networks
    • Support Vector Machines
    • MARSplines
    • Classification and Regression Trees
    • Time Series

    MAS allows you to define rules for the definition of events and actions. Events are defined very flexibly; they can be as simple as an out-of-limits sample or can be defined based on the predictions from a model. MAS allows you to define specific actions to associate with each parameter being monitored. When an event occurs, MAS executes one or more actions, including the distribution of an email message to a defined list of recipients, executing a Statistica workspace , or a call to another application.

    Proactive Alerting Applications

    One category of application for MAS is applicable when there are many critical parameters to be monitored in your process or products. Rather than requiring a manual review of these parameters, MAS allows you to automate the ongoing analysis and offload this resource intensive process to one or more Statistica servers. MAS applies statistical techniques and your rules for the definitions of events that are noteworthy. Actions define the response to these events (e.g., deviations on a critical quality attribute) such as alerting personnel to a potential problem. MAS is scalable for the monitoring of thousands of parameters.

    Dashboard Monitoring Applications

    With a complex manufacturing process or a product suite with many critical quality characteristics, often it is not possible to review the latest samples or batches manually for each characteristic. Instead, personnel needs an easy and efficient way to be updated on the latest status on those critical parameters. MAS provides the definition of dashboard summary user interfaces that provides a snapshot of the status of many parameters in a single user interface. Dashboards are associated with User/Group permissions in Statistica so that a particular User or Group has access to the Dashboard that fits their respective responsibilities.


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