The business model and context of each organization is unique but the rationale for improving operational data quality is universally the same: ensuring the integrity and reliability of all business processes that have a dependency, direct or indirect, on operational data and sustaining this capability over time through the meanders of change.
Consistent decisions and business process execution demand the best possible operational data and information at all times when dealing with planning, scheduling, supply chain, make or buy decisions, restocking, value add maximization, loss reduction, economic and operational performance improvement, etc. In other words, when the mission is critical, Data Quality matters.
Implementing Sigmafine® will maximize the accuracy of data and improve the usability of operational information which will create a noise free and data driven decisional and business execution environment and avoid the hidden cost of uncertainty and inconsistent decision and business process.
The benefit model of Sigmafine(r) (Figure 1) addresses a) the avoidance of economic downside due to poor data quality, b) the sustainability of actionable and trustworthy data and c) creates potential for upside realization through better usability of operational data, fit for business, timely and noise free.
Sigmafine® is an PI AF application running as a standalone AF Server processing mass, volume and energy flows along with their associated physico-chemical attributes (temperature, pressure, composition), according to rules defined in models by users. The output of the process is a reconciled data set corresponding to model, a balance and a time period. The reconciliation is based on the laws of conservation of mass and energy.
For each relevant input data streams from the PI System, Sigmafine publishes back to the PI Data Archive its corresponding reconciled values. The aggregation of all the input and reconciled streams generates cases which are the transformation of time domain data into period summaries and business context.
Sigmafine® data and models can be consulted and analyzed using PI ProcessBook, PI DataLink, Sigmafine Excel Add-in, PI System Explorer, PI Coresight and PI WebParts. Case Data are accessed using Sigmafine SQL Access, Sigmafine Reporting Package and the Intelligent Material Movement (IMM) application of Pimsoft. Sigmafine® can run automatically or on demand, based on periods matching the business requirements (hourly, by shift, daily, weekly, monthly).