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April 16, 2012 Ray Miciek VP Smarter Building Strategies.

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Presentation on theme: "April 16, 2012 Ray Miciek VP Smarter Building Strategies."— Presentation transcript:

1 April 16, 2012 Ray Miciek VP Smarter Building Strategies

2 REAL ESTATE EXECUTIVES OPTIMIZE ACROSS TWO DIMENSIONS  Strategic Optimization - Global Portfolio Analysis –Aggregation of Key Global Indicators: Lease Information Space Utilization Energy Usage & Conservation Work Order History Supplier Performance Drives resource and investment prioritization: higher efficiency & effectiveness –Focus on building efficiency through visibility to operating anomalies Software integrated with building systems to report Ambient conditions Equipment malfunctions Set point deviations Real time demand for water, HVAC and lighting Automated response to improve building efficiency, reduce CO2 emissions & improve reliability  Building Optimization – Individual Building Performance

3 A Few Questions to Ask Regarding Energy Spend

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5 Challenge  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. Tulane’s buildings represent two-thirds of the university’s carbon footprint. After initial work to upgrade physical systems, the University turned to IBM and Johnson Controls to help further improve century-old Richardson Memorial Hall, home to the Tulane School of Architecture. Solution  IBM Intelligent Building Management Solution  IBM installation and configuration services  Johnson Controls Integration services to connect to existing building systems Customer Value  Tulane can collect, manage and analyze data from buildings to gain intelligence and insight to energy and facilities management.  Richardson Memorial Hall will become a “living laboratory” where this insight leads to understanding on the impact of design/operations on performance.  Integrating digital technology with best practices of building systems to create an exemplar for other historic buildings plus contemporary buildings on campus. Case Study: Tulane University Industry: Education Profile: Founded in 1834, Tulane is one of the most highly regarded and selective independent research universities in the United States. Tulane offers undergraduate and graduate degrees in the liberal arts, science and engineering, architecture, business, law, social work, medicine and public health. Its school of architecture has taken a lead position in sustainability Featured Products & Services: IBM Global Business Services, IBM Intelligent Building Management solution, Johnson Controls services

6 Richardson Memorial Hall Challenge Tulane’s buildings represent two-thirds of the university’s carbon footprint. 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.

7 Solution  IBM Intelligent Building Management Solution  IBM installation and configuration services  Johnson Controls Integration services to connect to existing building systems Benefits  30 +% reduction in Energy cost since the system was installed (still being validated)  Connect existing systems to collect metered data and bring together disparate data to drive better decision making  and use advanced analytics to gain insight in building condition  Richardson Memorial Hall will become a “living laboratory” where insight leads to learning Tulane University project * While long term data is still being collected to quantify the financial impact of identified improvements, IBM anticipates savings of approximately 30+%

8 Integration The IBM Intelligent Building Management Solution Visualization Intelligent Interconnected Instrumented Physical  Open standards  Building Management Systems  Data aggregation – single building Sensors and Meters Bricks and Mortar, Hardware Eaton Honeywell JCI Energy Management Operations Management Real-time Energy Monitoring Analytics & Optimization Alert, Work Order Management Dashboards / Mashups Schneider IBM Intelligent Building Management Siemens

9 Tulane University Pilot – Alerts Analytics detect issues and create work orders

10 Tulane University Pilot – Monthly Usage

11 Tulane University Pilot – December Usage Work Completed Substantially reduced cost Substantially reduced consumption

12 Tulane University Pilot – January Usage What Happened?

13 Air Handler Simultaneously Heating and Cooling - Based on Valve Positions. The solution found 3 units with this condition. The system had been programmed to leave valves always open. The Building Automation System was reprogrammed to correct the problem. Air Handler Heating Control Alert - Low Building Zone Temperature This solution found 8 units under this condition. This rule is looking for room temperatures that have fallen below 67 degrees over a rolling 2 hour window. In looking at the possible root cause of this, possible reason, which is common, is the cooling system of the unit needs to be cleaned and flushed so the chilled water can flow more freely. because minerals and other debris in the water over time can clog the system and cause it not to respond to valve position changes. Air HandlerTemperature Sensor Drift Detected The solution found 6 units under this condition. This rule is looking at the average room temperature and the temperature of the air as it returns back to the unit. If the delta between the two temperatures are greater than 3 degrees then there is a problem. A possible cause was the return air damper may not be open and this could be caused by a faulty actuator or other mechanical problem. Examples of Issues Identified Continuous improvements at Tulane

14 Results calculated for approximately two months prior to two months after December 10, 2012 system changes Results not adjusted for external temperature Additional savings are anticipated Tulane Richardson Hall Improvements “Simple” changes provide significant improvements

15  Established 1956  3.1M Sq Ft / 36 Bldgs  Variety of Space Type  Office  HW & SW Labs  Data Center  Manufacturing  Warehouse  Wide Variety of Equip.  Central Utility Plant  Metasys Controls Sys. (~ 30,000 Points)

16 Energy Consumption Exceeds Spec Equipment Not on Automatic Schedule Steam Leak Identified by Analytics KWH Usage Dual Energy Savings Opportunity Chilled Water & Steam

17 17 IBM Rochester Results: Building Maintenance Savings Compounding Productivity Impact 1)16% Reduction in # of Work Orders 2)34% Productivity in Remaining WO - 34% Work Order # & Hours Average Hours Per WO Baseline - 16%

18 16% reduction in work orders 34% reduction in time per AND 49% reduction in total work orders Rochester Air Handling Unit Work Order History Smarter Building Pilot Results at IBM Work Order Efficiency

19 CHALLENGES TO TRANSFORMATION  Resistance to change  Pride in status quo  Process has never been challenged  Fear: “You are automating me out of a job.”  Don’t believe the savings will occur  For Facilities Management supplier: Cost reduction = Revenue reduction (short term) RECOMMENDED ACTION PLAN Short term: reprioritize tasks Long term: –New career paths –Retraining required Create self-funding model Put savings opportunities in context Gain supplier executive buy-in –Key strategic value proposition

20  Assess client’s data availability of maintenance cost ◦ Labor / Materials / Subcontracted ◦ % of each element of the total  Does client use a Work Order logistic system  Is a standardized Preventative Maintenance program in place  Do the maintenance techs record hours/cost against Work Orders  What level of data is tracked ◦ How is it categorized ◦ How much history  Build credibility using client’s data

21  Site “starting point” is a critical component of ROI  Benefits ◦ Maintenance productivity ◦ Planned maintenance schedules ◦ Equipment efficiency levels ◦ Depth of implementation ◦ Type of space (office, manufacturing, etc.)  Implementation Cost ◦ Levels of existing instrumentation ◦ Building Control System sophistication ◦ Levels & types of connection to network ◦ Work Order logistics system (version of Maximo) ◦ Skilled staff availability

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