Sessions

SigmafineHub: A Digital Asset Factory for the enterprise

Download Now! SigmafineHub: A Digital Asset Factory for the enterprise For over 25 years, Sigmafine systems have been reliably delivering reconciled data to users, applications, and business processes across multiple verticals in the process industries. In today’s terms, the purpose of Sigmafine is to “Transform raw data and signals into digital assets” to support and …

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Sigmafine in ISAB refining and power generation

Hear how Sigmafine was expanded at ISAB to include the monitoring of power generation assets and utility networks. Giving insight and accurate production accounting for this integrated refinery & power generation site that is critical to maximize operational and financial performance.

ICL Rotem tests Sigmafine advanced analytics

Sigmafine extended capabilities were recently evaluated in the context of a proof of concept project to perform the daily mass & component balance; monitor the data quality of the meters, estimate material type and chemical properties of unmeasured inventories and flows. Hear about some of the findings in this presentation.

Using Sigmafine to facilitate communication and drive data-informed decisions across the organization

At the Billings refinery, Sigmafine is used to facilitate communication and drive data-informed decisions across the organization.   Accounting for timely and accurate inventory and production numbers involves taking disparate Data inputs from multiple sources and departments.  This information then needs to be conditioned in a manner that can provide a meaningful and accurate dataset to the data consumers.  The information needs to be timely, accurate, verifiable, and consistent with P66 business processes.  This presentation will discuss how Sigmafine is used to achieve this and the benefits derived.

Industrial IoT time-series data engineering – a layered approach to data quality

We will review the basic validation checks for missing data (I/O timeout), flat-line data (sensor malfunction), out-of-range data etc., and issues in source instrumentation/control system, network connectivity, faulty data collection configuration (scan rate, unit-of-measure, exception/compression specs) etc.  We will also cover advanced analytics, including machine learning and data reconciliation with illustrative use cases.

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