the journey - osisoft · defining the journey ... (mixed use class a, research, manufacturing) san...
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© Copyright 2018 OSIsoft, LLC 1
Find va lue locked
away in the da ta
T h e J o u r n e y
Scott Smith, Industry Principal Facilities and Data Centers
June 2019
© Copyright 2018 OSIsoft, LLC
▪ Defining the Journey
▪ Example Approaches
▪ Eli Lilly (Mixed Use Class A, Research, Manufacturing)
▪ San Leandro Tech Campus (Class A)
▪ UC Davis University (Mixed Use, Thermal Plant, Power, Campus)
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AGENDA
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Defining the Journey
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Today Future
Journey
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Today – Balancing Act
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Comfort/ Condition Requirements
ReliabilityEfficiency
Ongoing Projects
Resources
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Future - Defining
Predictive Analytics
Machine Learning
Self-Service
Integration
NetZero Resources
………….
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Journey – Starts with Data
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80%Facility Managers expect
the demand for data to be greater over the next 5
years*
58%
38%
57%
65%
*2018 Survey of 700 Facility Managers
Analyze performance data either upon failure, never or once a year
Analyze logs of system changes either upon failure, never, once a year or greater
Have not completed a cyber-security assessment
Have no plans for Smart Technologies
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Data Driven – First Steps of the Journey
Fault Detection Diagnostics
Condition Based Maintenance
Energy ManagementCyber-Security
Situational Awareness
CMMS
Cloud
Geo-Spatial
IOTSustainabilityAsset Management
Resilience
Automation
Reliability
Outsourcing
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CHALLENGES
AHEAD
Resources3
Costs2
OutsourcingFear of TechnologyLack of TechnologyResistance to ChangeLack of Awareness/Compelling EventMission Critical ValueShiny Object SyndromePrior FailuresOwner – Tenant Structure
(Cost vs Benefit)
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Today FutureJourney
Think Big – Execute SmallDefine Measurable ObjectivesFollow the Data
Packing for your Journey
Invest in ResourcesPrioritize Stakeholder Support
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Examples
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Business Need
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Monitoring
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Faults
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Results
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Efficiency in design
• Old HQ – 26 kWh Sq/Ft
• SLTC – 8.5 kWh/Sq/Ft
• Dynamic Window Tinting
• Neolith Tiles
• LED Lighting
San Leandro Tech Campus Project:1 M Sq Ft Mixed Use Development
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CHALLENGES SOLUTION BENEFITS
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▪ Design vs. actual
performance
▪ Failed equipment
▪ Inadequate or
missing
specifications
▪ Implement PI for
benchmarking the
HVAC, hot water
and window tinting
system.
▪ BACnet
▪ UFL
▪ PI Vision
▪ Found numerous gaps between the design specification and the actual system requirements.
▪ Failed or poorly installed equipment
▪ Programming errors
▪ Building design issues
Results
Problems with the real world - Issues they didn’t foresee
We allowed user overrides for temperature controls from 68 to 74 degrees
▪ No Global Reset was included in scope to the reset the building to target temperatures each night.
▪ Open floorplan and creating heating and cooling competition between VAV boxes.
▪ Reset to 73 degrees reduced complaints and comfort issues.
Post Commission Analysis
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CHALLENGES SOLUTION BENEFITS
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▪ Design vs. actual
performance
▪ Failed equipment
▪ Inadequate or
missing
specifications
▪ Implement PI for
benchmarking the
HVAC, hot water
and window tinting
system.
▪ BACnet
▪ UFL
▪ PI Vision
▪ Found numerous gaps between the design specification and the actual system requirements.
▪ Failed or poorly installed equipment
▪ Programming errors
▪ Building design issues
Problems with the new world - Issues they didn’t foresee
▪ Initially we allowed user overrides – but
that caused HVAC issues
▪ Individual window issues/override issues
▪ Initial IR sensor had issues with intermittent
cloud cover
How tinting should work
▪ 4 Tint Levels
▪ Follow the Sun
Single Pane of Glass
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CHALLENGES SOLUTION BENEFITS
19
▪ Design vs. actual
performance
▪ Failed equipment
▪ Inadequate or
missing
specifications
▪ Implement PI for
benchmarking the
HVAC, hot water
and window tinting
system.
▪ BACnet
▪ UFL
▪ PI Vision
▪ Found numerous gaps between the design specification and the actual system requirements.
▪ Failed or poorly installed equipment
▪ Programming errors
▪ Building design issues
Individual floors stopped responding to the pre-conditioning
The challenge
▪ 28% of the zones never make it to set point.
▪ The analysis highlighted fundamental issues:
▪ The user control option to 68 degrees is 2 degrees cooler than the design of the building allowed.
▪ Building pre-conditioned 1.5 hours prior to occupancy.
▪ Identified asset faults
Performance Monitoring – The Start of Machine Learning
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CHALLENGES SOLUTION BENEFITS
20
▪ Design vs. actual
performance
▪ Failed equipment
▪ Inadequate or
missing
specifications
▪ Implement PI for
benchmarking the
HVAC, hot water
and window tinting
system.
▪ BACnet
▪ UFL
▪ PI Vision
▪ Found numerous gaps between the design specification and the actual system requirements.
▪ Failed or poorly installed equipment
▪ Programming errors
▪ Building design issues
Individual floors stopped responding to the pre-conditioning
▪ Measuring Occupancy from a combination of sound and light
▪ Event Notifications when a user leaves a light on after the end of the meeting
▪ Measure utilization of conference room to assign a temperature set point specific to the demand of the room
IoT Sensors - $150 Portable Troubleshooter
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UC Davis: Meter to Meter Quality
• 1 Building is Useful
• Comparing finds patterns
• 2 Buildings Energy Balance
• 1 Building CHW does not follow pattern
• Meter issue
Outside Air Temperature [ºF]
Outside Air Temperature [ºF] Outside Air Temperature [ºF]
Outside Air Temperature [ºF]
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UC Davis: WIFI To Schedule
• Compare WIFI to Schedules
• Identify Schedule Savings Opportunities
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UC Davis: ∆T
• Identify ∆T for each building
• Identify load and flow use
• Identify targets based on value
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Summary
Today FutureJourney
• Only you know your challenges – Solution fits your need /not fitting your facility to their functions
• Small measurable objectives – Finding value• Follow the Data
© Copyright 2018 OSIsoft, LLC
Scott Smith
Industry Principal, Facilities and Data Centers
OSIsoft, LLC
25
© Copyright 2018 OSIsoft, LLC