Available online at www.sciencedirect.com
Procedia CIRP 7 (2013) 628 – 633
Forty Sixth CIRP Conference on Manufacturing Systems 2013
Energy Efficiency of Manufacturing Processes: A Critical Review
Fysikopoulos Apostolosa, Papacharalampopoulos Alexiosa, Pastras Georgiosa,
Stavropoulos Panagiotisa, Chryssolouris Georgea*
a
Laboratory for Manufacturing Systems and Automation, Department of Mechanical Engineering and Aeronautics, University of Patras, Patras,
26500, Greece
* Corresponding author. Tel.: +30 2610 997262; fax: +30 2610 997744. E-mail address: [email protected].
Abstract
A critical review on the energy efficiency of important manufacturing processes is presented in this study. Relevant conventional
and non-conventional processes, utilized in the three major industrial sectors of aeronautics, automotive and white goods are briefly
discussed. Information related to their energy efficiency is provided. The conclusions of both the analysis and the discussion
comprise some practical aspects and recommendations for the energy efficient use of selected processes.
© 2013
2013The
TheAuthors.
Authors.
Published
by Elsevier
©
Published
by Elsevier
B.V.B.V.
Open access under CC BY-NC-ND license.
Selectionand
and/or
peer-review
responsibility
of Professor
Pedro
Carmo Cunha
Selection
peer-review
underunder
responsibility
of Professor
Pedro Filipe
do Filipe
Carmo do
Cunha
Keywords: Energy Efficiency; Manufacturing Processes; Review
1. Introduction
for creating stable process conditions and peripheral
functions.
Manufacturing processes use one or more physical
mechanisms (Figure 1) to transform a material’s form or
shape [1].
Fig. 2. Total Consumption by End-Use Sector, 1949-2011 [2]
Fig. 1. Process from an energy point of view
The energy required for such operations is considered
as an input of the process, which is partially transformed
into useful work, embodied into the form and
composition of the products and wastes while the rest is
transformed into waste/lost heat. Machining utilize only
a fraction of the consumed energy for the actual valueadding process, while the majority of the energy is used
Energy efficiency becomes a driver for
manufacturing industry, since it is historically one of the
greatest energy consumers and carbon emitters in the
world (Figure 2). The manufacturing sector is
responsible for about 33% of the primary energy use and
for 38% of the CO2 emissions globally [3-4].
Moreover, the increasing price of energy and the
current trend of sustainability have exerted new pressure
2212-8271 © 2013 The Authors. Published by Elsevier B.V. Open access under CC BY-NC-ND license.
Selection and peer-review under responsibility of Professor Pedro Filipe do Carmo Cunha
doi:10.1016/j.procir.2013.06.044
Fysikopoulos Apostolos et al. / Procedia CIRP 7 (2013) 628 – 633
on manufacturing enterprises that have to reduce energy
consumption for both cost saving and environmental
friendliness, as well as Life-Cycle Inventories initiatives
[5-6]. During the last 20 years, an increase in energy
prices of up to 100% has been recorded in Germany as
indicated in Figure 3 [7]. Energy savings are expected to
be achievable from increasing both the energy efficiency
of production [8] and the logistic processes, as well as in
innovative energy monitoring and management
approaches [9], leading industries to a way of producing
“more with less” [10].
629
promulgated corresponding electricity usage control
policies and tariffs, such as the Rolling Blackout policy
for industry electricity supply, meaning that the
government electricity will be cut off several days every
week [13].
Increasing demand for energy, coupled with a
restricted supply on the world markets, results in prices
of energy being continuously increased. This general
development as well as the dynamics in price setting
generates uncertainties for organization schemes with
respect to accurately calculated energy costs [17]. The
situation becomes even more complex since proper
improvements in energy efficiency may be achieved by
an approach that considers multiple activities and the
involvement of relevant third parties [18]. Additionally,
the lack of energy efficiency definitions, classifications
and standards [19] of the machine tools increase the
modelling complexity [20-21].
Fig. 3. Electricity price in Germany [11]. Green line shows the price of
electricity on the German electricity exchange. Red line shows the
average price of electricity for households. Purple line stands for the
price of electricity for commercial clients and the blue for special
contracts.
The challenge for manufacturing companies is to
tackle the assumed dichotomy between competitive and
environmentally friendly operations. This holds for both
developed and developing economies. The German
industry consumes around 46% of the country’s overall
energy [12]. Previous studies have estimated that only
10-15% of this amount is consumed by machine tools
for machining operations [12]. At the same time, every
year in China, manufacturing spends around 50% of the
entire electricity produced [13], and generate at least
26% of the total CO2 emissions.
The environmental awareness leads the EU member
states agreeing on the principle of “20/20/20 by 2020”,
i.e. a 20% reduction in greenhouse gases, a 20% share of
renewable energies and a 20% increase in energy
efficiency by the year 2020 as compared to 1990
indicators [14]. Additionally, Germany has adopted the
“Energy Concept 2050”, which staggers the achievement
of goals in different phases. The greenhouse gas
emissions should have been reduced by 40% by 2020,
55% by 2030 and at least by 80% by 2050 [15]. The
International Energy Agency (IEA) has highlighted the
need for energy efficiency measures, in order to achieve
a reduction by two-thirds in the energy intensity of the
global economy by 2050 [16]. Furthermore, China, in
order to reduce the carbon emissions and balance the
time-based unevenness of electricity demand has
Fig. 4. Energy efficient analysis division.
It is necessary to divide the study of energy efficiency
into several different levels. In this study, as shown in
Figure 4, a definition for these levels is presented and
the most important factors that affect energy efficiency,
at each level, are studied and discussed as well as the
inter-level interactions. Furthermore, energy efficiency
definitions are provided at different levels. The lowest
level defined is that of the process. This concerns the
study of energy losses by the physical mechanisms that
are relative to the process itself. Moving upwards the
machine level is defined. A machine does spend energy
related to the process itself, as well as to a series of
peripherals, dedicated to different aspects of the process.
Finally, one has to consider the production line level and
the entire factory level, where energy efficiency is
mainly a function of production planning. Similar
classification approaches appear in recent literature [2224]. However, it is advantageous that the process and
machine levels be separated, since the relevant energy
loses are due to completely different mechanisms.
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Fysikopoulos Apostolos et al. / Procedia CIRP 7 (2013) 628 – 633
are related to the process parameters, resulting in the
energy efficiency equation indicated in Eq.2
2. Energy Efficiency at Process Level
Although recent studies [22, 25] indicate that the
percentage of energy spent at the process itself is
typically a small percentage of the total energy spent, the
study of the processes could be considered rather
interesting for a number of reasons:
The study of the processes provides the deeper
possible understanding of the energy transformations
that take place during the manufacturing process.
Simple analytical models that lead to qualitative and
quantitative results, adaptable to wide range of
applications may be applied.
Although the energy spent at the process level is
minor, an appropriate selection of process parameters
may also alter the consumption of machine
peripherals that correspond to larger percentage of
energy consumption. An example is that of the
dependence of the consumption of a cooling unit on
the processing speed.
Processing time is a function of the process
parameters. Thus, the selection of appropriate process
parameters has consequences for both the machine
peripherals consumptions (machine level) and the
production planning (line and factory levels).
Non-conventional processes, allowing space for
significant energy gains at process level, have not
been adequately studied.
The above points make clear the fact that a complete
analysis that will address the problem of energy
efficiency maximization requires process modeling, not
only describing the energy consumption at process level
as function of the process parameters, but also other
aspects of the process, such as the processing time.
d a a2 S
Eef
1 mp
p e
b k h
S
uc
1 mc
c e
kh
, (2)
1 mn
n e
kh
uc
where kp, kc and kn are the specific machining pressures
of the passive, cutting and normal cutting force
respectively, mp, mc and mn the Kienzle constants of the
passive, the cutting and normal cutting force
respectively, b is the chip length, h is the chip thickness,
a is the depth of cut, d is the starting piece diameter, S is
the feed rate velocity, uc is the cutting speed and
the
coefficient of kinetic friction.
Figure 5, shows the energy efficiency versus the feed
rate velocity, for some typical values of the material and
the process parameters. It is evident that the faster the
process, the more energy efficient it is. This is a general
trend that appears in several conventional processes.
2.1. Conventional Processes
Fig. 5. Energy efficiency as function of the feed rate.
Material removing processes are an important class of
manufacturing processes for a number of industrial
sectors that require high accuracy and flexibility in
processing different kinds of materials [1]. As a case
study, turning and milling processes are presented.
A simple and appropriate for most material removal
processes definition of energy efficiency is the ratio of
the volume of the removed material to the energy spent.
Further studies are needed to capture the behavior of
energy efficiency close to the machine limits. At this
region, factors such as the tool wear may be significant
and it is expected that they will set a limit to the above
trend.
Eef p
Vremoved
.
Espent
(1)
The index p stands for the process level.
With the help of a simple cutting force model, which
relates the cutting forces with chip thickness and length
[26], the consumed power and the material removal rate
2.2. Non-conventional Processes
Lasers have a wide range of applications to
manufacturing processes, such as cutting, welding etc
[27]. Due to the variety of applications, (1)
energy
efficiency for laser processes is studied, as a typical
example of non-conventional processes.
The energy efficiency definition has to adapt to the
process. For instance, in the case of laser drilling, a
further definition for energy efficiency could be:
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Fysikopoulos Apostolos et al. / Procedia CIRP 7 (2013) 628 – 633
Eef p
d hole
,
Espent
(3)
where dhole is the depth of the drilled hole, since the
required output of the process is a hole with specific
depth. When considering the case of laser welding, it is
critical to decide whether the numerator of the energy
efficiency definition should be the volume or the depth
of the melt pool of metal. Thus, the definition of energy
efficiency, at process level, is often process dependent.
At process level, there are energy losses due to
physical mechanisms related to the nature of the process.
Typically, in laser processes, energy is mainly lost
because of
Material reflectivity: A large percentage of the energy
that may exceed 90%, carried by the laser beam, is
simply reflected on the workpiece surface.
Laser beam defocusing: The laser beam is typically
focused on the workpiece surface with the aid of a
lens. As drilling advances, the beam does not focus
on the optimum position, thus resulting in a
significant percentage of energy being absorbed by
non-target regions of the workpiece. This does not
apply to welding, where there is no erosion front.
Heat Conduction: A large percentage of energy is
conducted away from the target because of heat
conduction.
All these factors allow only a small percentage (of the
order of 1%) of the laser beam energy to be converted
into useful form (e.g. latent heat of fusion in the case of
drilling). A quantitative analysis on the energy efficiency
of laser drilling and laser grooving processes is
presented in [28].
Reflectivity is a factor that does not depend on
process parameters. Beam defocusing depends on the
depth of the erosion front and the beam parameters. In
the case of material removing processes, such as drilling,
the faster the process is, the smaller the amount of
energy escaping due to conduction. On the other hand, if
one considers a laser welding process, conduction is
required by the process itself, thus resulting in an
optimum process power that has to be used in order for
minimum losses to be achieved because of conduction.
These kinds of processes require further studying and
can result in potentially large energy gains.
drawn by technical building services namely heating, air
conditioning or air suction. More studies have(1)
shown
that less than 13% of energy expenditures have been
utilized for productive operations [30]. All operating
states of a given process vary in their mean power
demand, timing and therefore also in their energy
amounts.
Energy management defines the sum of all processes
and measures to ensure minimal energy consumption by
a given demand, including the implementation of
organization, information structure, and tools [31].
Considering that both operations and possible
improvement measures are usually implemented at the
single process level [32], the calculation of energy
efficiency must be integrated into the bottom layer and
then transferred to the upper levels throughout the ITsystems.
The definition of energy efficiency, at machine level,
is simpler than that at process level i.e.:
Eef m
Eprovided to the process
Econsumed by machine
.
(4)
The index m stands for machine. Obviously the
numerator of the above definition is the same quantity
that appeared in the denominator of the definition of
energy efficiency at process level. Thus, the overall
energy efficiency, at process and machine levels, can be
acquired as the product of Eefp and Eefm. Finally, energy
efficiency, at machine level, is by definition a
dimensionless number.
A first step towards the study of energy efficiency at
machine level is the categorization of the peripheral
devices.
3. Energy Consumption at Machine Level
Gutowski et al. have shown that the actual consumed
energy required for machining processes is much
exceeded by the energy demand of the related peripheral
equipment that perform the auxiliary processes, such as
coolant pumps, lubrication supply and technical air
ventilation [29], not mentioning the indirect energy
Fig. 6. Laser power output versus power consumption for a CO2 laser
machine [33]
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Fysikopoulos Apostolos et al. / Procedia CIRP 7 (2013) 628 – 633
A major discrimination is between the peripherals
that are always turned on and the peripherals with
consumption that depends on the machine load. A way
of depicting this in an intuitive way was introduced in
[33] and plotted each peripheral consumption as a
function of the output power of the machine (the
numerator of Eefm definition) in a single graph (Figure
6). Several peripherals may be shared between different
machines in the factory (e.g. compressed air supply). In
such an occasion, it may be difficult for the amount of
energy spent by a single machine to be estimated and
possibly some of these considerations have to be
transferred to the line or factory levels. It turns out that
such consumptions may even be dominant [22].
Although the energy reaching the process level is a
small percentage of the overall energy, the energy
efficiency, at process level, plays a significant role [34,
35]. Using the definitions of energy efficiency at process
and machine levels, in the sections 2 and 3, it can be
observed that the doubling of energy efficiency at
process level results in the overall energy efficiency
being doubled at process and machine levels.
4. Energy Efficiency at Line and Factory Level
Duflou et al. [22] provide a systematic overview of
the state of the art in energy and resource efficiency
increasing methods and techniques, in the domain of
discrete part manufacturing, with attention being given
to the effectiveness of the available options.
Studies [36-38] for the use of energy in production
show that different production rates generate different
levels of energy consumption. Industrial companies have
recognized this trend and implement corporate strategies
for improving sustainability and energy efficiency. The
energy efficiency of the entire factory system does not
result directly from the sum of individual parts or
actions, i.e. individual actions can affect each other
positively or negatively. The energy optimization
potential of the overall process or the total system can be
exploited only through a holistic view of the complex
interactions of individual resources, processes and
structures of a factory [37, 39-41]. The application of
electricity control policies and tariffs further complicated
the system’s optimization scheduling problem [20],
since an optimized plan that led to reduction in
electricity consumption did not necessarily lead to
reducing the electricity cost in this situation. However,
very few research studies [20, 37, 42] currently focus on
this problem, despite the fact that a trade-off is important
to be delivered between the reduction in electricity
consumption and cost saving.
Operational methods including dispatching rules,
genetic algorithms and adaptive search procedures to
minimize the electricity consumption and classical
scheduling objectives, on a single machine and parallel
machines, should be investigated [37]. These
investigations should be based upon the observation that
in the manufacturing environment, large quantities of
energy are consumed by non-bottleneck machines as
they lay idle. A possible approach could be keeping such
machines turned off when idle. However, there is
typically some startup energy consumption that makes
this option useful only when it can be applied for time
intervals larger than a critical value. For smaller time
intervals an intermediate standby mode can be preferred.
In such a mode all non-necessary peripherals should be
turned off. Machine tool producers can help developing
machines with such features.
Moreover, when order forecasts and lot sizes are
released early enough, they can provide production
managers with adequate information so that they can
distribute the load evenly and thus prevent stalling and
leaving the resources idle.
5. Conclusions
Production planning plays a significant role on the
energy efficiency of a factory. The load management of
the line can offer great savings from an energy point of
view. Moving towards an energy efficient production
planning requires the inclusion of energy efficiency
within the goals of production design and control at all
levels, together with time cost and flexibility [1]. The
reduction of the idle time through energy efficient
process planning with the combination of better batch
and orders organization will lead to a better prediction of
the workflow. The order distribution combined with
early or periodical “machine shut down” can reduce
significantly the idle time, which is the most inefficient
state of the systems. The managers and production
planners should be able to plan their production not only
by considering the costs, but also by considering the
energy efficiency.
Tools and methods for the integration of energy
efficiency, in planning processes systematically, is now
greater than ever before [43]. The ENEPLAN [44]
project will try to answer that by delivering a
manufacturing planning decision support tool for the
optimization of the plant operation that will be usable
from the conceptual phase of the product to the final
dispatch of the product to the customer. This network
based Meta-CAM tool will promote green and flexible
manufacturing, eco-efficiency and quick respond to the
market demands.
Acknowledgements
The work reported in this paper was supported by the
Fysikopoulos Apostolos et al. / Procedia CIRP 7 (2013) 628 – 633
collaborative program entitled “Energy Efficient Process
planning System – ENEPLAN”, which is under the
seventh framework program - FoF.NMP.2011-1: The
Eco-Factory: cleaner and more resource-efficient
production in manufacturing Program.
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