Transforming Data into Digital Assets
Sigmafine is a model-driven advanced analytics software solution that validates and reconciles data as well as streamlines and automates the process of generating usable datasets for people, business processes, and other applications and systems.
Sigmafine combines knowledge, engineering principles, and statistics to maximize the quantity, value, and quality of information extracted from disparate data sources and sensor-based data regardless of the industry or the applications.
Sigmafine is an enterprise-class software for process and manufacturing industries that Transforms Data into Digital Assets.
Span of Application
Sigmafine is fully scalable and can range from a simple unit operation to a production unit, an industrial plant, a business unit, a utility transmission, and/or a distribution network.
Scope of Application
Sigmafine can address the requirements of multiple applications in the process industries: production accounting, mass & energy balance, composition, property & cost tracking, yield & loss accounting, inventory management, and/or performance monitoring. (see industry solutions)
- Data reconciliation analyses: mass, volume, energy, and component balance
- Tracking: materials, ownership, and material qualities
- Asset-based relational database with an open architecture based on MS SQL Server and the OSIsoft PI AF
- Web client interaction
- Seamless integration with industry-standard data historians, planning and scheduling systems, movement systems, ERPs, and Business Intelligence platforms
- Extensible with industry or customer-specific add-ons
- Scalable from small to very large models involving several thousands of assets
- Able to run on arbitrary time frames
- Fully auditable across the data workflow
- Produces balanced results which are suitable for business and operational use
- Minimize errors that can have a downside economic impact on operations, decision making, analytics, and KPI calculations
- Can detect defective meters and analyzers and effectively support a condition-based maintenance program for these instruments
- Easily fit in existing infrastructure or as a value enabler in a digitalization initiative
- Can support financial audits
- Can be used as a validation layer to build enough accurate dataset feeding AI/ML software
- Maximizes accuracy and precision
- Minimizes uncertainty
- Delivers validated data for integrity
- Reconciled data for consistency
- Organized data for ease of use
- Shared data for collaboration
- Save time for decision making