ArticlePDF Available

Abstract and Figures

The increasing demand for energy, coupled with concerns over pollution and climate change, has led governments to establish policy frameworks to reduce CO 2 emissions. Moreover, rises in energy price and increasingly greener customer behaviour are pushing the manufacturing industries to develop more sustainable processes. As a major source of energy consumption in manufacturing systems, machine tools have been the focus of sustainability research communities worldwide. This paper provides a survey of manufacturing industry's sustainability trends and presents a technology-foresight-based methodology for gathering key information on the research development in this topic. Furthermore, a correlation between real-world aspects, such as legal, economic and environmental, and the development of research on energy consumption and efficiency of machine tools is provided. The results highlight the leading countries, institutions, authors and subject areas in this field. Research and development shows a high correlation with governmental actions and appears to be of core importance to meet CO 2 reduction targets. This paper is a revised and expanded version of a paper entitled 'Research publications on energy consumption and efficiency of machine tools: an overview' presented at IMCC 2015, Hangzhou, China, 22-25 October 2015. Link to Journal issue:
Content may be subject to copyright.
nt. J. Nanomanufacturing, Vol. 14, No. 2, 2018
Copyright © 2018 Inderscience Enterprises Ltd.
Research on energy consumption and energy
efficiency of machine tools: a comprehensive survey
Lorena Caires Moreira* and Weidong Li
Futures Institute,
Coventry University Technology Park,
10 Coventry Innovation Village,
Cheetah Road, Coventry, CV1 2TL, UK
*Corresponding author
Michael E. Fitzpatrick
EC4 11,
Faculty of Engineering, Environment and Computing,
Gulson Rd, Coventry CV1 2JH, UK
Xin Lu
Futures Institute,
10 Coventry Innovation Village,
Coventry University Technology Park,
Cheetah Road, Coventry, CV1 2TL, UK
Xiaoxia Li
College of Informatics,
Huazhong Agricultural University,
Wuhan, 430070, China
Abstract: The increasing demand for energy, coupled with concerns over
pollution and climate change, has led governments to establish policy
frameworks to reduce CO2 emissions. Moreover, rises in energy price and
increasingly greener customer behaviour are pushing the manufacturing
industries to develop more sustainable processes. As a major source of energy
consumption in manufacturing systems, machine tools have been the
focus of sustainability research communities worldwide. This paper provides
a survey of manufacturing industry’s sustainability trends and presents a
technology-foresight-based methodology for gathering key information on the
research development in this topic. Furthermore, a correlation between
real world aspects, such as legal, economic and environmental, and the
development of research on energy consumption and efficiency of machine
tools is provided. The results highlight the leading countries, institutions,
Research on energy consumption and energy efficiency of machine tools 141
authors and subject areas in this field. Research and development shows a high
correlation with governmental actions, and appears to be of core importance to
meet CO2 reduction targets.
Keywords: CNC machining; machine tools; energy; research foresight;
sustainable manufacturing.
Reference to this paper should be made as follows: Moreira, L.C., Li, W.,
Fitzpatrick, M.E., Lu, X. and Li, X. (2018) ‘Research on energy consumption
and energy efficiency of machine tools: a comprehensive survey’, Int. J.
Nanomanufacturing, Vol. 14, No. 2, pp.140–164.
Biographical notes: Lorena Caires Moreira is currently an inquisitive PhD
student in the Materials and Manufacturing Engineering Research Centre at
Coventry University, in the UK. She has a BSc in Manufacturing and Systems
Engineering from UESC in Brazil; and received her MSc by research degree
in Mechanical, Automotive and Manufacturing Engineering from Coventry
University in 2016. Her current project involves process mining and
optimisation for targeting sustainability as a strategic goal to enhance the
performance of machining processes. It includes the use of smart sensors and
other ICT for process monitoring, data analysis, predictive modelling and soft
computing techniques.
Weidong Li is a Professor in Manufacturing. His research areas include
computer aided design (CAD), computer aided manufacturing (CAM), additive
manufacturing (AM), sustainable manufacturing, internet of things and
cloud-based manufacturing. In the past decade, he has been carrying out
various research projects in the area, sponsored by the European Commission,
EPSRC and industries. He has been well-recognised in international academic
societies. His research publications include three books (Monograph and Edited
books by the World Scientific Publisher, Springer), four book chapters in
Springer books, and 110 research papers in well-established international
journals/conferences (56 journal papers and 54 conference papers).
Michael E. Fitzpatrick is the Pro-Vice-Chancellor (Executive Dean) at
Coventry University, with responsibility for the portfolio of engineering,
environment and computing; and he also holds the Lloyd’s Register Foundation
Chair of Structural Integrity and Systems Performance. He is a Chartered
Engineer, Chartered Scientist, and Fellow of the Institute of Materials, Minerals
and Mining. His research centres around the application of advanced
experimental methods to materials engineering applications, particularly in the
nuclear power and aerospace industries. His group has a range of research
projects assessing materials performance and structural integrity issues,
particularly internal stress and damage development in metallic materials and
Xin Lu received his BSC in Electronic Science and Technology from the
Beijing Institute of Technology, China in 2004 and MSc in Electronic,
Electrical and Systems Engineering from the Loughborough University in
2005, respectively. He then held a System Engineers position in Shanghai
Flight T.TandC and Telecommunication institute, China from 2006–2007
before moving back to Loughborough University as a full time research student
and a part time Research Associate. In 2012, he gained his PhD in Computer
Science, after which he was appointed as a Senior Research Assistant in the
Centre for Automotive and Power System Engineering at the University of
South Wales. In 2013, he joined the Faculty of Engineering, Environment
and Computing, Coventry University to take up the position as a Research
142 L.
oreira et al.
Xiaoxia Li graduated from Wuhan University and received her PhD degree in
2012. During her PhD process, she researched the cooperation techniques of
CAD/CAM and the data exchange among heterogeneous CAD systems. After
graduation, she worked in Huazhong Agricultural University and researched
the optimisation of scheduling. Two years later, she joined the research team of
sustainable manufacturing of Coventry University. Currently, her research
work focuses on sustainable manufacturing.
This paper is a revised and expanded version of a paper entitled ‘Research
publications on energy consumption and efficiency of machine tools: an
overview’ presented at IMCC 2015, Hangzhou, China, 22–25 October 2015.
1 Introduction
The increase in energy demand, with the associated social, environmental and economic
aspects, has been a worldwide concern in recent decades. The manufacturing sector is in
the spotlight as a major consumer of energy. According to the US EIA (2010), the sector
was responsible for approximately one-third of primary energy use and 38% of CO2
emissions globally. A reduction in energy demand of production systems is, therefore, of
prime importance.
Government leaders are increasingly aware of the urgent need to make better use of
the world’s energy resources. A series of policies, commitments, and guidelines on
reducing lifecycle energy costs and the associated carbon emissions have been launched,
which have encouraged and supported efficiency improvements by industrial firms
(Geller et al., 2006).
Since the third industrial revolution, beginning in the 1970s, computer numerical
control (CNC) machines have become predominant in industry, especially in automotive
and aerospace sectors. Moreover, according to Liu et al. (2013), these machines are the
principal energy-consuming devices in manufacturing systems. For this reason, machine
tools have been the focus of research communities for achieving manufacturing
sustainability all over the world. Research plays a major role in the achievement of more
efficient machining processes. Considering the relevance of research development, the
urgent global need for energy saving and the significance of machines tools on energy
demand of production systems, a comprehensive survey on manufacturing industry trends
and research development on energy consumption and efficiency is imperative.
In response to this scenario, this paper contributes four main points, as follows:
x A methodology based on a technology-foresight approach that can support decision
making in the planning stage of research projects.
x A survey of key aspects that lead research development trends related to the
manufacturing sector.
x The scenario of research publications related to energy consumption and energy
efficiency of CNC machines in the period 2007–2015.
x A correlation between aspects such as government policies, manufacturing industry
trends and economic factors, and the research development scenario.
Research on energy consumption and energy efficiency of machine tools 143
Previously, similar work was done covering the last 20 years. It found that approximately
80% of all documents in this domain were published in the period from 2007 to 2015
(Moreira et al., 2015), hence, the choice of the period considered in this paper. The
results based on recent publications provide valuable and up-to-date information to
support future work.
The paper is organised as follows: Section 2 presents a methodology for gathering
data to support research decision process; research background is shown in Section 3,
Section 4 includes the scenario of research development related to energy consumption
and efficiency of machine tools and its analysis, and the conclusions are drawn in
Section 5.
2 Technology-foresight-based methodology
Anteriority research is one type of technology foresight study, which is largely used to
draw market trends to support the development of new products. Basically, this is a
science of understanding what has been done in order to predict future trending in a
specific area or subject. Although frequently used in research and development (R&D)
departments of private companies, such methodology is not commonly applied to support
research projects in academia.
As a methodology for gathering key information from several published documents,
anteriority research appears to be a potential tool to support research projects
development. There are different ways to carry out and analyse all the information
gathered during the scope definition phase research development, and it is highly
influenced by the researcher’s experience and their own methods. Nonetheless, this task
may be time-consuming, depending on the maturity of the field or lack of experience –
especially for new researchers.
For this reason, an adapted technology-foresight-based methodology is provided to
support research development. Basically, the methodology includes seven steps, as
1 To define research scope or subject area to be investigated and the period to be
2 To define keywords and operators (OR, AND, NOT) for the keyword search – this
step normally carries out a literature review together to a scope table in order to
define the best keyword combination.
3 To choose the tool (software, website, etc.) and database that will be used for the
search – which depends on the subject area.
4 To insert the keywords combination established in Step 2 in the tool chosen in the
previous step to gather the desired data.
5 To revise gathered data – to make sure the documents obtained are related to the area
investigated, skimming and scanning are techniques applied to check the documents
through their title and abstracts.
144 L.
oreira et al.
6 To generate graphs – this process depends on the tool chosen to obtain the data: if
software, it normally generates the graphs; if a website, normally the data is
downloaded in excel format and then graphs can be generated.
7 To analyse the graphs and report the most representative findings – it is of
paramount importance to correlate the information from graphs with real world
aspects that could affect the research development on the area under analysis.
This methodology was used to obtain the scenario of research development related to
energy consumption and energy efficiency of machine tools from 2007 to 2015, which
are analysed in Section 5. The details can be seen in Table 1.
The next section presents the research background. Key aspects that have led industry
research trends are discussed. Moreover, a comprehensive survey on energy consumption
of machine tools in the manufacturing sector is provided.
Table 1 Details of technology-foresight-based methodology carried out
Name Details Observation
1 Subject area Energy consumption and
energy efficiency of CNC
The significance of machine tools in
energy demand of manufacturing
2 Period [years] Between 2007 and 2015. This period was found as the most
representative in terms of the number of
research publications in the last 20 years.
3 Keywords ‘CNC machining’; ‘machine
tools’; ‘numerical control
machine’; and, ‘energy’.
These are the same keywords used on
previous work when analysis was carried
out for the last 20 years.
4 Tool and
Scopus®. This is the largest abstract and citation
database of peer-reviewed literature
(Scopus, 2015).
3 Research background
3.1 Manufacturing industry trends in energy efficiency
3.1.1 Reduction in energy demand
According to a report published by BP Energy Outlook 2035 (2014), primary energy
demand will increase by 41% between 2012 and 2035, with the growth averaging 1.5%
per year. The 2002–2012 decade recorded the largest ever growth of energy consumption
in volume terms over any ten-year period.
This report clearly suggests that energy consumption is a factor of high concern for
the coming years. Responsible for one-third of the total primary energy consumption in
the world (US EIA, 2010), manufacturing companies have been under increasing
pressure to provide more sustainable production systems. From the economic perspective,
rises in energy and raw materials price are two important factors that justify the urgent
need for smarter and more energy efficient processes in manufacturing industries. At the
same time, resources such as raw materials for metal machining companies are becoming
scarce, which makes imperative the adoption of techniques to reduce waste of material.
Research on energy consumption and energy efficiency of machine tools 145
Moreover, to remain competitive on a global manufacturing scale, manufacturing
companies need to be aligned with legal and environmental regulations, in addition to
complying with new customer and market requirements.
3.1.2 Customer behaviour
Customer environment awareness has led to a green consumer behaviour, in which
individuals consider environmental or social issues while making purchasing or non-
purchasing decisions (Peattie, 1992). This describes the increasing trending for greener
products. In addition, customers’ requirements for customised products have become
more and more evident in recent years. Therefore, companies are striving to improve
productivity and quality, while maintaining a clean and sustainable environment (Gupta
et al., 2015).
3.1.3 Process sustainable strategies
Sustainability can be implemented in the manufacturing sector in different manners. In
industries where machine tools are the core of manufacturing processes, the adoption of
sustainable techniques such as reduction of manufacturing steps by employing advanced
or alternative techniques, use of eco-friendly lubricants and more sustainable lubricant
techniques while machining, minimum waste of material and minimising the energy
consumption of processes are of great importance to achieve eco-friendly machining
However, to achieve sustainability, products and processes should meet challenges
from all social, environment and legal aspects, and not only concerning their functions,
performance, and cost (Gupta et al., 2015).
3.1.4 Policies and legal agreements
In accordance with the urgent need for a more sustainable world, government leaders
have launched many commitments and initiatives to reduce CO2 emissions, as well as to
boost the energy efficiency of manufacturing systems.
Leading countries in the manufacturing sector, such as China, Germany, the USA and
Japan have reported a high significance of the energy consumption of their manufacturing
sector. China, which has recently shown the fastest economic growth rate, emerged as the
key contributor to the growth of energy consumption over the last decade. Moreover, in
this country, manufacturing spends around 50% of the entire electricity produced and
generates at least 26% of the total CO2 emissions (Tang et al., 2006). Industrial
production in China increased 6% in July of 2015 over the same month in the previous
year; it averaged 12.84% annual growth from 1990 until 2015 (China Statistical
Yearbook, 2014). Together, the USA and China account for over one-third of global
greenhouse gas emissions (White House, 2014). As the worlds third largest emitter,
India is coming under increasing pressure to comply with commitments and targets
(India’s NAPCC, 2008). The industry sector in Germany consumes around 46% of the
country’s overall energy (König, 2010). For comparison, in 2013, the industry sector
accounted for 25.1% of the final energy consumption in Europe.
According to IEA’s World Energy Outlook (2014), effective policy commitment to
energy efficiency is essential. Moreover, without this policy commitment, international
146 L.
oreira et al.
efforts to help and assist developing countries will not be able to fully succeed (Janssen,
A number of policies and agreements have been launched by governments in recent
decades. Table 2 shows some recent important commitments and initiatives related to
climate change and energy efficiency that affect the manufacturing sector. From this
table, it can be seen that countries must continue to apply efforts to reduce energy
consumption, and energy efficiency is a spotlight topic.
According to Chartered Institute of Management Accountants (CIMA, 2010), the
manufacturing sector is seen as a source of stronger and more sustainable growth. As a
major source of energy consumption in manufacturing systems, machine tools can be an
important key to promoting more sustainability into this sector. For this reason, different
research approaches based on CNC machining have been carried out and appear to be of
great value to support the challenges faced by the sector.
Table 2 Recent policies, commitments, and Initiatives for energy saving
Country/region Content
Worldwide ‘United Nations Climate Change Conference Paris COP21’ (2015): keep the
rise in temperature below 2°C per year (COP21, 2015a).
Europe ‘2030 Framework’ (2014): new energy efficiency target of 27% or greater
by 2030.
China and USA ‘US-China Clean Energy Research Centre (CERC)’ (2014): 150 million
USD – CERC primarily researches advanced coal technologies, electric
vehicles, and enhanced energy efficiency (Climate Nexus, 2015).
EU ‘Energy Savings Opportunity Scheme (ESOS)’ (2014): the introduction of
regular energy audits for large enterprises (ESOS, 2015).
Germany ‘Energy Concept 2050’ (2010): Greenhouse gas emissions should have been
reduced by 40% by 2020, 55% by 2030 and at least by 80% by 2050
(Climate Action Plan 2050, 2015).
India ‘National Mission for Enhanced Energy Efficiency’ (2008): an initiative to
address national problems of inefficient energy use (India’s NAPCC, 2008).
China ‘Premier Wen Jiabao speech’ (2008): target to reduce energy consumption
for every 10,000 yuan (1,298 US dollars) of GDP by 20% by 2010, while
pollutant discharge should drop by 10% (Chow, 2008).
UK ‘CRC Energy Efficiency Scheme’ (2007): is a mandatory carbon emission
reporting and pricing scheme to cover large public and private sector
organisations (Carbon Trust, 2015).
Global ‘Energy Efficiency Standards and Labelling’ (1975*): aim to bring out
market transformation towards energy-efficient equipment (Janssen, 2010a).
Note: Date varies depending on country or region.
3.2 CNC machines and sustainability in the manufacturing industry sector
Production systems can be divided into two main energy consuming sources:
transportation and transformation of input raw material. The third industrial revolution in
the early 1970s landmarked the migration from manual production to automated systems,
in which machines controlled by computer hardware and software became predominant
to enhance productivity and/or quality of machining processes. Moreover, with the rise of
employment costs and the economy slowdown of most Western countries in the same
decade, CNC machines became predominant in manufacturing processes, displacing
Research on energy consumption and energy efficiency of machine tools 147
older technologies such as hydraulic tracers and manual machining (CNC Cookbook,
Nowadays, there are several types of CNC machines which can be found in a small
scale to large manufacturing companies. It can be used in industries for removing
materials where machining operations such as turning, milling, drilling, boring and so on
are performed; to transform materials, where the machining processes are performed on
thin metal plates and machines perform processes such as bending, forging, shearing,
plasma cutting, punching, laser cutting, forming, welding, etc.; in addition to,
electro-discharge machining (EDM) industries where sparks burn the material to be
Advances in machine technology, the design of machine and product, process
planning and machining strategies have been achieved in past years. Nevertheless,
machining processes have to change according to new technological developments,
environmental, legal and economic aspects, as previously described. This dynamic
system in which machine tools are included makes imperative the need for continuous
improvements of machining equipment, process planning, and machining strategies.
In this regard, an important action was taken by the International Organization for
Standardization (ISO). In 2010, this organisation drafted the standard Environmental
evaluation of machine tools (ISO14955-1, 2014), which includes three main parts:
1 eco-design methodology for machine tools
2 methods for testing of energy consumption of machine tools and functional modules
3 test pieces/test procedures and parameters for energy consumption on metal cutting
machine tools.
This ISO shows that different approaches can be adopted to improve the performance of
machine tools.
Newman et al. (2012) established that the energy consumed in CNC machining is
divided into a variety of categories and not only in driving the mechanical elements
directly to the cutting process. Accordingly, in recent years, several research topics have
been addressed to improve machining processes, which are commonly evaluated in terms
of energy consumption, productivity and surface quality. Table 3 summarises some topics
and related work on the field.
Table 3 Research topics on energy consumption of machine tools
Topic Related work
Eco-design of machine
Braungart et al. (2007), Lopes De Lacalle et al. (2011),
Kok-Soo and Sheng (2010), Strano et al. (2013)
Analysis of machining
parameter/machining configuration.
Newman et al. (2012), Rajemi et al. (2010),
Xue et al. (2010)
Machining operation sequence/tool
path optimisation.
Qudeiri et al. (2007), Lazoglu et al. (2009),
Kong et al. (2011)
Machining behaviour/motion
Avram and Xirouchakis (2011), Lv et al. (2015),
Tang et al. (2012)
Machining monitoring. Wang (2013), Segreto et al. (2013), Behrendt et al.
(2012), Hu et al. (2012)
Multi-objective optimisation of
machining parameters.
Wang et al. (2015), Yan and Li (2013)
Cloud manufacturing. Wang (2013), Xu (2012)
148 L.
oreira et al.
According to Lv et al. (2015), accurately characterisation of the energy consumed by
machining processes is a starting point to increase manufacturing energy efficiency and
reduce their associated environmental impacts. Hence, machine tools have been the focus
of research communities worldwide. Therefore, it is of utmost importance to comprehend
how energy consumption factor in machine tools has been addressed in order to enhance
their energy efficiency.
3.3 Energy consumption models and energy efficiency of CNC machines
Energy consumption models in manufacturing systems can be defined as the total amount
of energy required by the production process referred to the amount of production.
Furthermore, Schulz and Schiefer (1998) differentiated it into two ways: direct and
cumulative energy consumption, described in Figure 1.
Figure 1 Distribution of energy consumption in a production system
Source: Schulz and Schiefer (1998)
The direct energy consumption is a response of the power requirements of a machining
process, which can be divided into these four groups:
x cooling lubricant processing
x compressed air generation
x electrically powered auxiliary components
x CNC control package with main spindle and feed axis motors.
The energy distribution within machining processes depends on the characteristic of the
process (roughing or finishing) as well as the machine components. Zhou et al. (2015)
summarised the types of energy consumption decomposition for machine tool into five
different ways: composition system, operation status, energy attribute, main energy
consumption components and functional movement. Such definitions are important for
the development of energy consumption models and energy efficiency evaluation of
machine tools, which, according to Zhou et al. (2015), are prerequisites for energy
savings in manufacturing. The trends in these subjects are as follows:
x To achieve energy efficiency: multi-criteria optimisation approaches. Considering,
for instance, energy, quality, productivity, time, cost, etc.
Research on energy consumption and energy efficiency of machine tools 149
x Energy consumption modelling: in-process energy consumption monitoring,
consider kinematics of machines, consider NC code as input for calculation structure,
additional aspects of the model (tool wear, workpiece materials properties, etc.).
Energy consumption has not often been considered in manufacturing strategies during the
planning stage. However, this issue is becoming more prevalent, and is a topic of concern
in the board room in the last five years (O’Driscoll and O’Donnell, 2013). By integrating
energy consumption criteria into a process planning and operating structures, a reduction
in process energy demand is expected. Thus, energy modelling of a machine tool for
energy consumption prediction is of prime importance.
Accordingly, several energy consumption models for both the entire machine tool and
for the specific energy consumption of cutting processes have been developed. The
related work is summarised in Table 4.
Table 4 Energy models for machining processes
Author Type* Machining model
1 Wang et al.
i i i i toolchange i
idle working set up
2 Peng and
Xu (2013)
11 11
ij ij
nm nm
tate component state component i
ij ij
¦¦ ¦¦
3 Balogun
b b b r air air b cool c
EPt P t Pt P P kvt
Where Pb, Pr, Pcool and Pair represent the basic and ready state
powers, coolant pumping power and the average power for a
non-cutting approach and retract moves over the component,
respectively; tb, tr, and tc are the basic, ready and cutting times
respectively; tair is the total time duration of the non-cutting moves;
k (kJ/cm3) is the specific cutting energy; v (cm3/s) is the rate of
material processing.
4 Newman
et al. (2012)
Where P is the power demanded; f and h are
feed rate and depth of cut, respectively; and
D is the total volume removed.
5 He et al.
DE total spindle feed tool cool fix
This can be expanded to:
ms cs
me ce
total m c
i tool tool cool coe
servo fan e s
Pdt P t P t t
 
6 Avram and
This can be expanded to:
12 33 2
01 2 0 1
tt t t t
DE aY SY dY run c
tt t t t
E P dt P dt P dt P dt P dt
cc c c c
cc c c c
Notes: DE: direct energy, refers to models considering the entire machine tool system;
SE: specific energy refers to models considering the machining cutting process
150 L.
oreira et al.
Table 4 Energy models for machining processes (continued)
Author Type* Machining model
7 Mori et al.
SE 2
Where yi (Wh/cc) is the power
consumption per material removal unit,
and n is the number of experiments per
8 Kong et al.
DE machine const run time transient run time steady
EE E Ecut
 
 
The total energy consumption required by a machining process
was divided into four types: constant, run-time-transient,
run-time-ready and cut.
zv n
 
Where vf is the feed rate, n is the
rotational speed of the spindle, w is the
width of cut, b is the depth of cut, z is the
number of flutes of a cutter, and p and
Kcut are empirically determined fitting
9 Diaz et al.
cut air
EP t
Where Pavg is the average power demand
and Δt is the processing time. Pcut and
Pair are the cutting and air power,
SE 1
ek b
Where k is the machines constant, MRR is
the material removal rate and b represents
the steady-state specific energy.
10 Li and Kara
SE 1
Where C0 is the coefficient of the inverse
model, C1 is the coefficient of the
predictor, and MRR is the material
removal rate.
11 Draganescu
et al. (2003)
Where Pc is the necessary cutting power
at main spindle (kW), Z the material
removal rate (cm3/min) and Ecs the
specific consumed energy (kWh/cm3).
12 Li et al.
SE 01
SEC k k
Where k0 is the specific energy
requirement in cutting operations, k1 is
the specific coefficient of the spindle
motor, k2 is the constant coefficient of
machine tools and equals the sum of
standby power and the spindle motor’s
specific coefficient; n is the spindle speed
in rounds/second.
Notes: DE: direct energy, refers to models considering the entire machine tool system;
SE: specific energy refers to models considering the machining cutting process
Besides empirical models, the mechanistic approach has increasingly been applied to
develop energy consumption models. In this approach, the power required by the
machining process is a function of the cutting forces involved in the material removal
process and the cutting speed. There are different methods for estimating the cutting
Ehmann et al. (1997) traced the historical evolution of research in machining process
modelling and found that, in general, analytical models do not accurately predict the
Research on energy consumption and energy efficiency of machine tools 151
dynamic forces. Mechanistic and numerical methods are of more recent origin and rely
on empirical models and computer simulation techniques. The latter include both
mechanistic and finite element methods. It was concluded that a combination of these
methods is typically needed to obtain a working model and that mechanistic models
showed the most predictive power compared to other methods. For this reason, most
current research is steered towards mechanistic force models (Kadi et al., 2014).
The efficiency of CNC machining processes in energy terms is dependent on a
combination of factors including: operators’ experience and set-up of supporting tools;
base load which is determined by the auxiliary components of the machine; energy
management; machining cutting variables and strategies, and so on. The process itself,
such as roughing or finishing, is also a factor that impacts directly on the power demand.
Studies have also analysed the importance of periodic maintenance to improving the
energy efficiency of machine tools, please see Xu and Cao (2014).
Accordingly, different approaches were found and categorised into two stages of the
product life cycle energy efficiency enhancement, see Table 5.
Table 5 Research approaches related to energy efficiency of machining
Product life cycle energy efficiency enhancement approaches
design stage
Product design strategies Strategies for more sustainable part design
Waste material reduction
Easy-to-perform shapes
Machine tool innovation
New mechanical parts technologies
New parts design
New controllers
Machine tool auxiliary
components innovation
Cooling systems strategies/technology
Chip conveyor manners
New cutting tools (shape, technology,
execution stage
Non-productive machining Reduction of idle time:
Tool path topology/strategy
Process planning and scheduling strategies
Machining performance Strategies for cutting:
Tool path geometry
Number of passes
Tool selection
Machining parameters definition
Research approaches were divided into two stages: design and execution. These may also
be considered as ‘offline’ and ‘online’: the former focuses on the equipment of
machining process and product design, while the latter involves studies that enhance the
performance of machining processes as a function of machining cutting inputs and
strategies. For recent advances onto the first stage please refer to Zhang (2014).
Another topic is shop floor planning and scheduling solutions; however, this is out of
scope of this research. For more information on this please refer to Tang et al. (2015) and
Giret et al. (2015).
152 L.
oreira et al.
Figure 2 (a) Past study focuses and trends in machine tool energy efficiency (b) Study trends in
energy consumption model of machine tools
Source: Zhou et al (2015)
4 Results and analysis
A total of 1,584 documents were found by the methodology described in Section 2. The
documents were split into topics as presented in Figure 3. For instance, ‘Others’ category
refers to book chapters, short surveys, article in press and reports.
Research on energy consumption and energy efficiency of machine tools 153
The results show that the development of research related to energy consumption and
efficiency of CNC machines has increased significantly in recent years. From the Pareto
analysis, as shown in Figure 4, it can be noted that the period 2007 to 2015 accounts for
approximately 80% of the total research published over the last 20 years. Hence, as the
more representative period, the research documents published in this period are the focus
of investigation in this paper. Figure 5 brings a closer view of the documents published
per year during this period.
Figure 3 Documents published between 2007 and 2015 by type (see online version for colours)
Source: Adapted from Scopus® (
Considering the large amount of data under analysis - approximately 1,500 documents - a
cloud word construction procedure was identified as a feasible way to assess the most
frequent keywords. The result of applying this method is presented in Table 6. The details
are given in descending frequency order and provide an overview of research aspects
under investigation in the last years.
Table 6 Most representative keywords from documents published
Topic Details
Machining process Milling, laser, grinding, ultrasonic, boring, turning, welding,
drilling, and forging.
Machining process analysis Cut, wear, force, surface, cutter, spindle, feed, chatter and rough.
Research objectives Model, simulation, design and optimal.
Research techniques Regression analysis, response surface methodology and artificial
neural networks.
The substantial rise in research publications seen in Figure 4 from 2007 onwards can be
explained by legislative, economic and environmental aspects, such as commitments,
policies, initiatives, energy price rises as well as customer requirements for greener
154 L.
oreira et al.
In Figure 6, a division of the documents by its authors country shows the most
significant countries in terms of publications. From this point, a correlation between the
number of research published and actions taken by governments could be established, the
findings are analysed below.
Figure 4 Documents published by year between 1994 and 2015, total of 1,950 documents
(see online version for colours)
Source: Adapted from Scopus® (
Figure 5 Documents published by year between 2007 and 2015 (see online version for colours)
Source: Adapted from Scopus® (
Research on energy consumption and energy efficiency of machine tools 155
Figure 6 Documents by country between 2007 and 2015 (see online version for colours)
Source: Adapted from Scopus® (
Figure 7 Documents published by top 4 countries per year (see online version for colours)
Source: Adapted from Scopus® (
China, Germany, the USA and Japan are the most significant countries in this search,
accounting for 56% of the documents published in the last eight years. This information
suggests that these countries have been allocating greater efforts, when compared to other
countries, to improve machining techniques, processes and production systems through
research and development. Further, an analysis of the manufacturing output per country
in 2013, showed that those four countries together are responsible for 55% of world
156 L.
oreira et al.
manufacturing (Rhodes, 2016). This aspect, along with the commitments and legislations
made recently, such as ‘20/20/20 by 2020’, in 2007, ‘Energy Concept 2050’, in 2010,
‘Energy Efficiency Standards and Labelling’, in addition to target announcements for
reducing CO2 emissions, correlate well with those as the leading countries in Figure 6.
Figure 7 shows the leading countries’ publications by year. China is the most active
country, responsible for 27% of the documents published, followed by Germany, the
USA and Japan. The latter shows a steady output over the last 8 years, whilst China
showed a significant increase between 2009 and 2010, with a decrease from 2011 and
2013, and a subsequent substantial rise between 2013 and 2014, from 44 to 126
documents. Alike, Germany presented a similar curve of documents per year but with a
smaller amount of documents published. The USA showed a rise between 2007 and
2009, and a decrease from 2012 and 2014. As a result, the contribution of the USA and
Japan in 2014 was not as dominant on the amount of research publications in the area
under investigation as China was.
The slowdown in research publications in the USA between 2012 and 2014 can be
explained by a change in research investment topics. For instance, in 2012, President
Obama presented in his speech at the National Energy Action Month a high interest of his
government in cleaner and renewable energy sources, as well as to increase fuel
efficiency and to enhance US energy independence through domestic oil production
(White House, 2015a, 2015b). Another announcement of importance, at the same year,
by President Obama, was the Executive Order, Accelerating Investment in Industrial
Energy Efficiency. In his speech, he highlighted the expansion in the use of combined
heat and power (CHP) as a focus of investment to promote more efficient manufacturing
processes (White House, 2015c). Therefore, these announcements may have made effects
on research directions and, thus, can explain the drop in research publications in 2014, in
which only the US showed a decrease.
China emerged as the most significant country in terms of number of documents
published recently. In this country, the research development between the years 2013 and
2015 accounted for 50% of the total number of documents published over the entire
period analysed. This country is home to 20% of the world’s population and is a
fast-growing economy. The Chinese government has acknowledged that its current and
predicted resource usage is not sustainable, and is, therefore, encouraging improvements
in efficiency, technological innovations, and the use of renewable energy (Climate
Nexus, 2015).
Table 7 Summary of findings related to research published in China between 2007 and 2015
Topic Details
Most frequent documents keywords: Finite element method, optimisation, and algorithms.
Top three sources: Applied mechanics and materials, advanced materials
research and journal of cleaner production.
Top three affiliations: Chongqing University, Huazhong University of Science
and Technology and Zhejiang University.
Top three authors: He, Yan; Liu, Fei; and Zhao, Shengdun.
Most representative year: 2014.
Research on energy consumption and energy efficiency of machine tools 157
Considering the eminent high activity of research development in China recently, the
documents published in this country were further analysed. The findings are summarised
in Table 7.
The most frequent keywords found suggest that the computer science field has been
playing an important role in research related to machining processes in China.
Furthermore, it suggests that computer science has been an important field applied in
engineering to enhance machining process efficiency, which is also in accordance with
the trends and requirements towards the ‘fourth industrial revolution’ – Industry 4.0.
Figure 8 Documents published by top ten sources between 2007 and 2015 (see online version
for colours)
Source: Adapted from Scopus® (
Figure 9 Top ten affiliations worldwide (see online version for colours)
Source: Adapted from Scopus® (
158 L.
oreira et al.
Figure 8 shows the most significant sources in which documents were published
during from 2007. This can support students and the research community in finding
representative sources in their field, in addition to aiding the process of making decisions
upon the journal(s) in which to publish and to find relevant research. Identification of
affiliations (universities, institutes, research centres, etc.) and researchers that are
currently active in the area to be investigated is a valuable source for networking and
promotion of collaboration between different research groups from different countries or
Taking into account the geographic and demographic differences between the four
top countries, an investigation regarding the number of affiliations per country was
carried out. The results show that China and USA have the same number of affiliations,
with 160 in total; Germany showed 159; and Japan showed 142 affiliations. This shows
that there is only a slight discrepancy in the number of affiliations between those
The top ten affiliations (universities, research centres and institutes) can be seen in
Figure 9. Note that six out of the ten affiliations are located in China. It suggests that
energy consumption and efficiency of machine tools is a topic of high interest for some
Chinese universities, and efforts have been allocated for research in this field. The
German Fraunhofer-Institut fur Wekzeugmaschinen shows notable activity, followed by
the American University of California, Berkeley.
The most significant authors related to CNC machines and energy are presented in
Figure 10. This information is useful to support researchers to follow experienced
researchers in the field.
Nowadays, with the advance of science and research network websites, it has become
easier to track authors and publications. Some useful websites are summarised in Table 8.
It shows important sources of knowledge which can support research in academia.
Table 8 Useful websites to support research development
Name Description Link
Science Direct Leading full-text scientific database.
Scopus Largest abstract and citation database
of peer-reviewed literature.
IEEE Largest professional association for
the advancement of technology.
SCImago Journal &
Country Rank
Portal of scientific indicators for
journals and countries.
Research gate Scientific and research networking
Twitter Networking website.
The representative activity of European countries shown in Figure 10 presents a good
correlation with policies launched recently. Moreover, a recent report from the European
Commission Energy Efficiency Communication (2014), presented that energy
efficiency policies are delivering tangible results.
Germany and Belgium appeared as the most frequent countries of the universities in
which the researchers are currently based on. Although Belgium has not appeared on the
previous graphs, it shows that there are at least three researchers with active work on this
field in this country on the number of publications per country, Belgium is in 14th
position, after France (11th), Switzerland (12th) and Canada (13th).
Research on energy consumption and energy efficiency of machine tools 159
It is important to mention that the analysis carried out in this paper does not have the
intention of ranking countries, institutes, universities or authors, but to highlight the
representative ones in the field under analysis as determined from the leading online
databases and their importance for the planning stage of research; as well as to support a
correlation between research development and real world aspects, such as government
announcements in recent years related to energy saving and climate change.
Figure 10 Top authors between 2007 and 2015 (see online version for colours)
Source: Adapted from Scopus® (
Figure 11 Documents published divided by subject areas (see online version for colours)
Source: Adapted from Scopus® (
160 L.
oreira et al.
The documents obtained from the data gathered were further divided into their subject
areas, see Figure 11. It shows that the engineering area is responsible for approximately
77%, followed by materials science (22%) and computer science (14%).
5 Conclusions
The research presented in this paper provides key information that supports the
development of the scenario of research related to energy consumption and efficiency of
CNC machining processes.
Research publications related to energy consumption and energy efficiency of
machine tools have increased significantly since 2007. A total of 1,584 documents were
gathered for further investigation. The findings are summarised as follows:
x China was found as the most active country in terms of volume of research published
(27%), followed by the Germany (13%) and the USA (11%), since 2007.
x China, Germany, the USA and Japan ate the most significant countries: together,
these were responsible for 56% of the documents published in the last eight years.
x In China, 50% of the total number of documents was published since 2013.
x 2014 was identified as the most significant year for research publications (19%).
x Applied Mechanics and Materials, Chongqing University and Reimund Neugebauer,
were the most significant source, affiliation and author among all countries,
x There was found a strong relationship between government’s actions and research
development on energy consumption and efficiency of machine tools.
The information obtained by the technology-foresight-based methodology shows great
potential to support research development.
Meanwhile, different approaches to promoting better use of energy in CNC
machining process were highlighted, such as machining monitoring, eco-design for
equipment and product, cloud manufacturing, energy consumption modelling, and so on.
Additionally, it suggests that the computer science and engineering fields together are
leading research development to enhance machining efficiency.
A correlation between real world aspects and the scenario of research during the last
eight years was drawn and showed that governments’ commitments and initiatives related
to energy saving and climate change play a leading role in research development in the
manufacturing sector.
In summary, aspects such as rising energy prices, climate change agreements, greener
customer behaviour, as well as increasing demand for customised products have led the
manufacturing industry sector to adopt strategies to implement sustainability. Thus,
energy efficiency is going to remain a worldwide target in the manufacturing industry
Further investigations should be carried out based on the data of each country, in
order to provide a deeper understanding of the research scenario with a more detailed
viewing. Such findings would support the decision-making process for a more effective
Research on energy consumption and energy efficiency of machine tools 161
use of funding applied to research, as well as to help research community in defining
trends and gaps in this field.
Avram, O.I. and Xirouchakis, P. (2011) ‘Evaluating the use phase energy requirements of a
machine tool system’, Journal of Cleaner Production, Vol. 19, Nos. 6–7, pp.699–711.
Balogun, V.A. and Mativenga, P.T. (2013) ‘Modelling of direct energy requirements in mechanical
machining processes’, Journal of Cleaner Production, Vol. 41, pp.179–186.
Behrendt, T., Zein, A. and Min, S. (2012) ‘Development of an energy consumption monitoring
procedure for machine tools’, CIRP Annals – Manufacturing Technology, Vol. 61, No. 1,
BP Energy Outlook 2035 (2014) [online] (accessed 5 December
Braungart, M., McDonough, W. and Bollinger, A. (2007) ‘Cradle-to-cradle design: creating healthy
emissions – a strategy for eco-effective product and system design’, Journal of Cleaner
Production, Vol. 15, Nos. 13–14, pp.1337–1348.
Carbon Trust (2015) CRC Energy Efficiency Scheme [online]
(accessed 7 December 2015).
Chartered Institute of Management Accountants (CIMA) (2010) The Global Manufacturing
Sector: Current Issues, CIMA Sector Report, London, ISBN: 978-1-85971-674-8 [online]
Global_manufacturing_report.pdf (accessed 7 December 2015).
China Statistical Yearbook (2014) [online]
AnnualData./ (accessed 6 December 2015).
Chow, G.C. (2008) ‘China’s energy and environmental problems and policies’, Asia-Pacific
Journal of Accounting and Economics, Vol. 15, No. 1, pp.57–70.
Climate Action Plan 2050 (2015) [online]
climate/details-climate/artikel/scientific-bases-for-the-climate-action-plan-2050-1/ (accessed
7 December 2015).
Climate Nexus (2015) [online]
and-energy-policy#energy and climate (accessed 7 December 2015).
CNC Cookbook (2015) [online] (accessed
3 December 2015).
COP21 (2015a) [online] (accessed
13 December 2015).
COP21 (2015b) World Awaits Landmark Climate Deal [online]
science-environment-35082895 (accessed 13 December 2015).
Diaz, N., Redelsheimer, E. and Dornfeld, D. (2011) ‘Energy consumption characterization and
reduction strategies for milling machine tool use’, in Proceedings of the 18th CIRP
International Conference on Life Cycle Engineering, Braunschweig, Germany, pp.263–267.
Draganescu, F., Gheorghe, M. and Doicin, C.V. (2003) ‘Models of machine tool efficiency and
specific consumed energy’, Journal of Materials Processing Technology, Vol. 141, No. 1,
Ehmann, K.F., Kapoor, S.G., Devor, R.E. and Lazoglu, I. (1997) ‘Machining process modeling: a
review’, Journal of Manufacturing Science & Technology, Vol. 119, No. 4B, pp.655–663.
Energy Savings Opportunity Scheme (ESOS) (2014) [online]
(accessed 06 December 2015).
162 L.
oreira et al.
European Commission – Energy Efficiency Communication (2014) Energy Efficiency and its
Contribution to Energy Security and the 2030 Framework for Climate and Energy Policy,
COM(2014) 520 Final, Brussels [online]
2014_energy_efficiency_communication.pdf (accessed 7 December 2015).
Geller, H., Harrington, P., Rosenfeld, A.H., Tanishima, S. and Unander, F. (2006) ‘Polices for
increasing energy efficiency: thirty years of experience in OECD countries’, Energy Policy,
Vol. 34, No. 5, pp.556–573.
Giret, A., Trentesaux, D. and Prabhu, V. (2015) ‘Sustainability in manufacturing operations
scheduling: a state of the art review’, Journal of Manufacturing Systems, Vol. 37, No. 1,
Gupta, K., Laubscher, R.F., Davim, J.P. and Jain, N.K. (2015) ‘Recent developments in sustainable
manufacturing of gears: a review’, Journal of Cleaner Production, Vol. 112, No. 4,
Hu, S., Liu, F., He, Y. and Hu, T. (2012) ‘An on-line approach for energy efficiency monitoring of
machine tools’, Journal of Cleaner Production, Vol. 27, pp.133–140.
India’s National Action Plan on Climate Change (NAPCC) (2008) [online]
international/key-country-policies/india/climate-plan-summary (accessed 6 December 2015).
International Energy Agency (2012) Energy Technology Perspectives 2012 – Pathways to a Clean
Energy System, Executive Summary, ISBN: 978-92-64-17488-7.
International Organization for Standardization ISO14955-1 (2014) Environmental Evaluation of
Machine Tools, ISO, Geneva.
Janssen, R. (2010a) [online]
energy-efficiency-requirements-building-foundations (accessed 4 December 2015).
Janssen, R. (2010b) Harmonising Energy Efficiency Requirements – Building Foundations for
Co-operative Action, ICTSD Issue Paper No. 14, International Centre for Trade and
Sustainable Development, Geneva, Switzerland.
Kadi, El.H., Deiab, I.M. and Khattab, A.A. (2014) ‘Predicting cutting forces in aluminum using
polynomial classifiers’, Eighth International Conference on Materials Sciences, CSM8-ISM5,
Physics Procedia, Vol. 55, pp.237–242.
Kok-Soo, T. and Sheng, I.L.S. (2010) ‘Eco-efficient product design using theory of inventive
problem solving (TRIZ) principles’, American Journal of Applied Sciences, Vol. 7, No. 6,
Kong, D., Choi, S., Yasui, Y., Pavanaskar, S., Dornfeld, D. and Wright, P. (2011) ‘Software-based
tool path evaluation for environmental sustainability’, Journal of Manufacturing Systems,
Vol. 30, No. 4, pp.241–247.
König, J. (2010) ‘Energieeffiziente Produktherstellung’ in Uhlmann 2012: FUTUR
Produktionstechnik für die Zukunft, Vol. 12, No. 2, pp.12–13.
Lazoglu, I., Manav, C. and Murtezaoglu, Y. (2009) ‘Tool path optimization for free form surface
machining’, CIRP Annals – Manufacturing Technology, Vol. 58, No 1, pp.101–104.
Li, W. and Kara, S. (2011) ‘An empirical model for predicting energy consumption of
manufacturing processes: a case of turning process’, in Proceedings of the Institution of
Mechanical Engineers, Part B, Journal of Engineering Manufacture, Vol. 225, No. 9,
Liu, F., Wang, L.Q. and Liu, G.J. (2013) ‘Content architecture and future trends of energy
efficiency research on machining systems’, Journal of Mechanical Engineering, Vol. 49,
No. 19, p.87.
Lopes De Lacalle, L.N., Zulaika, J.J. and Campa, F.J. (2011) ‘An integrated process machine
approach for designing productive and lightweight milling machines’, International Journal of
Machine Tools and Manufacture, Vol. 51, Nos. 7–8, pp.591–604.
Lv, J., Tang, R., Jia, S. and Liu, Y. (2015) ‘Experimental study on energy consumption of
computer numerical control machine tools’, Journal of Cleaner Production, Vol. 112, No. 5,
Research on energy consumption and energy efficiency of machine tools 163
Moreira, L.C., Li, X.X., Li, WD., Lu, X. and Fitzpatrick, M.E. (2015) ‘Research publications on
energy consumption and efficiency of machine tools: an overview’, Paper presented at the
16th International Manufacturing Conference in China, Hangzhou, China, 22–25 October.
Mori, M., Fujishima, M., Inamasu, Y. and Oda, Y. (2011) ‘A study on energy efficiency
improvement for machine tools’, CIRP Annals-Manufacturing Technology, Vol. 60, No. 1,
Newman, S.T., Nassehi, A., Imani-Asrai, R. and Dhokia, V. (2012) ‘Energy efficient process
planning for CNC machining’, CIRP Journal of Manufacturing Science and Technology,
Vol. 5, No. 2, pp.127–136.
O’Driscoll, E. and O’Donnell, G.E. (2013) ‘Industrial power and energy metering – a state-of-the-
art review’, Journal of Cleaner Production, Vol. 41, pp.53–64.
Peattie, K. (1992) Green Marketing, Pitman, London.
Peng, T. and Xu, X. (2013) ‘A universal hybrid energy consumption model for CNC machining
systems’, in Reengineering Manufacturing for Sustainability: Proceedings of the 20th CIRP
International Conference on Life Cycle Engineering, Singapore, pp.251–256.
Qudeiri, J.A., Yamamoto, H. and Ramli, R. (2007) ‘Optimization of operation sequence in CNC
machine tools using genetic algorithm’, Journal of Advanced Mechanical Design, Systems,
and Manufacturing, Vol. 1, No 2, pp.272–282.
Rajemi, M.F., Mativenga, P.T. and Aramcharoen, A. (2010) ‘Sustainable machining: selection of
optimum turning conditions based on minimum energy considerations’, Journal of Cleaner
Production, Vol. 18, Nos. 10–11, pp.1059-1065.
Rhodes, C. (2016) Manufacturing: International Comparisons, House of Commons Library,
Briefing Paper, No. 05809.
Schulz, H. and Schiefer, E. (1998) ‘Prozessfuhrung und Energiebedarf bei spanenden
Fertigungsverfahren’, ZwF, Vol. 93, No. 6, pp.266–271, ISSN: 0947-0085.
Scopus® [online] (accessed 7 December).
Segreto, T., Teti, Simeone, A. and Teti, R. (2013) ‘Multiple sensor monitoring in Nickel alloy
turning for tool wear assessment via sensor fusion’ in Procedia CIRP: Eighth CIRP
Conference on Intelligent Computation in Manufacturing Engineering, Vol. 12, pp.85–90.
Strano, M., Monno, M. and Rossi, A. (2013) ‘Optimized design of press frames with respect to
energy efficiency’, Journal of Cleaner Production, Vol. 41, pp.140–149.
Tang, D., Dai, M., Salido M. A. and Giret, A. (2015) ‘Energy-efficient dynamic scheduling for a
flexible flow shop using an improved particle swarm optimization’, Computers in Industry,
Vol. 30, No. 3, pp.223–232.
Tang, D., Li, L. and Du, K. (2006) ‘On the developmental path of Chinese manufacturing industry
based on resource restraint’, Jiangsu Social Sciences, Vol. 4, pp.51–58.
Tang, R., Jia, S. and Lv, J. (2012) ‘Therblig-based energy demand modeling methodology of
machining process to support intelligent manufacturing’, Journal of Intelligent Manufacturing,
Vol. 25, pp.913–931.
US Energy Information Administration (EIA) (2010) Annual Energy Review, Technical report
DOE/EIA-0384, Office of Energy Statistics, US Department of Energy, Washington, DC,
[online] (accessed 03
December 2015).
Wang, L. (2013) ‘Machine availability monitoring and machining process planning towards cloud
manufacturing’, CIRP Journal of Manufacturing Science and Technology, Vol. 6, No. 4,
Wang, S., Lu, X., Li, X.X. and Li, W.D. (2015) ‘A systematic approach of process planning and
scheduling optimization for sustainable machining’, Journal of Cleaner Production, Vol. 87,
164 L.
oreira et al.
White House (2014) U.S.-China Announcement on Climate Change and Clean Energy
Cooperation, Fact-sheet, the White House, Washington, DC [online] https://www.whitehouse.
clean-energy-c (accessed 4 December 2015).
White House (2015a) [online]
presidential-proclamation-national-energy-action-month-2012 (accessed 05 December 2015).
White House (2015b) [online]
blueprint_for_a_secure_energy_future_oneyear_progress_report.pdf (accessed 5 December
White House (2015c) [online]
order-accelerating-investment-industrial-energy-efficiency (accessed 5 December 2015).
Xu, W. and Cao, L. (2014) ‘Energy efficiency analysis of machine tools with periodic
maintenance’, International Journal of Production Research, Vol. 52, No. 18, pp.5273–5285.
Xu, X. (2012) ‘From cloud computing to cloud manufacturing’, Robotics and Computer Integrated
Manufacturing, Vol. 28, No. 1, pp.75–86.
Xue, D., Lasemi, A. and Gu, P. (2010) ‘Recent development in CNC machining of freeform
surfaces: a state-of-the-art review’, Computer-Aided Design, Vol. 42, No. 7, pp.641–654.
Yan, J. and Li, L. (2013) ‘Multi-objective optimization of milling parameters – the trade-offs
between energy, production rate and cutting quality’, Journal of Cleaner Production, Vol. 52,
Zhang Y. (2014) ‘Review of recent advances on energy efficiency of machine tools for
sustainability’ in Proceedings of the Institution of Mechanical Engineers, Part B, Journal of
Engineering Manufacture, Vol. 62, No. 13, pp.606–610.
Zhou, L., Li, J., Li, F., Meng, Q., Li, J. and Xu, X. (2015) ‘Energy consumption model and energy
efficiency of machine tools: a comprehensive literature review’, Journal of Cleaner
Production, Vol. 112, No. 5, pp.3721–3734.
... Computer numerical control (CNC) machining processes have increasingly drawn the focus of research communities worldwide in the past 20 years. A substantial rise in research publication has been identified in the last 8 years by Moreira et al. [1]. Process control of CNC machining processes is used to achieve two major objectives of manufacturing systems: maximising productivity and enhancing the part quality [2]. ...
Conference Paper
Full-text available
Intelligent control algorithms are a key enabling technology for the smart factory concept of Industry 4.0. They must cope with complex, nonlinear and time-varying processes. Die and mould operations, in particular to milling, are known for their complexity; and improvements to process quality are of utmost concern, owing to economic factors, the drive to reduce lead times, and increasingly stringent customer requirements. Hence, a hybrid artificial intelligence (AI) controller (HaiC) is designed to supervise the spindle speed cutting profile of machining processes to ensure the desired surface quality of the machined part is achieved. It is comprised of artificial neural networks (ANNs) and fuzzy logic (FL) predictive models, and a proportional-derivative (PD) loop, to promote an efficient control based on the manufacturing requirements. Milling experiments were carried out for data collection for the development of the predictive models. The control part is developed and implemented in a simulation environment, and its performance is assessed through several machining scenarios. The results show that the controller provides high-accuracy spindle speed control for assuring surface quality in milling operations. Furthermore, it can also be used for offline optimisation of the spindle speed at the process planning phase.
The manufacturers are facing unprecedented pressures to decrease their energy intensities in the context of global warming which is believed as being caused by human-produced greenhouse gas emissions. However, it is still challenging to achieve this due to the lack of proper tools for energy consumption prediction for complex machining processes. To bridge this gap, a new framework integrating energy consumption analysis into the current tool-chain of manufacturing engineers was established by fusing the energy consumption evaluation into the virtual manufacturing process. And to eliminate ambiguity of results, a novel joint spatially and temporally controlled boundary of machining energy was first introduced. The proposed method was further extended to enable the assessment of carbon footprint and comprehensive cost, the other two critical pillars of sustainability. A multi-perspective analysis of energy consumption characteristics of a complex machining process was demonstrated followed by the assessment of carbon footprint and comprehensive cost, based on the developed application for the proposed framework after being fully validated by experiments. The aforementioned framework opens a door for improving sustainability of machining processes.
In machining the selection of cutting parameters is done normally on the basis of the optimization of either cost or production rate or profit. But due to government policies the environmental aspects also become important. Major environmental impacts are due to electrical energy consumption in machine tool during machining. So it is essential to minimise energy consumption. This criteria of minimisation of energy should also be considered while selecting the cutting parameters along with the other criteria in view of the present day requirements to reduce pollution. In the present study a multiobjective mathematical model is presented for optimizing energy consumption, processing time and cost during a turning process. Experimental studies are used for validating the model. The optimization of experimental values and theoretical model is done using same range of parameters. Results are compared and discussed.
Full-text available
Due to increasing energy requirements and associated environmental impacts, nowadays manufacturing companies are facing the emergent challenges to meet the demand of sustainable manufacturing. Most existing research on reducing energy consumption in production scheduling problems has focused on static scheduling models. However, there exist many unexpected disruptions like new job arrivals and machine breakdown in a real-world production scheduling. In this paper, it is proposed an approach to address the dynamic scheduling problem reducing energy consumption and makespan for a flexible flow shop scheduling. Since the problem is strongly NP-hard, a novel algorithm based on an improved particle swarm optimization is adopted to search for the Pareto optimal solution in dynamic flexible flow shop scheduling problems. Finally, numerical experiments are carried out to evaluate the performance and efficiency of the proposed approach.
Full-text available
Problem statement: In recent years, much attention has been focused on the eco-efficiency of product development. The majority of environmental decisions are only made in the later stages of product development where not much modification can be done. To produce eco-efficient products, environmental decisions ought to be considered in the early stages of product development. With the demand of developing more eco-efficient products, designers are found to be lacking the appropriate design tools and guidelines. Approach: Products were designed to solve problems. Therefore, we suggest the usage of the 40 principles of TRIZ to generate eco-efficient product designs. The 40 principles of TRIZ is one of the fundamental tools of TRIZ. We studied the design features of different water filters, washing machines and power drills to correlate the elements of eco-efficiency and the principles of TRIZ. Results: From the case studies, it was shown that there is a correlation between eco-efficient elements and TRIZ principles in existing products. The information obtained from the product case studies alongside with the study of the individual TRIZ principles resulted in the formation of a new tool. This new tool was called the TRIZEE Design Tool. After that, literature review on the commonly practiced design methodologies were carried out. A new methodology termed TRIZEE Design Methodology was developed. New tools and existing tools were incorporated within this methodology. Conclusion: We proved that there is a correlation between eco-efficient elements and the 40 principles of TRIZ. Through this research, a new design methodology is also formed to that can be a guideline for designers.
Full-text available
To cope with the serious situations such as rising energy price, the global resource depletion and climate warming, improving energy efficiency in manufacturing becomes an inevitable trend for energy conservation, emissions reduction and sustainability. As the basis energy consumed device in manufacturing system, machine tools’ energy consumption modeling and energy efficiency evaluation are the prerequisite for energy-saving in manufacturing. A comprehensive literature review is needed because some related concepts are not clear and the precision of models still need to be promoted in this field. Firstly, the connotation of energy efficiency for machine tools was discussed. It was pointed out that specific energy consumption refer to the mapping relationship between energy consumption and the processing parameters, which reflected the energy efficiency of machine tools from the perspective of effective input and output. Secondly, design, scheduling management, optimization and environment assessment of machine tools were introduced based on energy efficiency. Thirdly, the existing energy consumption models were classified into three categories in this work:1) the linear type of cutting energy consumption model based on material remove rate,2) detailed parameter type of cutting energy consumption correlation models and 3)process oriented machining energy consumption model. Finally, conclusions were drawn for the future study in two major points: 1) the accuracy of current energy consumption models could be improved through introducing the correlation analysis of machine tools, parts, tools and processing condition, 2) more scientific evaluation index system is required for the assessment and test of machining tools’ energy efficiency.
Environment awareness is of the utmost importance to all socially responsible manufacturers. To be competitive on a global scale manufacturing needs to be aligned with various strict environmental regulations. The manufacturing industry at large is striving to improve productivity and product quality while maintaining a clean and sustainable environment. This can only be achieved by adopting sustainable techniques of manufacturing which include minimizing the number of manufacturing steps by employing advanced and alternative methods, environment-friendly lubricants and lubrication techniques while machining, reducing wastage, active waste management and minimizing energy consumption etc. Gear manufacturing industries, the major service providers to all other industrial and manufacturing segments are also focusing on to implement the techniques targeting overall sustainability. Some of the recent developments to achieve sustainability in gear manufacturing can be summarized as: reducing the use of mineral-based cutting fluids by employing alternative lubrication techniques i.e. minimum quantity lubrication (MQL) and dry machining; material saving, waste reduction , minimizing energy consumption and maintaining economic efficiency by reducing the number of gear manufacturing stages; eliminating the necessity of finishing processes by utilizing advanced methods such as gear rolling and wire electric-discharge machining (WEDM) and finally increasing productivity by minimizing tool wear at high gear cutting speeds through the use of alternative tool materials and coatings. This paper reviews and amasses the current state of technology for sustainable manufacturing of gears and also recommends ways to improve the productivity and quality while simultaneously ensuring environmental sustainability.
Sustainability in manufacturing systems is an urgent requirement for today's manufacturing companies. This paper focuses on sustainable manufacturing operations scheduling, a subject which has been attracting increasing interest from researchers in recent years. This paper presents a state of the art review of this field. First, it characterizes what can be considered as sustainable manufacturing operations scheduling, and introduces the relevant challenges and issues. An analysis of the literature is then proposed, and organized according to three keys. The shortcomings in the literature are then discussed in depth, and subsequently urgent problems that must be solved through research in order to meet industry requirements are pointed out.
Due to the high power consumption of machine tools in the manufacturing plants, study of the energy efficiency of machine tools has been the urgent need for sustainability. This article is focused on a comprehensive literature review about energy-efficient machine tools, including the analysis of energy loss, the modeling, and evaluating of energy efficiency of machine tools. These techniques are applicable for the design of new machine tools, and the analysis or redesign of the existing machine tools. Furthermore, some limitations and barriers of the previous studies on reducing machine tool energy consumption are discussed and outlined. The significant potential toward improving the energy efficiency of machine tools is presented, and some challenges are identified and summarized.
The lack of effective process planning and scheduling solutions for the sustainable management of machining shop floors, whose manufacturing activities are usually characterized by high variety and low volume, has been crippling the implementation of sustainability in companies. To address the issue, an innovative and systematic approach for milling process planning and scheduling optimization has been developed and presented in this paper. This approach consists of a process stage and a system stage, augmented with intelligent mechanisms for enhancing the adaptability and responsiveness to job dynamics in machining shop floors. In the process stage, key operational parameters for milling a part are optimized adaptively to meet multiple objectives/constraints, i.e., energy efficiency of the milling process and productivity as objectives and surface quality as a constraint. In the consecutive system stage, to achieve higher energy efficiency and shorter makespan in the entire shop floor, sequencing/set-up planning of machining features/operations and scheduling for producing multiple parts on different machines are optimized. Artificial Neural Networks are used for establishing the complex nonlinear relationships between the key process parameters and measured datasets of energy consumption and surface quality. Several intelligent algorithms, including Pattern Search, Genetic Algorithm and Simulated Annealing, are applied and benchmarked to identify optimal solutions. Experimental tests indicate that the approach is effective and configurable to meet multiple objectives and technical constraints for sustainable process planning and scheduling. The approach, validated through industrial case studies provided by a European machining company, demonstrates significant potential of applicability in practice.