An Approach for Reducing Energy Consumption in

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Procedia CIRP 17 (2014) 505 – 510
Variety Management in Manufacturing. Proceedings of the 47th CIRP Conference on Manufacturing
Systems
An Approach for Reducing Energy Consumption in Factories
by Providing Suitable Energy Efficiency Measures
Manuela Krones*, Egon Müller
Professorship Factory Planning and Factory Management, Technische Universität Chemnitz, Erfenschlager Straße 73, 09125 Chemnitz, Germany
* Corresponding author. Tel.: +49-371-531-39416; fax: +49-371-531-839416. E-mail address: [email protected]
Abstract
Energy efficiency has developed into an important objective for industrial enterprises. However, there is still a need for systematic approaches
to reduce energy consumption in factories. Existing methods focus on the optimization of manufacturing processes and lack upon considering
the entire factory system. Additionally, they are based on a detailed quantitative analysis of processes and thus, they need a high effort during
the phase of data acquisition. Therefore, an approach for reducing energy consumption by providing energy efficiency measures to factory
planning participants was developed in order to overcome these barriers. The general approach is described in this paper and supported with a
use case that demonstrates the required information and possible outcomes in terms of energy efficiency information. Main advantages of this
approach are reducing the effort to acquire energy data and the possibility to consider the factory system holistically.
© 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license
© 2014 The Authors. Published by Elsevier B.V.
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Selection
and peer-review under responsibility of the International Scientific Committee of “The 47th CIRP Conference on Manufacturing
Selectioninand
responsibility
of the International
Scientific Committee of “The 47th CIRP Conference on
Systems”
thepeer-review
person of theunder
Conference
Chair Professor
Hoda ElMaraghy.
Manufacturing Systems” in the person of the Conference Chair Professor Hoda ElMaraghy”
Keywords: energy efficiency; energy management; factory planning; factory management; energy efficiency measure
1. Introduction
The importance of energy efficiency as an objective for
industrial enterprises increases due to ecological, political and
economic reasons. Considering the ecological perspective, the
International Energy Agency identified energy efficiency as
most important driver to reduce global greenhouse gas
emissions [1]. Political conditions are fixed upon both
international and national levels. For example, the European
Union drafted a long-term strategy in the “Energy Roadmap
2050”, which includes, among other things, an 80-95 %
reduction of greenhouse gas emissions until 2050 [2]. From
an economic point of view, industrial enterprises have an
incentive to reduce their energy consumption because of
increasing energy prices, such as the European average prices
for gas in industry, which rose by approximately 34 % during
the last four years [3].
Despite this situation, the implementation of energy
efficiency measures has not met the expectations yet. The
reasons for the deficits in realizing energy efficiency include
lack of time, lacking transparency on energy consumption,
lacking capital for investments and divided responsibilities
within a company [4].
Different tools and methods have been developed in recent
years to support the systematic analysis and optimization of
industrial enterprises for reducing their energy consumption.
However, the existing methods mainly focus on
manufacturing processes and systems. Although these are
important aspects of the energy-efficient factory, considering
the interrelationships between products, processes and
resources in the factory system is essential for a holistic
integration of energy efficiency in the enterprise.
Another barrier in implementing methods is the high effort
for data acquisition. Therefore, an approach to reduce energy
consumption within factory systems was developed that
2212-8271 © 2014 Elsevier B.V. This is an open access article under the CC BY-NC-ND license
(http://creativecommons.org/licenses/by-nc-nd/3.0/).
Selection and peer-review under responsibility of the International Scientific Committee of “The 47th CIRP Conference on Manufacturing Systems”
in the person of the Conference Chair Professor Hoda ElMaraghy”
doi:10.1016/j.procir.2014.01.045
506
Manuela Krones and Egon Müller / Procedia CIRP 17 (2014) 505 – 510
provides energy efficiency measures to factory planning
participants based on qualitative data [5].
The remainder of the paper is organized as follows: An
overview of the state of the art of energy efficiency-oriented
factory planning is described in section 2. The overall concept
for the methodical approach is presented in section 3. A
detailed use case describes the implementation of the
approach in section 4. Section 5 summarizes the results and
gives an outlook on future research work.
2. State-of-the-art
In general, existing tools for considering energy efficiency
of manufacturing systems can be divided into assessment,
monitoring and inventory tools on the one hand while
engineering, design and improvement tools on the other [6].
The following discussion is focused on the second group,
since the aim is to reduce energy consumption in factory
systems.
The existing tools to support energy efficiency-oriented
factory planning and management can be divided into energy
efficiency guidelines, principles and methods [5]. Table 1
provides an overview on these tools, which are described in
detail in the following.
Table 1. Overview on existing types of tools for energy-efficient production.
Description
Example(s)
Energy
efficiency
guidelines
Collection of energy
efficiency measures in
specific sectors or fields
US Department of Energy –
Energy Efficiency &
Renewable Energy: Guide to
Energy-Efficient Lighting [7]
Energy
efficiency
principles
Small number of general
approaches for energy
efficiency
Energy
efficiency
methods
Systematic approaches to
identify and realize energy
efficiency improvement
opportunities
x
x
substitute energy sources
increase efficiency of
equipment
x energy recovery
(selected according to [8])
Energy metering and
assessment of manufacturing
processes
energy recovery and direct use of losses for heating [8].
Further examples can be found in [5].
Energy efficiency methods describe a systematic approach
on the identification and realization of energy efficiency
improvement opportunities. There are varieties of energy
efficiency methods available in scientific literature, from
which only a selection is presented in the following. The
majority of energy efficiency methods focuses on
manufacturing processes and identifies measures based on a
detailed quantitative analysis of the underlying processes,
whereof mainly manufacturing processes are considered (e.g.
[9, 10]). Some contributions describe the implementation of
analyses with regard to the requirements of a specific sector
[11]. Other publications expand the approaches in terms of
other objectives (e.g. resources, waste) and to a wider system
definition (e.g. factory level) [12, 13]. There are also methods
that do not require a quantitative analysis but lack to provide
methodical support for the deduction of appropriate energy
efficiency measures. The main focus of these methods is to
create transparency within the process (e.g. [14]).
In general, the existing energy efficiency methods can be
described by the general scheme to define a system, analyze
the processes within the system by means of energy
measurements, prioritize sub-systems and deduce energy
efficiency measures. By using the measurement results, the
expected savings of energy efficiency measures can be
assessed quantitatively.
However, this state-of-the-art approach requires high
efforts during the analyzing phase in order to acquire the
relevant data. Another barrier lies in the necessity of expert
knowledge for the deduction and description of energy
efficiency measures since the existing methods do not
describe this step detailed enough to enable practitioners to
transfer it to another application on their own.
Thus, there is need for research for developing an approach
to systematically identify suitable energy efficiency measures
for a defined project task without the high effort of acquiring
energy consumption data. The deduction of measures should
be transparent in order to make the approach understandable
and manageable.
3. Methodical Approach
Guidelines provide an overview on energy efficiency
measures within a specific industrial sector or a specific field
of application (e.g. lighting). The guidelines are mainly
published by independent institutions or governmental
organizations (e.g. [7]). By providing information close to
application and including examples of realization within
enterprises, the guidelines are suitable for practitioners.
However, finding the information that is relevant to a specific
use case requires lots of effort and time.
Energy efficiency principles contain a collection of a small
number of general approaches to increase energy efficiency.
They are identified by generalizing energy efficiency
measures and are mainly published by research institutions or
consultancies. One example is distinguishing between
substitution of energy sources, reduction of energy demand,
increase efficiency of equipment, reduction of process losses,
The two most important requirements for the methodical
approach are the systematic procedure and the reduction of
effort for system analysis. The systematic procedure needs to
ensure that information to factory planning participants is
provided in a structured way (compared to energy efficiency
guidelines, where there is no guidance for practitioners to find
the information that is relevant for their specific situation).
The reduction of effort for system analysis increases the
applicability of the methodical approach since high effort for
data acquisition without the possibility to forecast the results
in energy savings is a high barrier for industrial application.
Based on these requirements, a general concept has been
developed to systematically guide a factory planning
participant from his or her project task to appropriate energy
efficiency measures. The goal is to provide suitable energy
efficiency approaches in order to increase the efficiency of
Manuela Krones and Egon Müller / Procedia CIRP 17 (2014) 505 – 510
information gathering. The approach consists of four major
steps, which are explained in the following (Figure 1).
The starting point for the approach is the definition of the
project task or planning situation by the factory planning
participant (user input). The most important parameters to
describe the task are object level, system process, part of the
energy chain, energy form, planning case and user’s role.
According to their background, the first four parameters are
defined as technical parameters and the last two as
organizational parameters.
The object level describes the level of abstraction of the
considered system (e.g. factory, building, plant area, single
machine). The system process defines the process of the
enterprise to which the considered system belongs to (e.g.
assembly, logistics). The part of the energy chain describes
whether the system performs energy generation, conversion,
distribution, storage or use, since factories increasingly
integrate several of these functions [15]. The energy form
defines the types of resources that are used within the
considered system (e.g. electricity, water). The planning case
comprises the extent to which changes are possible in the
system; planning a new system has the highest degrees of
freedom, whereas operating the existing system equals the
lowest degree of freedom. Finally, the user’s role defines the
perspective of the user (e.g. factory planner, worker).
When applying the method, not all of these parameters
need to be specified. The user can choose which parameters to
specify; however, if the number of specified parameters is too
small, the user may receive too unspecific results and needs to
repeat the approach with changes in the input.
User input
1. Analysis of the situation
2. Identification of
influential opportunities
3. Deduction of measures
Changes in
user input
Energy efficiency
measures
4. Identification of
realization information
Energy efficiency
realization information
User satisfied?
No
Yes
Suitable energy efficiency
measures and information
towards their realization
Figure 1. Overall concept for methodical approach to systematically identify
energy efficiency measures
As a first step, a model of the considered system is created
in order to identify improvement opportunities (1. analysis of
the situation). The required energy form defines the objective
as starting point of the analysis (e.g. consumption of
electricity). The model of the considered system consists of
two parts: The general model is developed depending on the
parameter object level, whereas the subordinate systemspecific model refers to the parameter system process. The
general model contains indicators that can be influenced on
the object level. The detailed physical parameters that affect
these indicators are specified in the system-specific model.
Afterwards, the organizational parameters of the user input
are analyzed in order to identify improvement opportunities
for the specific project task (2. identification of influential
opportunities). The general possibilities, i.e. the technical
improvement opportunities, are limited to the opportunities
within the given organizational restrictions. This means that
the parameters identified within the general and systemspecific model during the situation analysis are examined in
more detail. For each of them, it needs to be checked whether
the parameter can be influenced in this situation (control
factors) or not (noise factors). The control factors that are
determined in this step are also referred to as influential
opportunities.
The information of the influential opportunities is used in
order to search for suitable energy efficiency measures in a
database (3. deduction of measures). For this step, the energy
efficiency measures need to be structured according to
different criteria in order to support the matching between
influential opportunities and energy efficiency measures. The
existing energy efficiency guidelines and energy efficiency
principles (see section 2) need to be integrated in the
collection of energy efficiency measures.
In the next step, useful information on the realization of
energy efficiency measures is identified (4. identification of
realization information). A set of categories was developed to
structure this information:
x Basic information: Which basics are relevant to know?
x Relevance: Why is energy efficiency important in this
field?
x External requirements and information: Which
requirements do exist?
x Principles: How does this measure work?
x Benefit: What is the benefit in realizing this measure?
x Industrial examples: Who applies this measure
successfully?
The content provided within these categories is tailored to
the user’s situation by using all of the input parameters. For
example, the plant engineer receives more information on the
functionality of a measure whereas the manager receives more
information regarding the economic efficiency.
At this point, the user has the possibility to change the
inputs if the results are not yet satisfying. Otherwise, the user
receives suitable energy efficiency measures and information
towards the realization.
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Manuela Krones and Egon Müller / Procedia CIRP 17 (2014) 505 – 510
4. Use Case
In the following, a fictive use case for the application of
the methodical approach is demonstrated. The necessary
information in terms of energy efficiency measures and
realization information is provided by a small prototype
which was created using a literature review. It includes 35
energy efficiency measures and 80 blocks of realization
information. The case is on the object level of a single
machine and analyzes a plate conveyor in the final assembly
of an automotive assembly line.
The initial situation of this use case is a plate conveyor that
is operated within an automotive final assembly line. It
transports the finished cars from the wheel assembly to and
through the quality assurance at the end of the assembly. For
this task, the conveyor needs electricity as energy form. The
project task is to redesign the plate conveyor as part of a
rationalization measure. The logistics planner wants to know
about energy efficiency measures that can be realized in this
situation with a moderate budget.
The starting point for the approach is the user input for this
specific project task, which is shown in Table 2.
Table 2. Use case machine – user input for methodical approach
Specification
Object level
Machine
System process – core process
Assembly
System process – support process
Logistics
Part of the energy chain
Energy use
Energy form
Electricity
Planning case
Retrofit
User’s role
Logistics planner
Objective
Parameter
In the next step, the technical parameters are used to create
a model of the energy consumption in the considered system
(Figure 2). As described in section 3, the starting point for the
analysis is the required energy form. In this use case,
electricity is the only one, so the objective is to reduce the
electrical work of the plate conveyor. The next step is to
create the general and the system-specific model. The general
model depends on the object level “machine”. Thus, the
electrical work for the system is divided into the different
condition states of the machine, i.e. processing, ready-tooperate and stand-by. The processing state means that the
system operates, i.e. transports cars. The ready-to-operate
state means that the conveyor is ready to transport cars, which
means that the conveyor is moving without any car on it
(system waits). The stand-by state indicates that the system is
not in movement but not totally switched off. This means,
control panels and similar facilities are switched on and it
only takes a short time to move the system back into
operation.
Since the work for processing refers to mechanical work
rather than electrical work, a conversion of electrical energy
to mechanical energy is needed in this system. Therefore,
conversion losses are part of the objective electrical work and
need to be considered in the general model.
It should be noted that this general model can be used for
any considered system on the object level “machine”, i.e. it is
only based on the input parameter “object level” but does not
depend on the system process. The system process, however,
is included in the system-specific model, i.e. in the physical
parameters that influence the parameters within the general
model.
Using the organizational parameters, the basic influential
opportunities are now divided into control factors and noise
factors – depending on whether they can be changed within
the given restrictions. In Figure 2, the control factors in this
use case are formatted bold.
Electrical
work
System-specific
Model
General Model
Work for
processing
Operating
time
Mass
goods
Mass
conveyor
Friction
coefficient
Processing
power
Conveyor
velocity
Power peripheral
components
Work for readyto-operate
Waiting
time
Work for
stand-by
Ready-tooperate power
Mass
conveyor
Stand-by
time
Stand-by
power
Conveyor
velocity
Friction
coefficient
Power peripheral
components
Figure 2. Use case machine – model of the energy consumption for identifying influential opportunities
Losses
work
Operating
time
Losses
power
Drive
efficiency
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Manuela Krones and Egon Müller / Procedia CIRP 17 (2014) 505 – 510
Energy efficiency measure
…
Use energy-efficient motors
Basic information
•
•
Motor efficiency = ratio between offered mechanical power and
supplied electrical power [16].
Losses in a motor [16]:
• Fixed losses (iron losses, friction losses)
• Variable losses (copper losses in stator and rotor)
Relevance
•
•
Which basics are relevant to know?
Why is energy efficiency important in this field?
Up to 95 % of the life cycle costs of a motor are caused by energy
consumption [17]
Systems driven with electric motors cause approximately 70 % of
industrial energy consumption [16]
External requirements and information
•
•
•
Principles
•
Benefit
•
•
How does this measure work?
Motor efficiency improved by increased copper diameter, improved
winding technology and improved air routing inside [16]
What is the benefit in realizing this measure?
Investment in energy-efficient motors usually pays off after 1 to 3
years [17]
What needs to be considered when evaluating a replacement [21]:
• Investment cost
• Motor run-time
• Planned replacements due to maintenance
Which requirements do exist?
IEC 60034-30 specifies energy-efficiency classes, which need to be
provided by the motor producer (motor plate and documentation)
[18]:
• IE 1 Standard Efficiency
• IE 2 High Efficiency
• IE 3 Premium Efficiency
• IE 4 Super Premium Efficiency
EU requirements: IE 2 motors as from June 2011, IE 3 motors as
from January 2015 [19]
USA requirements: IE 3 motors as from December 2010 [20]
Industrial examples
•
Who applies this measure successfully?
Example handling of baggage in an airport [22]:
• Starting point: use of standard motors
• Measure: replacement by energy-efficient motors (IE 2)
• Reduced energy consumption of 61.900 kWh/year
• Reduced energy costs of 6.190 €/year
• Pay-off time approximately 2.2 years
Figure 3. Use case machine – detailed description of realization information for measure 5 “Use energy-efficient motors”
In the following, each of the influential opportunities is
described and the assignment to control or noise factors is
explained. It should be noted that the differentiation between
control and noise factors is performed on the last stage of
parameters, i.e. when there is no further refinement of a
parameter.
The general model contains the parameters operating time,
waiting time, stand-by time and stand-by power. The planning
case in this use case is a retrofit, i.e. no changes in the
logistics process are intended. This means that the logistics
planner has no influence on the operating time. However, the
logistics planner may influence the share of waiting and
stand-by times by changing the system control. The stand-by
power is influenced by the definition of the components that
are operated in stand-by mode. Therefore, the control factors
in the general model are waiting time, stand-by time and
stand-by power.
The system-specific model comprises the parameters mass
of goods, mass of conveyor, friction coefficient, conveyor
velocity, power of peripheral components and drive
efficiency. As already mentioned, the logistics planner does
not intend to change the process, i.e. the mass of the goods
and the conveyor velocity cannot be influenced. The mass of
the conveyor and the friction coefficient depends on the
material and the construction of the plate conveyor. Changing
these components would need a high effort in time and cost,
which is not possible within this retrofit. The power of
peripheral components depends on the control of the plate
conveyor which can be changed in a small project. The drive
efficiency depends on the choice of motors and gearboxes,
which can be changed as part of the retrofit.
Combining the general and the system-specific model, the
control factors are waiting time, stand-by time, stand-by
power, power of peripheral components and drive efficiency.
Using this information of control factors, a database is
searched for relevant energy efficiency measures. The result is
shown in Table 3.
Table 3. Use case machine – identified energy efficiency measures (selection)
No.
Energy efficiency measure
Directly influenced
parameter
1
Adjust nominal power of motors
Drive efficiency ↑
2
Enable switching conveyor sections in
stand-by mode when they are not in use
Waiting time ↓
3
Increase transmission efficiency
Drive efficiency ↑
4
Reduce energy consumption of control
system
Power peripheral
components ↓
5
Use energy-efficient motors
Drive efficiency ↑
6
Use synchronous motors instead of
asynchronous motors
Drive efficiency ↑
Finally, the user receives information on the energy
efficiency measures which enables him or her to integrate the
measures in the planning project. An example of realization
information of measure 5 “Use energy-efficient engines” is
shown in Figure 3.
As described in section 3, the information is divided into
six parts. The content within the categories is adjusted
according to the user’s role. For example, the logistics planner
does not need to know the details of the principles, i.e. how
motors are constructed and developed to reach a higher
efficiency. Therefore, the part “principles” is very short in this
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Manuela Krones and Egon Müller / Procedia CIRP 17 (2014) 505 – 510
case. Furthermore, the content in the realization information
can be changed dynamically, i.e. the users themselves can add
relevant information, such as their own experiences in
implementing the measure.
It should be noted that the primary goal of the approach is
to reduce energy consumption. The effectiveness in terms of
costs and benefits needs to be estimated by the user with the
help of the realization information (especially categories
“Benefit” and “Industrial examples”).
5. Summary and Outlook
In this paper, it has been shown that there is a research
need in developing an approach for the systematic
identification of energy efficiency measures without the high
efforts of acquiring energy consumption data. The developed
general approach is based on qualitative input information and
enables the user to identify energy efficiency measures that
are appropriate in his or her planning situation. The use case
demonstrated the developed categories for structuring both the
planning situation and the energy efficiency information.
Further research will contain expanding the existing
approach both in terms of a higher abstract level of the
considered system (e.g. factory buildings) and in terms of the
considered objectives (e.g. greenhouse gas emissions).
Furthermore, additional information needs to be integrated
into the realization information (e.g. correlation between
measures).
Acknowledgements
The Cluster of Excellence “Energy-Efficient Product and
Process Innovation in Production Engineering” (eniPROD®)
is funded by the European Union (European Regional
Development Fund) and the Free State of Saxony.
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