This presentation 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.  It will also cover advanced analytics, including machine learning and data reconciliation with illustrative use cases.

Recorded October 22nd, 2020
At the Sigmafine Virtual Summit

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

Data quality is a foundational prerequisite for data engineering in your digital transformation and data science/machine learning initiatives.  Join us in this session for a “how-to” on getting started and implementing a layered approach to data quality with the PI System, such as:

PI System Monitoring
Simple analytics to validate (individual) sensor data streams
Simple analytics to validate at an equipment level (several related sensors)
Advanced (multivariate/machine learning) analytics to validate at a functional equipment group (FEG) level - tens or hundreds of sensors
Advanced (connectivity model-based) analytics - data reconciliation with mass/energy balance (one or more process units)

Whether it is an individual sensor (pressure, temperature, flow, vibration, etc.) an individual piece of equipment such as a pump (with a few sensors), a functional equipment group (FEG) i.e. a feedwater system (made up of a group of equipment like motor/pump/valve/filter/pipe assembly), or an entire process unit or a plant – the scope of data quality requirement has to be understood in its usage context.  And, with streaming industrial sensor/IoT time-series data, a layered approach to data quality gives you the flexibility to apply fit-for-purpose techniques mapped to use case requirements.

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.

About OSIsoft

With the explosion of data, it is no longer efficient or cost-effective to use conventional methods for accessing silos of data. It takes the PI System to connect disparate sources of sensor-based time-series data and deliver the right information to the right people at the right time in the right context.

Through a single infrastructure, companies can transform their business.

As businesses expand into sensor-enabled equipment, more assets are streaming more data – increasing the need for and value of the PI System.

OSIsoft has installations in 127 countries and is widely used across manufacturing, energy, utilities, pharmaceuticals, life sciences, data centers, facilities, and the process industries, as well as the public sector and the federal government. OSIsoft is headquartered in San Leandro, California, with offices around the world.

About Pimsoft

Pimsoft is the owner & maker of Sigmafine, an enterprise-wide solution for improving the reliability of business processes through better data fit for use at all times.

The mission of the Sigmafine team is to generate value for our customers by ensuring the continued accuracy and usability of their process and manufacturing data so that their data can be fully trusted for decision and action. Pimsoft brings innovative software solutions and engineering skills to industries where data quality and usability is mission-critical in shaping information for action and decision. With its offices in Turin, Milan and Rome, Italy, and Houston, Texas, Pimsoft maintains the largest contingent of skilled and experienced IT and Engineering professionals in this application domain.

At the core of Pimsoft is expertise in process and manufacturing know-how applied to data curation and governance. We ensure the successful implementation and application of Sigmafine to support operational, business, and compliance mandates of the enterprise.

Gopal GopalKrishnan, P.E.
Solution Architect
OSIsoft LLC
gopal@osisoft.com

Gopal GopalKrishnan has held several roles at OSIsoft and has been working with the PI System since the mid-1990s in software development, technical and sales support, and field services. Attached to the Philadelphia office, he is currently a Solution Architect in the Partners & Strategic Alliances Group. Previously, he was a Product Manager with a focus on Enterprise and Asset Integration and PI Data Access.

Gopal has a master's degree in Engineering, continuing education in business administration, and is a registered professional engineer in Pennsylvania. He is also active in the MESA Technical Committee and the MESA Continuous Process Industry Special Interest Group, and active in topics such as data mining, data science & machine learning, energy efficiency, manufacturing intelligence, sustainability, including green initiatives in facilities and data centers.

Bernard Morneau
Business Development
Pimsoft Inc.
bernard.morneau@pimsoftinc.com
+1 (415) 349-1281

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