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Customer Story

DSA leverages value from the PI System data at the University of Maryland, College Park

facilities-of-university-of-maryland
  • Challenge
    Channel high-quality data from multiple disparate systems to a centralized and accessible location.
  • Solution
    Use PI System algorithms to connect data to existing infrastructure, allowing for the timely transmission of accurate information to relevant stakeholders.
  • Benefits
    Reduced operational downtime and used it more efficiently, leading to more preventive maintenance and time and money savings.

The University of Maryland, College Park is a global leader in research, entrepreneurship, and innovation. Electrical distribution across the multi-building campus is complex. Important electrical distribution data exists in multiple, disparate, and isolated systems across a large facility space, making it difficult to harness data and promptly and effectively put it to use. The university turned to Data Systems Analysts, Inc. (DSA), an IT consulting company, and the PI System to support the university’s objectives of improving critical systems and making facilities smarter by translating data into action.

You really can’t assess the complete operation of a large system unless you have all of the data in one place.
Eoin O’Driscoll
PhD, PE, CEM, Critical infrastructure protection, practice lead at DSA

Harnessing the right data at the right time

DSA used the PI System to collect critical data from isolated systems and centralize it in an operations data warehouse. DSA could then visualize real-time data within PI Vision, a tool that can be easily and securely accessed remotely. PI Vision provides critical information that assists operators when presented with challenges, such as electrical outages or issues with generators and on/off switches. This level of end-to-end transparency has improved the university’s ability to respond to outages and significantly reduces downtime when outages do occur. In this way, without changing any instruments in the field, DSA can create situational awareness by collating the data to one central location. DSA applies analytics to the gathered data to improve operational intelligence, which provides new and improved logic-based FDD rules, best practices, and machine learning. As a result, DSA helps the University of Maryland ensure that new intelligence makes its way to the right people at the appropriate time.

The PI System allows DSA to continuously provide critical information to troubleshoot any potential electrical issues on the campus. For example, when an electrical outage occurs, there are notifications built into PI Vision dashboards that immediately alert all of the appropriate utilities and engineering stakeholders. According to Dr. Eoin O’Driscoll, critical infrastructure protection practice lead at DSA, “one of the most time-consuming tasks when responding to any outage is collecting and sharing information.” Within the PI System, data gathering and communication are automatically translated through repeatable templates, and notifications are generated in the event of any issues. In this way, remote access to PI Vision forewarns maintenance teams, improves facilities’ ability to respond to outages, and significantly reduces downtime when outages occur.

Overcoming data gaps with the PI System

Although the collection and distribution of data from complex facilities is crucial, no building or campus has perfect data quality. However, even with inconsistent data, it is still possible to harness the benefits of analytics performed within the PI System. When there are data gaps or data quality is poor, the best approach is to leverage the known correlation between variables. This approach is done through regression analysis and pattern matching from historical data recorded within the PI System. Even if a building automation system (BAS) is in place, native automation systems simply do not have the analysis capabilities that exist within the PI System. Once data is rebuilt and analyzed using this model, operations engineers at facilities can predict consumption, allowing for more informed decisions around equipment scheduling and maintenance planning.

facilities-graph-university-of-marylandDSA uses the PI System to connect the university’s IT and OT systems, garnering a 30% HVAC energy savings for the university.

The PI System and data-driven maintenance

Scheduling projects is one of the most cost effective improvement measures within a given facility space. While working on a research facility air handler at the University of Maryland, College Park campus, DSA aimed to avoid unscheduled downtime as much as possible. Through monitoring vibration signals and referencing vibration standards within the PI System, DSA created a spectrum of acceptable vibration velocities. This capability provided advanced warning of any mechanical issues. From the analytics in place, DSA identified a shaft alignment issue that was causing excessive wear on the bearings. Over time, this issue would have persisted and caused an unscheduled downtime. Instead, the university scheduled maintenance work to address this issue, contributing to the ultimate goal of maximizing uptime.

According to O’Driscoll, when it comes to facility maintenance, making the connection between IT and OT systems is at the core of any smart building. DSA has successfully made this connection with the PI System. The university can now pull data from cloud-based room reservation services, bring it through to the PI System, and then send commands from the system to the building automation systems. This important connection has led to a 30% HVAC energy savings. O’Driscoll said, “This is a really powerful example of how connecting different systems can improve facilities operations and generate significant cost savings.”

For more information about University of Maryland and the PI System, watch the full presentation here.

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