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BigData’sImpactonFacilitiesOperations
DonGuckert,P.E.,APPAFellowTheUniversityofIowa
“If the rate of change outside your organization is greater than the rate of change inside your organization, the end is in sight .”
Jack Welch – former CEO of General Electric
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WhatisBigData?
WhatisBigData?
Banking
It takes only seconds for banks to find out if someone else has used your credit card. So much big data in this industry has been collected and utilized and in such a powerful way that computer software can now instantly detect suspicious activity and block it in real‐time.
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WhatisBigData?
Online Shopping
Ever notice how the ads on your browser are similar to something you just bought or just looked at buying? You can thank big data for that one. Big data is also responsible for any “Recently viewed items” or “Featured recommendations” you might find on websites. This allows companies to target customers with ads specifically for them.
WhatisBigData?
Netflix
Netflix is the largest provider of streaming video in the U.S.. It has also become a sponge for data—what users watch, when they're watching, where they're watching and what device they're using. It has data on when you rewind or fast‐forward, when you pause and when you stop watching a show or movie entirely. Now Netflix is beginning to produce its own original programming and it's leveraging all that data to do it.
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WhatisBigData?
Driverless Cars
WhatisBigData?
Merriam‐Webster's Collegiate Dictionary added Big Data in 2014….
Big Data
• nounDefinition of BIG DATA
• : an accumulation of data that is too large and complex for processing by traditional database management tools
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WhatisBigData?
Industry Definition:
High volume, high variety and high velocity of information assets that demand cost effective and innovative forms of information process‐ing for enhanced insight and decision making.
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Velocity(speedofchange)
Moore’s Law: an axiom of microprocessor development usually holding that processing power doubles about every 18 months.
Volume(datasize)
Capacity to store data is growing exponentially …doubling every 40 months since 1980.
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Variety(datasources)
Variety(datasources)
It is expected that the global Smart Building Market will grow from $7.3 billion in 2015 to $36.4 billion by 2020.*
The campus built environment is mirroring, and even outpacing, the overall national trends in both big data growth and the investment in intelligent buildings.
*source: MarketsAndMarkets
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Variety(datasources)
Air Handler performance
• Fan Runtime• Fan Power• VFD Control• Static Pressure• Heating Control• Cooling Control• Ventilation Air Control• Economizer Control• CO2 control
• Outside Air Temperature• Return Air Temperature• Make‐up Air Temperature• Supply Air Temperatures• Freeze Stat Alarms• Smoke/Fire Alarm• Pressure Drop Alarm
SoWhat?
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BenefitsofLeveragingBigData
Business Intelligence: Understand what has happened in the past.
In‐memory Processing: Understand what is happening now.
Predictive Analytics: Understand what will probably happen.
BenefitsofLeveragingBigData
Business Intelligence: Understand what has happened in the past.
In‐memory Processing: Understand what is happening now.
Predictive Analytics: Understand what will probably happen.
All three processes require intense data collection in order to make accurate predictions based on the past, present and presumably the future
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BigData&PredictiveAnalytics
Understanding what has happened in the past, happening now, and what will probably happen is foundational for predictive analytics.
BigData&PredictiveAnalytics
Understanding what has happened in the past, happening now, and what will probably happen is foundational for predictive analytics.
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BigData&PredictiveAnalytics
Hot/cold calls often lag by hours or days of a system failure. With predictive analytics we’ll see it and fix it, or avoid the failure altogether, before the occupant feels it.
ManagingRisk
Predicting impending failure, and preventing that failure, mitigates risks to business continuity and financial risk.
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InvestingversusSpending
The dollar outlay shifts from productivity losses, repair costs and wasted energy to investments in infrastructure and technology and active monitoring.
TheUniversityofIowa’sJourneyintoBigData
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EnergyControlCenter
EnergyControlCenter
In 2009 the Energy Control Center was established, serving as a central information center to view all that was happening in energy production, distribution and consumption.
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EnergyControlCenter
Business Intelligence: Understand what has happened in the past.
In‐memory Processing: Understand what is happening now.
Predictive Analytics: Understand what will probably happen.
Original vision was to use the central center to monitor and analyze building systems in support of field operations.
Realized the system to do much more.
MonitoringBuilding
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BuildingSystemsOptimizationHub
Commissioning
Optimization begins with Commissioning.
The success of our retro‐commissioning and re‐commissioning efforts have revealed the drift our systems experience over time.
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ContinuousCommissioning
a.k.a. Monitor‐based Commissioning
Our new building commissioning programs and retro‐commissioning efforts are now being viewed as precursors to a continuous commissioning mode.
ContinuousCommissioning
By establishing operating parameters for commissioned or recommissioned buildings systems, we can manage systems drift.
Degradation of energy performance is avoided – and operational performance is maintained.
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ContinuousCommissioning
Microsoft Smart Buildings White Paper 11/2011
Continuous Commissioning Benefits (Illustrative)
FaultDetection&Diagnostics
Iowa’s journey in pursuing continuous commissioning led us to Fault Detection & Diagnostics.
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FaultDetection&Diagnostics
FDD is a software TOOL used to PROACTIVELYdiscover building system problems and identify optimization opportunities BEFORE they lead to alarms, excessive waste of resources, occupant discomfort or system failure.
Big Data Information Decision Action
Software Tool Facilities Management
RespondingtoFaults
Faults are categorized and prioritized and then responded to accordingly:
• Does the fault indicate a threat to health and safety?
• Does the fault threaten mission critical functions?
• Does the fault reveal an ongoing expense?
• Does the fault impact performance?
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RespondingtoFaults
20BuildingsAcademic, Lab, Office, Recreational, etc.
49,000 Points
5 min interval collection
All Major HVAC Equipment
AHUs, HW/CHW Systems, Pumps, VAVs
4 Building Automation SystemsAndover Continuum, Schneider StruxtureWare, JCI Metasys, Pi OPC
Initial pilot at major lab building helped to identify strengths and
shortcomings before larger roll out.
FDDImplementation
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SystemLevelAnalytics
Analytics must accurately handle unique sequences and automatically find opportunities in addition to problems:
Opportunity: The economizer lockout temperature is Lower than necessary, causing the economizer to lock out while partial free cooling is still available
Suggested Action: Raise the economizer lockout temp to within a couple degrees of the return air temp. If the lockout was reset to 73 degrees, 2 degrees less than the avg. return temp 75 degrees, the air handler could save 2661 kBTU’s and $799 of wasted energy during the last month
SystemLevelAnalytics
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System Level Analytics
By Looking at systems as a whole, analyses can identify opportunities to improve efficiency
SystemLevelAnalytics
Automated Text Output Directs resolution: On average each day, the air handler was occupied for an excess of 17.4 hours and running for an excess of 17.4 hours during times when all zones were unoccupied
Analytics bring prioritized insight into dozens of zones at once
SystemLevelAnalytics
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The operator generates a task in Clockworks, which generates a
work order in CMMS
Notes entered in Clockworks are pushed to the work order description within the CMMS
WorkOrderIntegration
FDD activities are now captured in the CMMS in order to illustrate impact and indicate time and resource needs.
WorkOrderIntegration
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BigDataChallenges
Connected infrastructure
Overcoming cultural entrenchments
BigDataChallenges
Connected infrastructure
Overcoming cultural entrenchments
Workforce readiness
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BigDataDrivenMegatrends
“If the rate of change outside your organization is greater than the rate of change inside your organization , the end is in sight .”
Jack Welch – former CEO of General Electric
BigDataDrivenMegatrends
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BigDataDrivenMegatrends
From operations expenses to capital investments
BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
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BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
From component diagnostics to systems diagnostics
BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
From component diagnostics to systems diagnostics
From systems drift to systems hold
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BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
From component diagnostics to systems diagnostics
From systems drift to systems hold
From reactive response to predictive response
BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
From component diagnostics to systems diagnostics
From systems drift to systems hold
From reactive response to predictive response
From institutional knowledge to shared knowledge
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BigDataDrivenMegatrends
From operations expenses to capital investments
From mechanics to technicians
From component diagnostics to systems diagnostics
From systems drift to systems hold
From reactive response to predictive response
From institutional knowledge to shared knowledge
From valuing expertise to valuing collaboration
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Don Guckert Alex GraceAssociate Vice President VP Business [email protected] [email protected] 978-502-0658