Præsentation fra PCTY 2012 v. Claire Penny

1. Smart Buildings
A smarter way to manage real estate and
facilities
Optimizing the World’s Infrastructure
22nd May 2012, Copenhagen
Claire Penny
© 2012 IBM Corporation
© 2011 IBM Corporation

2. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

3. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

4. It’s time for change
It is clear that there is an immediate requirement to significantly and urgently
change the way buildings are managed.
Businesses need to “…prepare for this century, not the last. Turning the oldest
building stock in Europe into the most improved, with a nationwide commitment to
energy efficiency”.
UK Secretary of State for Energy & Climate Change, 2011 Annual Energy Statement 1
“Efficiency means less costly waste”
President Obama at the “Better Buildings Initiative” launch which aims to make US commercial buildings
20% more efficient. The purported impact of the initiative is a reduction US companies’ energy bills by
about $40 billion 2
1
http://www.decc.gov.uk/en/content/cms/news/aes_2011/aes_2011.aspx
2
http://www.good.is/post/better-buildings-initiative-and-innovation-cluster-announced-by-president-obama/

5. Smarter Buildings – who should care?
 Companies with:
• Over 1 million sq. ft. of real estate
• Energy reduction targets
• CO2 reduction targets
• OpEx reduction targets

6. Challenges
 Properties operating as silos  Difficult to identify true full cost
of systems and data of operating a property
 Too many business processes  Disparate building management
require manual intervention systems
 Difficult to determine the value  Rich data is often unexploited in
of FM services pursuit of business efficiency
 Loss of corporate knowledge  Disparate facilities providers in
to 3rd parties soft and hard services
Real estate & facilities functions NOW have an opportunity to
drive strategic business value

7. What are smarter buildings?
Smarter Buildings are well managed, integrated physical and digital infrastructures that
provide optimal occupancy services in a reliable, cost effective, and sustainable manner.

8. Evolution of a smarter building
Value
Gain greater control Build more effectiveness Achieve a smarter
over your facilities data, into your operations across buildings strategy to
systems, people and the lifecycle of facilities generate higher returns
processes. assets. on facilities assets.
 Increased productivity  Improved decision-making  Automated real-time response
 Improved compliance  Mitigated risk  Predictive analytics
 Historical analysis  Real-time analytics  Institutionalized controls
 Reduced cost  Increased return on  Increased return on assets
investments
Maturity

9. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

10. IBM solutions for smarter buildings
ENERGY SPACE OPERATIONS
OPERATIONS R.E. INVESTMENT PLANNING

11. Energy
Real time monitoring of building and data center equipment; reduces
energy consumption and waste over the lifecycle of the building and
increases facility performance in a sustainable manner.
IBM Intelligent Building Management
Continuously collect measurements,
correlate and analyzes data to detect energy
optimization opportunities and to predict
potential failures.

12. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

13. Managing the data
Fire Functionality
Energy Checks,
Smart Meter, Detector Service
Portfolio Demand Response Elevators
HVAC
RE Mgmt Maintenance,
Fans, Variable Air
Performance
Volume, Air Quality
Weather
Asset Mgmt Current
Water
Lifecycle Smart Meters, Predictions
Use / Flow
Sensing
Energy Use
Passive/Active Emergency
Services
Analytics and Optimization
Building Services Alerts, Actions
External Integration
Maintenance/Projects
Lighting
Occupancy Occupancy Utilities
Space Mgmt Sensing Demand Mgmt,
Cost Control
Tenant Services Access/Security
Help Desk Badge In, Community
Cameras, Integration
Perimeter, Doors,
Services
Waste Mgmt Floors, Occupancy Transportation,
Trash/Water/Recycle Traffic, Events
24/7 Monitoring Space Utilization
Condition Monitoring, Occupancy/
Compliance Management
Real Estate Mgmt
Parking Lot Utilization Commercial
Potential
Advertisement
Industry Specific
Hospital, Hotel, Etc.

14. Managing Buildings Smarter: Solution overview
Advanced operational & energy analytics which:
• Uncover previously hidden systemic operational and energy use
malfunctions and inefficiency (waste)
• Drive down operational costs and energy use
• Continuously monitor and improve performance
Provided through near real-time data collection, event enrichment and
automatic work order/ service request generation.
Takes existing large amounts of data:
• Transforming it into intelligent & interconnected actionable information
Enabling end users to:
• Ensure reliability
• Reduced maintenance costs
• Reduced energy costs

15. Energy and maintenance management
Data Sources
Enterprise View
Meter
Real Time Collection Processes
Enterprise Energy Metrics Energy Analysis view
Energy Building
management management Databases
Systems Systems IBM Intelligent Buildings
Real time energy tracking
Performance base
Buildings monitoring
Energy & Operational
analytics
Maintenance management Automated Work
Route cause analysis Orders
Energy systems integration

16. Smarter buildings require continuous improvement
Instrumentation Complex,
inter-related
data sets
provide new
insights
Enables
collection of
large data
sets
Reports
Deliver and
maintain best Transform
practice, current
efficiency and practices
cost reduction
16

17. Performance Management - Using the data
Business rules alert when equipment is operating sub-optimally
AHU Cooling
Valve Passing - AHU Simultaneous
Leakage Heating & Cooling
Detection
AHU Heating AHU in Override mode
control issue for 2 or more
(Valve) consecutive hours
AHU Economiser AHU Cooling Control
Mode Alert - Not in Alert - High Building
Free Cooling Mode Zone Temp

18. Example of compressor performance monitoring
Perform performance based maintenance instead of timed maintenance
 Level 1: Monitoring
Enable telematics, collect data , set thresholds,
generate alerts and create work orders
 Level 2: Proactive Analytics
Run analytics on telematics data to identify
anomalies such as compressed air leeks – feed
directly to work orders
Tune devices for energy management
 Level 3: Predictive Analytics
Run analytics on telematics and compare to
statistical data and make predictions about
potential failures.
Run analytics on warranty and service data.
Predict maintenance based on unit usage and
conditions.
 Level 4: Diagnostic Tool

19. Typical compressor data points
MotorOil Discharge Air
Cooling WaterTemperatureLow
Oil Cooler Stage-3 Temperature
Inlet Stage-2 Scan Time Alarm/Trip Trip (Alarm) Alarm
Package Temperature
Vibration Pressure(Alarm) Temperature High
Discharge Differential Pressure
LubeStage-3 Air Flow Temperature
System pressureTemperature Sec
ParameterStage-1 Airpressure Cooler Reporting SMS
FilterStage-1
CurrentTrip
stage-3
stage-2
Water
AirDaily
Stage-2
Yes
Flow
Discharge 5min
Inlet 30
Daily
Immediate Yes
after Immediate Yes
5min Trip

20. IIBM Dashboard Views
IBM Internal dashboard
EuroGreenIT
Energy Contractor

21. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

22. Case Studies: Solution value proposition
IBM Rochester, 3.3M sq ft multi-building mixed use light industrial
campus. Facilities date to the 1950s. Consistently achieved year on
year energy reductions of 5% to 7% over the last 10 years.
• Reactive maintenance decreased by 16%
• Hours per work order reduced by 34%
• Total number of work order hours decreased by 49%
• Energy cost reduction on equipment monitored of between
Rochester, MN 10-15%
In the wake of Hurricane Katrina’s destruction in 2005, Tulane
University saw an opportunity and a responsibility to advance
campus-wide sustainability and energy efficiency.
• Significant reduction in energy cost since the system was
installed
• Tulane can collect, manage and analyse data from buildings
to gain intelligence and insight to energy and facilities
Tulane University
management.
A global life sciences company recently completed a PoC, in their
tightest controlled building environment. The findings were therefore
Global life sciences
based on the best case scenario within Client A’s buildings.
company • Energy savings benefits from PoC are estimated to be c. EUR
57,000 pa.
• Equates to a decrease in energy costs of up to 14% for some
assets.
.

23. Project EuroGreenIT – Public Sector Buildings
(Belgium)
Euro Green IT partnered with IBM and Dapseco
(energy optimisation consultants) to deliver an IBM
Intelligent Building Management proof of concept to
five public sector buildings (schools) with little to zero
instrumentation. 5 buildings in the pilot project (3 schools
/ 30000 m², 2 administrations / 9000 m²)
Savings example
Heating too
early

24. Client Project Tulane University/New Orleans
(USA)
Goal to solve building shortcomings with the most effective
and energy efficient approach.
• 100 year old Richardson Memorial Hall
• Connect existing systems to collect metered data
• Use advanced analytics to gain insight in building
condition
• Bring together disparate data to drive better
decision making
• collection and analysis of heating, air conditioning,
electric usage, and water consumption
Results: Energy Savings
Pre-
IIBM
Post-IIBM

25. Client Project Energy Performance Contracting
(UK)
Monitoring and analysis for performance
contract
- Monitoring SLA performance
- Monitoring Asset Performance
- Monitoring energy production/CO2
- Data trending

26. IIBM Results: Maintenance savings
AHU Work Order Numbers & Hours Average Hours Per WO
200%
150%
- 34%
100%
-
16%
50%
Ave Hr/WO
0%
Prior Yr Qtrly 4Q10 1Q11 2Q11 3Q11
Ave
-50%
- 49%
-100%
# of Work Orders Work Order Hours Pre IIBM Post IIBM
Observed reduction in WO numbers and WO hours for reactive maintenance
1680
1800 1412
1600
34% = 480
1400
16% = 67 932 0.5 headcount - £32.5k
1200 4hr per WO
1000 4hr per WO
800 420
600 353
ASSUMPTIONS:
400 • Available service 1,736 hrs
200 • £65K per headcount
0
# of WO Old Hrs # of New WO # of New WO New Hrs
w Old Hrs

27. AHU preventative maintenance work order
history & productivity - Example
Predicted Preventative Maintenance WO hours for AHU
600
500
400
300 1.7 hrs per WO 560
50% = 280
0.2 headcount - £13k
200 320 280
100
PM
0
# of WO Old Hrs New Hrs ASSUMPTIONS:
• Work Order quantity remains constant
PM • Available service 1,736 hrs
•£65K per headcount
(Hypothetical Data)
Client specific data & savings
estimates required

28. Areas of Future Opportunity
All Other Classes
Shop Equip
Plumbing
Fans
CRAC
Fire Prot. Alarm Future Savings Opportunities
Manual Door
driven by:
• New Rules &
Kitc hen
• Wireless Sensors
Elec tric LV
Pump
Determine Number of
Comp. Air
Hours Covered by solution
Chiller
Condensate Rec .
Rest Room
Arc hitec tual
Lighting
AHU
W O Hours
Analytic Opportunity
Expanded Smart Building Analytic Opportunity / 30% of Total Work Order Hours

29. IIBM Results: Operational Energy Savings
Rapid Savings: Small sample of results for the first month for Phase 1
IBM Internal Examples
SAVINGS
ALERT ACTION
YR-1
AHU simultaneous heating  Created program to keep AHU’s from heating &
$3k
and cooling cooling at the same time
Variable speed drive  Replaced damaged duct work
running fan at 90% capacity $10k
 Repositioned sensor
for more than 2 hours
 Control panel software failure prevented AHUs from
3 AHUs running outside turning off at normally scheduled time $18k
scheduled hours
 Performed cold start on panel to clear problem
Electrical current detected  AHU had been manually set to run constantly
when AHU is supposed to  Reset to cycle on and off as dictated by the central $19k
be in off mode control system
Expected Savings: 10% - 15% Annual Saving For Equipment Covered By Analytics

30. IIBM Typical Energy Savings Results
Equipment Not on Automatic Schedule
Energy Consumption Exceeds Spec 2% Savings
2.5% Savings
KWH Usage
Usage
KWH
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
01
03
05
07
17
19
21
23
09
11
13
15
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
:00
05
15
21
01
03
07
09
11
13
17
19
23
Unit Performance Operational Baseline
Unit Performance Operational Schedule
Dual Energy Savings Opportunity
Steam Leak
Chilled Water & Steam 3.5%
AHU Air Flow Temp. Delta
Identified
15
Savings
5
-5
-15
-25
-35
0
0
0
0
0
00
0
00
0
0
0
0
00
0
0
0
00
0
0
0
0
0
0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:0
:
:
:
:
02
03
07
11
12
13
16
17
21
22
01
04
05
06
08
09
10
14
15
18
19
20
23
Actual Normal Operation

31. Value add to your existing building management
system(s)
Integration
Work order generation
Rules programming
Data
Analytics/Rules Security
Event Management Existing Clients
Performance Operational support
Maintenance Services

32. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

33. Why IBM for smarter buildings?

34. Why IBM for smarter buildings: one year payback
Factors that will influence site-specific results:
 Implementation cost:
– Level of existing instrumentation
– Building Management System sophistication
– Work order logistics system
– Skilled staff availability
 Benefits:
– Maintenance productivity
– Equipment efficiency levels
– Depth of implementation
– Type of space (office, data center, etc.)

35. Managing Buildings Smarter: Summary
Individual Building Performance
Deliver better building performance for all stakeholders
 Increased reliability
 Automatic work order generation based on multiple point near real-time
data collection
 Legislative compliance
 Identify, track and sustain energy reduction
 Reduced maintenance costs
 Reduce the number of work orders and work order hours
 Continuous performance based monitoring
 Ensuring that equipment is always performing optimally
 Effective asset management
 On-going work order history for each asset
 Defer capital projects
 Efficacy of each asset clearly understood
 Reduced energy use & costs
 Energy reduction opportunities through performance based monitoring

36. Agenda
 Smarter buildings overview
• Drivers
• Who should care?
• Real estate management challenges
• What are smarter buildings?
• Smart building evolutionary roadmap
 What IBM offers
• Smart Building portfolio
 IIBM – Energy and maintenance optmisation
• How it works
• Example
• Dashboard views
 Smarter buildings benefits
 Why IBM?
 Summary
 Next steps: call to action

37. Next steps
Ready to embrace change, strategically manage and optimize your real estate
portfolio?
Do you want to drive down your real estate portfolio costs?
Do you want to know which are most efficient and highly utilized buildings?
Do you want to know when your buildings are underperforming?
If so, our next steps are:
1) Decide on a focus area, could be number of buildings or IBM capabilities
2) Deploy the solution – reap the rewards
37

38. Thank You and Q&A
Smarter Buildings: a smarter way to manage real
estate and facilities
© 2011 IBM Corporation