Implementing Sigmafine in Water & Utilities
Water is an essential, life sustaining resource everywhere in the world, and the systems that produce and deliver water are critical, capital-intensive infrastructures with unique operational challenges. Some of those challenges include:
- Sustaining water quality
- Producing and delivering water to meet demand
- Improving water conservation and reuse
- Minimizing energy consumption
Meanwhile, the industry as a whole continues to be challenged to:
- Do more with less
- Extend the life of aging infrastructures
- Improve public safety and water system reliability in the face of growing demographic pressure, extreme weather events, and growing water stress worldwide
To rise above those operational and business challenges, the industry is making better use of data to accomplish three goals:
- Enhancing operational understanding through analytics
- Developing insight into a predictive capability
- Automating actions to achieve reliability and predictability
The result is smarter operations, smarter plants and smarter systems that can take industry challenges head on.
4-Step Process to Improved Data Integrity
This transformation begins with organizing data into a clean, usable dataset that can be trusted by people, systems and business process – a core value proposition of Pimsoft’s Sigmafine technology. Sigmafine pulls together disparate data types (operations, inventory, quality, energy and utilities consumption, chemicals and catalysts usage, material movement including receipts and shipments) into an integrated model that is solved continually. The result is a validated, trustworthy operational dataset ready for use by:
- People in operations management, planning and scheduling, business, financial control, energy management, environmental control, etc. for decision making and redirecting business and operations
- Applications that require validated data to perform optimally
- Business process that depend on trustable data to achieve their targeted outcome
Improving data quality and usability in the water and utilities industry is accomplished in four steps:
- Identify the business scenarios and associated applications that have low tolerance for bad data or unusable data.
- Construct a data model that is representative of the desired application. This step involves determining the inputs and outputs, the relationships between assets, and the calculations required to estimate the dataset’s consistency and accuracy.
- Collect inputs and outputs, run and solve the model. This step identifies data issues and proposed corrections to achieve the best dataset.
- Run this process according to the frequency requirements of the applications (minutes, hours, shifts, days, weeks, etc.). The initial runs are often a discovery, but over time, data issues diminish and the process is automated. The KPI becomes keeping the data quality index estimated by Sigmafine within the tolerance level of the applications.
Sigmafine can deal with a wide range of model sizes and complexities to support specific applications as well as global facilities and distribution network datasets. The main applications supported by the resulting model include:
- Water and energy balancing, including water stock management
- Suspect meter identification
- Leakage estimation and monitoring, including loss calculations (ILI)
- Fiscal and/or commercial reconciliation of water, energy, and other utilities exchanges through third-party interconnections
- Data validation for compliance reporting
- Gross error detection
- Closed loop business process integration with ERP for cost allocation, performance reporting, etc.
The Benefits of Improved Data Quality
The direct benefits of improved data quality in the water industry include:
- Reduced water losses
- Reduced energy and utilities consumption
- Improved cost allocation accuracy
- Improved billing
The indirect benefits include:
- Improved loss avoidance by identifying bad meters early on
- Reduced time to decision due to data validation automation
- Reduced risk due to an improved dataset with quantifiable quality
- Deferred capacity increase investments due to more optimal operations
Reference Sigmafine Implementation
Customer: Instem Beaver Valley by Rexsoft
Used for: Improving data quality used in water balance, leakage estimation, meter analysis, and compliance mandates
Benefit: Improved process knowledge, leakage reduction, and pricing accuracy; benefits totaling $3.8 MM