Carbon Emission Modeling and Analysis in Manufacturing Process for Numerical Control Machine Tools

LIU Xiao-long (劉曉龍)， LIU Zhi-jie (劉志杰)， LIN Cheng-xin(林成新)， BAI Bo(柏 博)

Transportation Equipments and Ocean Engineering College, Dalian Maritime University, Dalian 116024, China

Carbon Emission Modeling and Analysis in Manufacturing Process for Numerical Control Machine Tools

LIU Xiao-long (劉曉龍)， LIU Zhi-jie (劉志杰)*， LIN Cheng-xin(林成新)， BAI Bo(柏 博)

TransportationEquipmentsandOceanEngineeringCollege,DalianMaritimeUniversity,Dalian116024,China

Reducing carbon emissions (CEs) is the urgent demand all over the world. In order to realize the low-carbon numerical control(NC) machining, the evaluation model of a part’s manufacturing carbon emission with NC machine tools was built by considering the influences of the cutting tool geometrical parameters. The manufacturing CEs were produced by electric power, cutting tools, and cutting fluid consumed in manufacturing process. The parameters of cutting tools affected not only the CEs, but also the machining quality. Then the actual constraint models of the machine performance, machining quality were given in order to optimize the cutting parameters and achieve the low-CEs. Finally, a case was given to analyze the influences of the cutting tool angles on the manufacturing CEs. The results show that the CEs decrease as the rake angle and edge angle increase under the constraints of the machine specifications and machining quality.

carbonemission(CE);low-carbonmanufacturing;numericalcontrol(NC)machining;cuttingtoolangle

Introduction

Low-carbon emissions(CEs) have become equally important with the function, performance, quality, and cost for a product. According to statistics, nearly a third of the world’s energy consumption and 36% carbon dioxide emissions attribute to manufacturing industries[1]. How to reduce CEs is a urgent task for manufacturing industry.

Numerical Control(NC) machining technology has been widely used in manufacturing industry. The cutting parameters are important for the machining quality, CEs,etc. Some scholars have studied the cutting parameters optimization for low-carbon manufacturing. Lietal.[2]presented the CEs quantitative method of machining system based on generalized boundary. In additional, they built the multi-objective optimization model, which took the minimum cutting time and the lowest CEs as the optimization objectives, and the spindle speed and feed rate as the optimization variables[3]. Based on LCA, Caoetal.[4]analyzed the CEs of a machine tool during the life cycle including the stages of manufacturing, usage, transportation and disposal. Lietal.[5]proposed a CE model for machine tool manufacturing process based on Petri net, and proposed the dynamic quantification methods for CE in the manufacturing process. Rajemietal.[6]studied the optimal cutting conditions to decrease the energy consumption.

In NC turning process, the parameters of the cutting tools influence not only the machining quality, machining stability and production efficiency, but also the manufacturing CEs. So the analysis and optimization of the parameters of the cutting tools are important for reducing the CEs. In this paper, the evaluation model of the manufacturing CEs has been proposed so as to analyze and optimize the parameters of the cutting tools.

1 CE Modeling in Manufacturing Process

1.1 CE boundary definition in manufacturing stage

To evaluate CE, the boundary of the CE is firstly defined. In general, the CE of a product or part in each life cycle stage includes the CEs caused by use of raw materials, manufacturing, distribution, use, and end of life stages. In the manufacturing stage, the CEs include the direct and indirect ones. The direct emission sources can be classified into stationary combustion, mobile combustion, process emissions, and fugitive emissions[7]. The indirect emission is often caused by consumed electricity and other resources. For mechanical machining, the emission is mainly indirectly caused by electricity consumption and auxiliary materials consumption. The scrap processing will cause CE. But they can be reused and will partly reduce the CE of the raw material extraction. So in this paper, the manufacturing CEs include the emissions caused by electricity, cutting fluid, and cutting tool consumption. The parameters of cutting tools affect the machining quality, cutting forces, power and in turn the CEs. In the NC machining process, the cutting tool angle includes the cutting tool rake angle (CTRA)γ, tool clearance anglea0, side angle, inclination angle, cutting tool edge angle (CTEA)κ,etc[8]. Meanwhile, the CTRA and CTEA have greater influence on the wear resistance and cutting force. So the CTRA and CTEA are considered as the main parameters of the cutting tool in the proposed model.

1.2 CE modeling in manufacturing stage

As stated above, the CEs in manufacturing stage mainly include the CEs caused by cutting energy, cutting tool, and cutting fluid consumption.

(1) Energy consumption CEsCe

The total input power of NC machine tool processing is composed of the no-load powerPu, cutting powerPc, and additional power lossPa. The no-load power and additional power loss of the NC turning process can be calculated as follows[3]. The NC practical turning process of radial thrust forceFrdoes not consume power, which mainly affects the machining precision of the workpiece and cutting vibration. Axial thrust forceFfon the NC feed mechanism is the main basement of calculating and testing the weakness and strength of the parts on the feed mechanism. The power consumption byFfaccounts for 1% to 5% of the total power[9]. So the NC cutting power is simplified as

Pc=1000Fc·v.

(1)

And

(2)

whereCFc,xFc,yFc, andnFcare coefficients related to the workpiece material and the cutting conditions,vis cutting speed,fis feed rate,apis cutting depth, the correction coefficientKFcis mainly determined by the correction coefficientKγFcof the CTRA and the correction coefficientKκFcof the CTEA when the processing materials and cutting condition are determined.

The additional power lossPais difficult to obtain accurate theoretical function. Liuetal.[10]proposed additional power and cutting power linearly proportional relationship as

Pa=bm·Pc,

(3)

wherebmis the loss factor of additional load, and in generalbmis in the range of [0.15， 0.25].

From the above conditions, the energy consumption CEs are given by

(4)

wherePu0is the minimum no-load power of an NC tool,A1andA2are the spindle speed coefficients,nis the spindle speed,Tpis the machining process time,Feis the carbon emission factor, andtwpis the NC cutting process time. The national average carbon emission factor is 0.6747 kg CO2/kW·h[3].

(2) The cutting tool CEsCT

In the NC turning process, the direct CEs caused by the cutting tool are relatively small. The indirect CEs are the main, which are mainly concentrated in the tool manufacturing stage and the use of raw materials. The indirect CEs of the cutting tool can be calculated by the proportion of the use time in the manufacturing process to the life cycle of the cutting tool. The cutting tool CECTdepends on the average qualityWT,i.e.

(5)

(3) The cutting fluid CEsCq

The water-soluble cutting fluid (water-based) is commonly used in the production and studied in this paper. There exist the evaporation and leakage in the use process of cutting fluid, which will cause the cutting fluid loss. So in the using process, the workers often adjust the concentration of the cutting fluid by adding water and pure mineral oil in order to make it satisfy the use requirements[3]. The adding and replacement cycle of the cutting fluid is longer in the using phase. For a specific processing in the workshop, the cutting fluid CEs are calculated by the proportion of the use time in the process to the life cycle of the cutting fluid,i.e.

(6)

whereTtis the cutting fluid replacement cycle,Fois the emission factor of the pure mineral oil,Fwis the CE factor of the waste cutting fluid processing,Ccfis the initial cutting oil consumption,Acfis the additional cutting oil consumption, andδis the cutting fluid consistency. Reference [3] presented mineral oil CE factor was 2.85 kg CO2/L and the carbon emission factor of the waste cutting fluid processing was 0.2 kg CO2/L.

1.3 CE model for the NC single-step process

(7)

wheretctis the working hour of each tool change. The tool lifeTcan be calculated by

(8)

wherext,yt, andntare tool life coefficients, andCt1is the constant related to the cutting condition.

Synthesizing the influence law of the cutting parameters and other factors on the tool life, the tool life index formula is as follows[9].

(9)

whereKtis correction coefficient of cutting tool life influenced by other factors (CTRA and CTEA),mis the coefficient influenced byvandT,CKis constant related to cutting condition. Generally,m= 0.125 under the condition of carbide cutting tool with cutting fluid.

By the above formula, the NC turning process hours of a single-process can be given by

(10)

wherelis the length of a tool feeding,dis the diameter of the workpiece,Δis a unilateral machining allowance of the workpiece,C0is a coefficient related to cutting speed. According to Eqs. (7-10), one can obtain

(11)

So the manufacturing CEs of a single turning process can be given by

CP=Fe·[(Pu0+A1n+A2n2)·

(Ccf+Acf)+Fw·(Ccf+Acf)/δ]

(12)

1.4 Other constraint conditions

In common cases, the NC machining parameters are generally constrained by the spindle speed, feed rate, maximum cutting force, cutting power, processing quality of the selected machine tool,etc. In the process of optimizing the NC turning process CEs, the selection of NC machining parameters should satisfy the constraints of the restricted conditions.

(1) The constraint of CTRA

The reasonable selection range of CTRA is as follows.

-15°≤γ≤30°.

(13)

(2) The constraints of CTEA

The CTEA affects the tool life and cutting tool temperature.

30°≤κ≤90°.

(14)

(3) The cutting force constraint

In the NC turning process, the largest axial thrust force that the machine is achieved can not exceed the maximum axial thrust force of the machine,i.e.

(15)

whereFmaxis the maximal feed force,CFf,KFf,xFf,yFf, andnFfare coefficients related to the workpiece material and the cutting conditions.

(4) Power constraint

The turning power can not be more than the maximum cutting power.

(16)

wherePmaxis the maximum cutting power, andηis the machine effective coefficient of cutting power.

(5) The constraints of processing qualityRa

When the corner radiusrs=0 mm, the surface roughness of the parts should satisfy the requirements of parts quality roughness[8].

(17)

whereκ′ is tool minor cutting edge angle, andRmaxis the allowed maximal surface roughness value.

2 Calculation and Analysis of a Case

In this section, we take the cutting workpiece as shown in Fig.1 as an example to verify the proposed model. Referring to Ref.[3], the NC machine specifications are shown in Table 1. The workpiece material is 45 steel, tensile strengthσb=0.637 GPa, cutting depthap= 1 mm, the spindle speedn= 10 r/min, feed ratef= 0.34 mm/r, the cutting tool is the carbide cutting tool, the cutting edge inclinationλs= 5°, and the corner radiusrs=0 mm, the surface quality of machining requirements shall not be more than 6.4 μm. In the process, the cutting fluid is required.

Fig.1 Workpiece dimensions of the example/mm

We choose the tool life 60 min. The cutting force correction coefficientsCFc=2650,xFc=1.0,yFc=0.75, andnFc=-0.15. The cutting coefficients are shown in Tables 2-4. And the other correlation coefficients are shown in Tables 5-6[3].

Table 1 NC machine specifications

Table 2 The coefficients of the tool life and cutting force

Table 3 The cutting tool rake angle correction coefficients of cutting force and feed force

Table 4 The cutting tool edge angle correction coefficients of cutting force and feed force

Table 5 The rated calculatation parameters of the example

Table 6 The rated calculation coefficients of the example

According to the proposed models,the CEs are calculated using MATLAB, as shown in Figs. 2-3 while CTRA and CTEA change respectively. The calculation results show that while the CTRA is constant, the manufacturing reduce with the increasing of CTEA. When the CTEA increases, the cutting thickness increases and the machining deformation decreases. Thus the cutting force reduces. From Eq. (12), the cutting force is the main reason for the power consumption. So it is concluded that NC machining CEs relatively decrease with the increasing of the CTEA in the turning process.

Fig.2 The influence of the CTEA on CEs

From Fig.3, when the CTEA is constant, with the increasing of CTRA in NC turning process, the CEs reduce. In turning process, the shear angle increases while CTRA increasing. The chip formation coefficient decreases and the friction decreases along the rake face. The cutting force is reduced. From Eq. (12), the cutting force is the main reason for the power consumption. So NC machining CEs relatively decrease with the increasing of CTRA in the turning process. But to be noted, CTEA and CTRA have important influences on the cutting temperature, which will affect the durability of the cutting tool.

Fig.3 The influence of the CTRA on CEs

3 Conclusions

In this paper, the manufacturing CEs for the NC turning process are modeled, which include the CEs caused by the cutting power consumption, cutting tool, and cutting fluid. The proposed model considers the influences of the parameters of the cutting tool, such as CTRA and CTEA. The analysis results of a workpiece turning case show that as CTRA and CTEA increase, the manufacturing CEs decrease with the constraints of the cutting tool angle, the maximum cutting power, the largest axial thrust force, and processing quality. But the parameters of the cutting tool have great influence on the cutting temperature and tool life. The optimal parameters selection of the cutting tool is a problem to be resolved. In additional, the NC machining is often multi-step and multi-process. These issues will be investigated in the future.

[1] International Energy Agency. Tracking Industrial Energy Efficiency and CO2Emissions[EB]. (2009) [2014-05-20]. http://www.global-greenhouse-warming.com/industry-CO2-emissions.html.

[2] Li C B, Cui L G, Liu F,etal. Carbon Emission Quantitative Method of Machining System Based on Generalized Boundary[J].ComputerIntegratedManufacturingSystems, 2013, 19(9): 2229-2236.

[3] Li C B, Cui L G, Liu F,etal. Multi-objective NC Parameters Optimization Model for High Efficiency and Low Carbon[J].JournalofMechanicalEngineering, 2013, 49(9): 87-95.

[4] Cao H J, Li H C, Cheng H Q,etal. A Carbon Effciency Approach for Life-Cycle Carbon Emission Characteristics of Machine Tools[J].JournalofCleanerProduction, 2012, 37: 19-28.

[5] Li X G, Li C B, Liu F,etal. Modeling and Quantification Methods for Carbon Emission in Machine Tools Manufacturing Processes Based on Petri Nets[J].ComputerIntegratedManufacturingSystems, 2012, 18(12): 2723-2735.

[6] Rajemi M F, Mativenga P T, Aramchroen A. Sustainable Machining: Selection of Optimum Turning Conditions Based on Minimum Energy Considerations[J].ManufacturingTechnology, 2011, 60(1): 145-148.

[7] Song J S, Lee K M. Development of a Low-Carbon Product Design System Based on Embedded GHG Emissions[J].Resources,ConservationandRecycling, 2010, 54(9): 547-556.

[8] Xiong L S, Yan X G, Zhang F Y. Mechanical Manufacturing Technology Foundation[M]. Wuhan: Huazhong University of Science and Technology Press, 2007: 219-224. (in Chinese)

[9] Yang X L, Li X J. Metal Cutting Theory and Cutting Tools[M]. Xi’an: Northwestern Polytechnical University Press, 2012: 42-46.(in Chinese)

[10] Liu F, Xu Z J, Dan B,etal. Energy Performance of Mechanical Processing System and Application[M]. Beijing: China Machine Press, 1995: 62-68.(in Chinese)

Research Fund for the Doctoral Program of Higher Education of China (No.20122125120013); Scientific Research Fund of Liaoning Provincial Education Department, China (No.L2013206); the Fundamental Research Funds for the Central Universities, China (Nos. 3132014303, 3132015087)

1672-5220(2014)06-0827-04

Received date: 2014-08-08

* Correspondence should be addressed to LIU Zhi-jie, E-mail: liuzj@dlmu.edu.cn

CLC number: TH17 Document code: A