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Find the hidden “DNA” in your AMR data.
The Energy Manager's Biggest Challenge?
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Where to begin?
Now you can't manage what you have measured
You can’t manage what you can't measure....
220 meters
1,100 graphs
The traditional approach
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The Complex approach
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Why Automation is Key?
• Big Data cannot be interpreted by humans
• Interpretation takes skill and too much time
• Current Energy Management portals do not solve this
Pattern recognition is the answer
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What is Data-mining ?
A
B
C
D
A, B, C, D are characteristics (both of criminals and of waste)
Key performance indicators (KPI)
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Optimum
Start
Optimum
Stop
Dry
Cycling
Excessive
Boost
Pattern recognition of time clock control
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Pattern recognition of time clock control
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Idealised Heating Response to Outside Air
Temperature
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Sites sorted by relative performance
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Median
Unpredictable
Predictable
Weather
Response KPI
Weather response KPI
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Best Worst
Tight Clustering Loose Clustering
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Best Worst
Summer Turndown KPI
Summer Off Summer On
Daylight Saving time overview
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Some sites don’t change time clocks
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FailedWorking
What we found
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Retail Chain
KPI % £
Daylight Saving Time 2 20,000
Weather Response 16 170,000
Summer Turndown 3 30,000
Total 21 220,000
Scalable expertise provides:
• Immediate waste identification
• Ranked monetary priority
• Avoidance of speculative surveys
• Self-adaptive comfort and cost models
• Quantification of project impacts
• Productivity gains
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Example Deliverables
• Remedial recommendations for action:
Plant refurbishment, Controls, Behavioural,
• KPI based league tables ranked by potential
• Tailored reporting scheduled or on-demand
• Automated forecast and budgeting
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In Summary
• Productivity gains, actionable savings and CSR
benefits,
Only possible with AMR-DNA
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Find the hidden “DNA” in your AMR data….