Modeling Method for Flexible Energy Behaviors in CNC Machining Systems
Li et al. Chin. J. Mech. Eng.
Modeling Method for Flexible Energy Behaviors in CNC Machining Systems
Yu‑Feng Li 0 2 3
Yu‑Lin Wang 1
Yan He 2
Yan Wang 4
Shen‑Long Lin 2
0 Economics and Business Administration, Chongqing University , Chongqing 400030 , China
1 School of Mechanical Engineering, Nanjing University of Science and Technology , Nanjing 210094 , China
2 State Key Laboratory of Mechanical Transmission, Chongqing University , Chongqing 400030 , China
3 Economics and Business Administration, Chongqing University , Chong‐ qing 400030 , China
4 Department of Computing, Mathematics and Engineering, University of Brighton , Brighton , UK
CNC machining systems are inevitably confronted with frequent changes in energy behaviors because they are widely used to perform various machining tasks. It is a challenge to understand and analyze the flexible energy behaviors in CNC machining systems. A method to model flexible energy behaviors in CNC machining systems based on hierarchical objected‑ oriented Petri net (HOONet) is proposed. The structure of the HOONet is constructed of a high‑ level model and detail models. The former is used to model operational states for CNC machining systems, and the latter is used to analyze the component models for operational states. The machining parameters having great impacts on energy behaviors in CNC machining systems are declared with the data dictionary in HOONet models. A case study based on a CNC lathe is presented to demonstrate the proposed modeling method. The results show that it is effective for modeling flexible energy behaviors and providing a fine‑ grained description to quantitatively analyze the energy consumption of CNC machining systems.
Energy behaviors; CNC machining systems; Modeling method; HOONet
1 Introduction
Presently, manufacturing companies are not only facing
strong economic pressure due to complex and diverse
economic trends of shorter product life cycles, increased
diversity in customer demand, and the globalization
of production activities but are also seeking to meet
emerging industrial criterions including sustainability
for environmental benefits [
1, 2
]. According to a report
by Schipper [3], manufacturing is responsible for 84%
of energy-related industrial CO2 emissions and 90% of
industrial energy consumption. Sustainable
manufacturing has been hailed for manufacturing enterprises to
achieve sustainable production and improve their
sustainable competitive advantage [
4
]. Computer Numerical
Control (CNC) machining systems are the key players for
metal cutting in manufacturing activities. Approximately
95% of the environmental impact of CNC machining
systems is attributed to electrical energy consumption
during the utilization phase [
5
]. Therefore, a thorough
analysis of energy consumption in CNC machining
systems is of utmost importance, to implement sustainable
manufacturing [
6
].
As a prerequisite, it is important to understand and
analyze how electrical energy use or power demanded
is consumed in CNC machining processes. Most
studies have been based on machining parameters to analyze
energy consumption for CNC machining systems.
Draganescu et al. [
7
] statistically modeled the relationship
between energy consumption and machining
parameters using the Response Surface Method. Diaz et al. [
8
]
and Velchev et al. [
9
] characterized the specific energy
of machine tools as a function of material removal rate.
Li et al. [
10
] established an empirical model of energy
consumption based on power measurements under
various cutting conditions with different machining
parameters. Lv et al. [
11
] investigated the energy
characteristics related to machining parameters and proposed
the power models of CNC machining systems through
an experimental method. Camposeco-Negrete [
12
]
modeled energy consumption of machining parameters for
a specific lathe machine tool with the Response Surface
Method. Liu et al. [
13
] characterized the energy
consumption of machining parameters for a specific milling
machine tool. Sun et al. [
14
] described the relationship
between the specific energy consumption and the
production rate for ball milling. Shin et al. [
15
] presented
a component-based energy-modeling methodology to
implement online optimization. These studies mainly
focused on identifying critical machining parameters for
analyzing energy consumption, and energy
consumption was modeled as a function of certain machining
parameters.
Some researchers have focused on modeling the energy
consumption of components to analyze the energy
consumption in CNC machining system. Gutowski and
Kordnowy broke down the energy consumption of
machining systems according to functional components
such as computer and fans, servos, coolant pump,
spindle, tool changer, and so on [
16–18
]. He et al. [
19
]
modeled the total energy consumption of CNC machining by
summing up the energy consumed by the spindle, feed,
t (...truncated)