2. ENERGYMAESTRO – PRESENTATION OUTLINE
1. Challenges in energy management today
2. ENERGYmaestro methodology
3. ENERGYmaestro examples of implementation
Ulrika Wising – VP Sales & Marketing
Slide | 2
3. INDUSTRY HAS ALREADY SAVED A LOT
But we can still do more!
• 2010 McKinsey
report :
There is still a
potential to
reduce energy
consumption up
to 25% by
improved energy
management
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4. WE ALL WANT TO SAVE ON ENERGY COSTS
Investments
Procurement Operations
Energy
Cost
Savings
Slide | 4
5. ENERGY MANAGEMENT CHALLENGES
• Reduce energy costs • Operations are
while maintaining production-oriented, not
production levels cost optimization-oriented
• Secure already made • Few actionable
investments for parameters for operators
increased energy • Problem solving is based
efficiency on opinions and
• Increase experience rather than on
sustainability facts
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6. EFFECTIVE ENERGY MANAGEMENT
• Is integrated in the overall management of
production, quality and energy
• Is part of a continuous improvement activity
• Perform Audit
• Install necessary measurements
• Install a Data historian
• Implement the “management” part of an energy
management system (targets, responsibilities,
models)
• Improve (training, audit, projects)
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7. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
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8. GAP ANALYSIS
1. Assess 3. Analyze
where you and close
KPI are the gap
Design 2. Target
Maintenance
where you
want to be
Variability
OEE
NOW Waste = Opportunity
TARGET
time
Energy projects are rarely pure energy projects Slide | 8
10. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 10
11. KPI DEFINITION
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
Supervisors
Is it because of the steam users or the steam recovery?
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Water recirculation Water / Air heating
Slide | 11
12. KPI DEFINITION (SMART)
• WHO? WHAT? WHEN? HOW? the
right decision-making support to the
right people, at the right time
Role of KPI
• related to business goals
• linked to relevant targets
• assigned to people that are
accountable
• actionable
• visually adapted to user
• easy to interpret
• in limited number (<5)
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14. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 14
15. DATA COLLECTION – EXAMPLE
It all starts with a very simple question:
What makes the natural gas consumption at the furnace
vary?
Slide | 15
16. What makes the
natural gas
consumption at the
furnace vary?
Slide | 16
17. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 17
18. VARIABILITY ANALYSIS
steam per ton of paper
The causes for variability in
steam use is not clear
Slide | 18
20. VARIABILITY ANALYSIS
Pareto Root cause data analysis
Step 2: chart
%
30
25
20
15
10
5
0
A B C D E F G H I J K L M N O P
Parameters
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21. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 21
23. TARGETING AND MODELING
Best performance Most of the bad
when steam valve performance
1 2
is open <15% and occurs when
heating tower KPI steam valve is
outlet temp is open more than
>85°C 15%
Valve Valve
1 opening 2 opening
< 15% > 15%
USER KPI KPI
CASE Heating Heating
1 tower temp. tower temp. >1.1 <1.1
> 85 °C < 85 °C
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24. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 24
25. MONITORING
Previously unseen situation!
Operator alerts energy
0 00! improvement team for more
00, EAR! !
$6 ER Y ENT investigations
P RR Predicted regimes
ECU !
NGS
R
OF
I
SAV KPI>1.1 KPI<1.1
A: Performance is C: Performance is
> 1.1 good and we know good “but we do
Actual why not know why”
value
of KPI B: Performance is D: Performance is
< 1.1 bad “but we do bad and we know
not know why” why
USER Insight to solve the problem
CASE
1. CO pre-heater < 15%
2. Temp heating tower > 84,5°C
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26. METHODOLOGY
Impact of decision on day-to-day energy cost
Level 1: Monitoring of total GJ/day of steam consumed
Managers
Is there a problem with the mill steam consumption?
GAP
Level 2: Monitoring of GJ recovered / GJ boilers
Is the ratio normal, and if not,
NOW
Supervisors
Is it because of the steam users or the steam recovery?
Target
Level 3: Monitoring of specific equipment / process
Recovery Users
Operators
Reboiler Tempering
Heat exchanger Pickling
Gap Analysis KPI definition
Water recirculation Water / Air heating
Data collection
Variability analysis Targeting + modeling Monitoring
Implementation
Slide | 26
27. IMPLEMENTATION
• An energy management system
should be an integral part of the
manufacturing management system –
not a stand alone separate system
ENERGY,
Cos PRODUCTIVITY
t
AND QUALITY
SHOULD BE
Ene
rgy
MANAGED
TOGETHER WITH
A COST
OPTIMIZATION
FOCUS
Slide | 27
28. IMPLEMENTATION
“Turning everyone into
a decision maker.
Impact of decision on day-to-day energy cost
Push decision-making
Managers
down to the lowest
level.
Our experience strongly
Supervisors
suggests that when you
ask employees to make
most of the decisions,
they become more
Operators
productive”
- Nucor
Slide | 28
