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Development of Prediction System for Environmental Burden for Machine Tool Operation (1st Report, Proposal of Calculation Method for Environmental Burden)

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(1)1188. Development of Prediction System for Environmental Burden for Machine Tool Operation∗ (1st Report, Proposal of Calculation Method for Environmental Burden) Hirohisa NARITA∗∗ , Hiroshi KAWAMURA∗∗∗ , Takashi NORIHISA∗∗∗∗ , Lian-yi CHEN† , Hideo FUJIMOTO† and Takao HASEBE∗∗∗∗ Recently, some activities for environmental protection have been attempted to reduce environmental burdens in many fields. The manufacturing field also requires such reduction. Hence, a prediction system for environmental burden for machining operation is proposed based on the Life Cycle Assessment (LCA) policy for the future manufacturing system in this research. This system enables the calculation of environmental burden (equivalent CO2 emission) due to the electric consumption of machine tool components, cutting tool status, coolant quantity, lubricant oil quantity and metal chip quantity, and provides accurate information of environmental burden of the machining process by considering some activities related to machine tool operation. In this paper, the development of the prediction system is described. As a case study, two Numerical Control (NC) programs that manufacture a simple shape are evaluated to show the feasibility of the proposed system.. Key Words: Environmental Burden, End Milling Operation, Machine Tool, LCA. 1.. Introduction. Manufacturing technologies have been evolving with the goal of achieving high productivity and high precision in manufacturing high-quality products rapidly at a low cost. A reduction in burden to the earth’s environment, however, is indispensable; thus, some attempts have been carried out in recent years. In the manufacturing field, the reduction in environmental burden at manufacturing, usage and disposal processes of products have been attempted on the basis of Design for Environment (DfE)(1) , ∗. ∗∗. ∗∗∗. ∗∗∗∗. †. Received 6th March, 2006 (No. 04-0443). Japanese Original: Trans. Jpn. Soc. Mech. Eng., Vol.71, No.704, C (2005), pp.1392–1399 (Received 16th April, 2004) Tsukuri College, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466–8555, Japan. E-mail: narita@vier.mech.nitech.ac.jp Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466– 8555, Japan OKUMA Corporation, 5–25–1 Shimokoguchi, Oguchicho, Niwa-gun, Aichi 480–0193, Japan Omohi College, Graduate School of Engineering, Nagoya Institute of Technology, Gokiso-cho, Showa-ku, Nagoya, Aichi 466–8555, Japan. Series C, Vol. 49, No. 4, 2006. Life Cycle Assessment (LCA)(2) policies, and good results have been obtained by utilizing product designs and business strategies. In this study, manufacturing processes are focused in terms of the life cycles of some products, and a prediction and an evaluation system for environmental burden for machine tool operation, which is vital in a production system, is developed. Machine tools are mother machines and widely utilized in the manufacturing fields. Therefore, one of the most important issues to be solved is to develop an estimation of the environmental burden related to the machine tools. The development of the evaluation system enables us to calculate the environmental burden of a product and carry out an LCA. The promotion the developments of eco-manufacturing techniques and machining know-how are expected. Furthermore, a trial of such research will be important, because the environmental burden and impact will be treated as cost in the near future. An evaluation system for environmental burden for machine tool operation has been developed thus far(3) . This system, however, can evaluate only the difference among dry, minimal quantities of lubricant (MQL) and wet machining operations, but not that of the difference among depth of cuts, feed rate, spindle speed and tool path JSME International Journal.

(2) 1189 pattern. Furthermore, if removal volume and metal type are the same, the environmental burden becomes same. In other words, the conventional evaluation system can’t provide accurate environmental burden information and sufficient information for deciding the cutting conditions. In a previous study, some eco-machining operations of a turning process were compared using the conventional evaluation system(4) , but the results obtained can’t be adapted to all machining methods. Moreover, this evaluation process was found to be no feasible, because almost all parameters were obtained by real machining operation. Secondary effects of machine tools have been discussed(5) , but not concrete evaluation ways of evaluating machining operation. Manufacturing system planning with consideration of multi-endpoint environmental effects has been proposed(6) , but concrete evaluation methods for machining operation haven’t been provided, neither. Hence, in order to realize true eco-friendly manufacturing, an accurate evaluation system of environmental burden is required in the manufacturing field. A prediction system for the environmental burden for machine tool operation is developed in this study. In this paper, a conceptual architecture and a system design for the prediction system are introduced, and the effectiveness and the feasibility of such a system are described. 2. System Overview of Environmental Burden Analyzer Figure 1 shows an overview of the proposed evaluation system for environmental burden for machining operation. This system consists of an estimator, a database and an analysis block. This system can evaluate the machining strategies generated by CAM from the viewpoints of the electric consumption of machine tool components, coolant quantity, lubricant oil quantity, cutting tool status, metal chip quantity and other factors, and calculate environmental burden automatically. Other factors mean evaluation factors input by users according to needs, such as the electric consumption of light, air conditioning, AGV transportation, products washing. The analysis block evaluates machine tool motions and analyzes status of machining operation. The database block consists of background and resource databases. The background database stores some parameters required for the calculation of environmental burden. The resource database stores machine tool specification data, cutting tool parameters and data for the estimation of machining process. This research deals with only the background data related to the production and disposal processes. The data related of the other processes are not considered, since the data related to such processes as transportations depend on the location and environment of the individual users of the machine tools. In a general LCA, an impact category is determined JSME International Journal. Fig. 1 Prediction system for environmental burden for machine tool operation Table 1 Characterization factors of global warming. from global warming, ozone layer depletion, toxicity to human and so on, and influential emission factors for each impact category are selected. This study focuses on global warming, and an evaluation system for the emissions of carbon dioxide (CO2 ), methane (CH4 ) and dinitrogen monoxide (N2 O), which are influential emission factors, is developed. The effects of halocarbon, and sulfur hexafluoride (SF6 ) on global warming are well known. However, these emission factors are eliminated, because they are not emission factors related to machine tool operation. All emissions are converted to equivalent CO2 emission by multiplying them by characterization factors, and their environmental impact as an indicator is calculated by adding all emissions. By this calculation, a unified evaluation can be carried out and the influence ratio of emission matters to the environment can be represented as numerical data. The global warming potential (GWP) of 100-year impact(7) is used as the characterization factors, as shown in Table 1. 3. Calculation Algorithm for Environmental Burden Total environmental burden (equivalent CO2 emission) is calculated from the electric consumption of machine tool components, coolant quantity, lubricant oil quantity, cutting tool status, metal chip quantity and other factors, as mentioned in section 2. The evaluation method introduced in this paper can basically be applied to all machine tool operations. Pe = Ee +Ce + LOe +. . (Tei ) + CHe + OTe. (1). i→N. Pe : environmental burden of machining operation [kg-CO2 ] Ee : environmental burden of electric consumption of machine tool [kg-CO2 ] Ce : environmental burden of coolant [kg-CO2 ] LOe : environmental burden of lubricant oil [kg-CO2 ] Te : environmental burden of cutting tool [kg-CO2 ] Series C, Vol. 49, No. 4, 2006.

(3) 1190 CHe : environmental burden of metal chip [kg-CO2 ] OTe : environmental burden of other factors [kg-CO2 ] N : number of tools used in NC program Equivalent CO2 emission is calculated using Eq. (1) by analyzing the behavior of a machine tool and machining operations. In this paper, environmental burden of other factors is not described. 3. 1 Environmental burden of electric consumption of machine tool (Ee) The environmental burden of the electric consumption of a machine tool is expressed as Eq. (2). Ee = k × (SME + SPE + SCE + CME + CPE + TCE1 + TCE2 + ATCE + MGE + VAE). (2). k : CO2 emission intensity of electricity [kgCO2 /kWh] SME : electric consumption of servo motors [kWh] SPE : electric consumption of spindle motor [kWh] SCE : electric consumption of cooling system of spindle [kWh] CME : electric consumption of compressor [kWh] CPE : electric consumption of coolant pump [kWh] TCE1 : electric consumption of lift up chip conveyor [kWh] TCE2 : electric consumption of chip conveyor in machine tool [kWh] ATCE : electric consumption of ATC [kWh] MGE : electric consumption of tool magazine motor [kWh] VAE : vampire energy (stand-by) of machine tool [kWh] In Eq. (2), the electric consumptions of servo motors and a spindle motor are varied dynamically according to the machining process; thus, their analysis model has to be constructed. Figure 2 shows the electric consumption model of machine tools. As shown in the left part of Fig. 2, the electric consumption of the servo motors and the spindle motor is calculated by considering table weight, the friction coefficient of slide way, ball screw lead, the transmissibility of ball screw, cutting force and cutting torque. The electric consumption of peripheral devices of machine tools such as an NC controller, an ATC and a coolant pump are calculated from their running times. The load torques of servo motors are calculated as. Fig. 2. Electric consumption model of machine tools. Series C, Vol. 49, No. 4, 2006. follows. T L1 = T U + T M. (3). T L1 : load torque of servo motor [Nm] T U : axis friction torque [Nm] T M : application torque of ball screw [Nm] Where T U is the torque due to rubber sealing and can’t be obtained theoretically, thus its value is decided experimentally. T M is calculated as follows. TM =. (µ · M ∓ f ) · l · cosθ ± (M − f ) · l · sinθ 2π · η. (4). µ : friction coefficient of slide way η : transmissibility of ball screw system l : ball screw lead [m] M : moving part weight (table and workpiece) [N] f : cutting force in axis [N] θ : Gradient angle from horizontal plane [rad] This equation is reconstructed by a monitoring method for cutting force(8) with normal and reverse rotations of the servo motor. θ is 0 in the X- and Y-axes, and π/2 in the Z-axis. The load torque of the spindle motor, T L2 , is calculated from the cutting force model. The calculated motor torque is converted to electric consumption as follows. 2π × n × TL × t P= (5) 60 P : electric consumption [Wh] T L : load torque [Nm] n : motor rotation speed [rpm] t : time [hr] CO2 emission is calculated from the electric consumption calculated using this equation. The cutting force and cutting torque must be calculated by simulating the machining process and according to cutting conditions. Thus, VMSim (Virtual Machining Simulator) has been developed, and applied to the prediction of the cutting force and cutting torque. The prediction method used in the VMSim(9), (10) is applicable to many machining operations, so it is possible to evaluate various machining operations. 3. 2 Environmental burden of coolant (Ce) A coolant (water-miscible cutting fluid) is generally stored in a tank, and supplied to a cutting point by a coolant pump during machining. The coolant is evacuated with the metal chips, and re-stored in a tank and then reused after being separated from the chips at a catch pan. That is the coolant is circulated until the coolant is updated. Cutting oil is adhered to the metal chips, so they are reduced bit by bit until the coolant is updated. Hence, the cutting oil is supplied for compensation during this period. The dilution fluid (water) is also supplied at regular intervals due to loss through vaporization. Hence, the environmental burden due to the coolant is calculated as follows by considering the aforementioned process. JSME International Journal.

(4) 1191 Ce =. CUT × {(CPe + CDe) × (CC + AC) CL + WAe × (WAQ + AWAQ)}. (6). CUT : coolant usage time in an NC program [s] CL : mean interval of coolant update [s] CPe : environmental burden of cutting fluid production [kg-CO2 /L] CDe : environmental burden of cutting fluid disposal [kg-CO2 /L] CC : initial coolant quantity [L] AC : additional supplement quantity of coolant [L] WAe : environmental burden of water distribution [kgCO2 /L] WAQ : initial quantity of water [L] AWAQ : additional supplement quantity of water [L] 3. 3 Environmental burden of lubricant oil (LOe) Lubricant oil is mainly used for a spindle and a slide way, so two equations are introduced. Here, oilair lubricant is assumed to be used for spindle lubricant. In the case of oil-air lubricant, minute amounts of oil (0.01 cc∼0.06 cc) is infused into an oil pipe by a pump and supplied to a spindle part at decided intervals. The lubricant oil of the slide way is supplied by a pump at decided intervals. Grease lubricant is not mentioned, but the same equations can be adopted to calculate environmental burden. LOe = Se + Le. (7). Se : environmental burden of spindle lubricant oil [kgCO2 ] Le : environmental burden of slide way lubricant oil [kg-CO2 ] SRT Se = × SV × (SPe + SDe) (8) SI SRT : spindle runtime in NC program [s] SV : discharge rate of spindle lubricant oil [L] SI : mean interval between discharges [s] SPe : environmental burden of spindle lubricant oil production [kg-CO2 /L] SDe : environmental burden of spindle lubricant oil disposal [kg-CO2 /L] LUT × LV × (LPe + LDe) (9) Le = LI LUT : slide way runtime in NC program [s] LI : mean interval between supplies [s] LV : lubricant oil quantity supplied to slide way [L] LPe : environmental burden of slide way lubricant oil production [kg-CO2 /L] LDe : environmental burden of slide way lubricant oil disposal [kg-CO2 /L] 3. 4 Environmental burden of cutting tool (Te) Cutting tools are managed from the viewpoint of tool life. The cutting tools, particularly those for a solid end mill, are recovered by regrinding after reaching their life JSME International Journal. limit. In this study, environmental burden is calculated by comparing machining time with tool life and considering the aforementioned process. MT × {(TPe + TDe) × TW Te = TL × (RGN + 1) + RGN × RGe} (10) MT : machining time [s] TL : tool life [s] TPe : environmental burden of cutting tool production [kg-CO2 /kg] TDe : environmental burden of cutting tool disposal [kg-CO2 /kg] TW : tool weight [kg] RGN : total number of regrinding processes RGe : environmental burden of regrinding [kg-CO2 ] 3. 5 Environmental burden of metal chip (CHe) Metal chips are recycled in an electric heating furnace after they are accumulated and separated from the coolant. This process generates environmental burden. Input energies seems to be different for some metal types, but electric power consumption rate is represented [kWh/t], so environmental burden is also calculated from the metal chip weight in this study. CHe = (WPV − PV) × MD × WDe. (11). 3. WPV : work piece volume [cm ] PV : product volume [cm3 ] MD : material density of work piece [kg/cm3 ] WDe : environmental burden of metal chip processing [kg-CO2 /kg] 4.. Case Study. 4. 1 Parameter setting The evaluations of environmental burden due to the machining operation are attempted using the developed system. In this case study, the machine tool is MB-46VA (OKUMA Corp.), the cutting tool carbide-square end mill with two-flute and a 30◦ helical angle, and a workpiece cast iron (FC250). The cutting coefficients required to predict cutting force in the VMSim are shown in Table 2. These cutting coefficients are obtained by comparing the approximated average cutting force, which is measured experimentally under various feed rates, with theoretical average cutting force obtained using a cutting model. These coefficients depend on the material types of the workpiece and cutting tool, and tool edge parameters. Cutting force can be calculated under various cutting conditions, once these coefficients are obtained. Table 2. Cutting coefficients. Series C, Vol. 49, No. 4, 2006.

(5) 1192 Table 3 Machine tool parameters for servo motor torque calculation. Table 4. Table 5 CO2 Emission intensities. Electric powers and consumptions of machine tool components. Table 6. The parameters required for calculating the electric consumption of the servo motor of the machine tool are shown in Table 3 and the electric powers of the peripheral devices of the machine tool are shown in Table 4. These values have been measured and obtained from an instruction manual of the machine tool. The electric consumption is, however, listed for an ATC and a tool magazine, because they do not depend on their running time. For reference, the machine tool can hold twenty cutting tools. From the parameters shown in Table 3 and experimental results for determining the axis friction torque, conversion equations of the servo motors are as follows. These equations express the torques of the normal and reverse rotations; thus, there are two conversion equations of torques in each axis. In these equations, f∗∗ indicates the cutting force along each axis, and n means the motor rotation speed. − fX × 0.02 + 2.088 4n−0.170 3 T L1X+ = 2π × 0.95 fX × 0.02 + 2.242 7n−0.057 7 T L1X− = 2π × 0.95 − fY × 0.02 + 1.142 9n−0.017 2 T L1Y+ = 2π × 0.95 (12) fY × 0.02 −0.029 5 + 2.021 1n T L1Y− = 2π × 0.95 fZ × 0.016 + 16n−0.003 T L1Z+ = 2π × 0.95 fZ × 0.016 T L1Z− = + 11.449n0.011 8 2π × 0.95 Table 5 shows the CO2 emission intensities required to calculate the environmental burden of machining operations. These values were cited from some reports, such as environmental reports, technical reports, homepages and industrial tables(11) – (17) . The environmental burden of regrinding is estimated Series C, Vol. 49, No. 4, 2006. Other parameters related to evaluation factor. by us. For analysis, the cutting oil used is water-miscible type A1. Distillation concentrate and combination processing of pressure flotation, and activated sludge processing are used as disposal processes for cutting oil, but the latter is adopted in this research. Table 6 shows the other parameters required for calculating environmental burden. These values correspond to the input data the developed system by users. Here, the coolant is diluted with water 20 times. The evaluation is carried out using the aforementioned data. 4. 2 Case 1 (comparison of two NC programs) The conventional evaluation system for environmental burden for machining operation can’t be used to compare different machining strategies and tool path patterns for manufacturing the same-shape products. Here, such a comparison is tried. Figure 3 shows the product shape. Figure 4 shows the tool path patterns of the two NC programs used for the above-mentioned comparison and Table 7 shows the spindle speeds and feed rates. The total machining time of Program 1 is 224.1 sec, and that of Program 2 is 172.8 sec. The CO2 emission of the two NC programs calculated from the parameters shown in Tables 3–6, and Eq. (12) are shown in Table 8. As shown in Table 8, Program 2 is efficient for maJSME International Journal.

(6) 1193. Fig. 3 Product shape of case 1 Fig. 5 CO2 emission tendency due to high-speed milling. (a) Program 1. (b) Program 2. Fig. 4 Tool path pattern of case 1 Table 7 Cutting conditions for two NC programs. Table 8 Detailed results of equivalent CO2 emission. chining operation and has a low-environmental burden. It is found that environmental burden varies under different cutting conditions, though the same product is manufactured. That is to say, various cutting conditions, which can’t be realized by a conventional evaluation system, can be calculated effectively. Here, the machining operation, which realizes a low CO2 emission, is discussed on the basis of the CO2 emission of each factor. As shown in the table, the electric consumption of the peripheral devices of the machine tool, except for the servo motors and spindle motor is the highest among all factors. In order to reduce the CO2 emission effectively, this value must be reduced. The improvement of the peripheral device performance is one method of reducing the electric consumption, but this factor is proportional to the machining time. In other words, high-speed milling, which can reduce the machining time, in dry machining seems effective for reducing environmental burden. 4. 3 Case 2 (effect of high-speed milling) To confirm the effect of high-speed milling, the spindle speed and feed rate of Program 1 shown in Fig. 4 (a) JSME International Journal. are changed to a fixed feed per tooth of 0.04 mm/tooth and the CO2 emission is analyzed. Tool wear increases markedly, and the environmental burden due to the cutting tool is expected to increase. Here, the tool life TL in Eq. (10) is determined from the time required to reach the actual cutting length of the end life limits, which denotes the contact length of the tooth edge and workpiece(18) even if the cutting conditions are different. The actual cutting length of the end life limit of the cutting tool is determined as the basis for 5 400 sec at which the spindle speed is 2 500 rpm, the feed rate is 200 mm/min, the axial depth of cut is 6 mm and the radial depth of cut is 6 mm. The analysis result is shown in Fig. 5. As shown in this figure, the total CO2 emission decreases as the spindle speed increases. This is mainly caused by a reduction in electric consumption due to the shortening of the machining time described in the last part of case 1. From this analysis, it is found that high speed milling may be effective for reducing the CO2 emission. However, the assumption that tool life is proportional to the actual cutting length may not be acceptable for high-speed milling from the viewpoint of the heat value in the machining operation and the increase in flank wear(19), (20) . More detailed analysis of high-speed milling is required. 4. 4 Case 3 (effect of coolant usage in machining operation) To confirm the effects of coolant usage in the machining operation, an analysis using Program 1 shown in Fig. 4 (a) with the coolant is attempted. Here, the tool life is assumed to be increased to twofold the original one due to the coolant effect. The analysis result is shown in Table 9. As shown in this table, the environmental burden due to the cutting tool is reduced due to the coolant effect. However, the electric consumption and CO2 emission due to the peripheral devices are increased by the effect of the coolant pump and so on. The environmental burden due to the coolant is increased as a matter of course. The increase in CO2 emission due to the coolant usage is, however, concluded to be related to the peripheral devices used rather than their effect. As shown in this case study, the environmental burden due to the coolant usage, Series C, Vol. 49, No. 4, 2006.

(7) 1194 Table 9 Predicted result of Program 1 with consideration of coolant effect. should be acquired, and the database for the calculation of environmental burden, particularly for machine tool operation should be constructed according to each process of contributing factors of environmental burden. Acknowledgement We would like to express our sincere appreciation to OKUMA Corp. for thoughtful advice and the provision of experimental apparatus, and Enomoto BeA Corp. for the provision of information. References. which is vague, can be discussed in detail and calculated automatically. Moreover, in case 3, all emission factors of environmental burden appear, and the comparison of the impacts of CO2 , CH4 and N2 O is carried out. These are included in the results shown in Table 9 obtained by converting the equivalent CO2 emission as described in section 2. The impacts of CH4 and N2 O calculated from Table 1 correspond to about 0.001 g-CO2 by comparing the amount of the emission of each factor. In other words, CO2 is the dominant environmental burden in machining operation concerning global warming. 5.. Conclusions. Machine tools are mother machines. Hence, the development of an evaluation system for environmental burden for machine tool operation should first be carried out to reduce the total environmental burden in the manufacturing field. In this paper, a method of calculating accurate environmental burden due to machine tool operation is proposed and the evaluation system is developed. The conclusions are summarized as follows. 1. An evaluation system for environmental burden for machine tool operation is proposed to calculate the environmental burden from the difference among depth of cuts, feed rate, spindle speed and tool path pattern. Such evaluation can’t be realized using a conventional commercial evaluation system. Moreover, the validity of the system is demonstrated through simple case studies. 2. It is found that CO2 is the dominant environmental burden in machining operation concerning global warming by comparing CO2 emission with the equivalent CO2 emission of CH4 and N2 O. 3. High-speed milling may be effective from the viewpoint of the mitigation of global warming (CO2 emission), though more detailed analysis is required. In the future, evaluation models of eco-friendly machining methods such as minimal quantities of lubricant (MQL)(21) , Oil on Water (OoW)(22) will be proposed and applied to the evaluation system, and various machining operations should be analyzed. Moreover, detailed background data, which are used for the analysis in this paper, Series C, Vol. 49, No. 4, 2006. (1). (2) (3). (4). (5). (6). (7) (8). (9). (10). (11). (12). e.g. Sakao, T., Masui, K., Kobayashi, M., Aizawa, S. and Inaba, A., Quality Function Deployment for Environment: QFDE (2nd Report)—Verifying the Applicability by Two Case Studies—, Proc. of the Second International Symposium on Environmentally Conscious Design and Inverse Manufacturing (EcoDesign 2001), (2001), pp.858–863. e.g. SETAC, Guidelines for Life-Cycle Assessment: A Code of Practice, (1993). e.g. Shimoda, M., LCA Case of Machine Tool, Symposium of 2002 Japan Society for Precision Engineering Spring Annual Meeting “Leading-Edge Trend of Environmental Impact Evaluation for Inverse Type Design and Manufacturing”, (in Japanese), (2000), pp.37–41. Touma, S., Ohmori, S., Kokubo, K. and Tateno, M., Evaluation of Environmental Burden in Eco-Friendly Machining Method Using Life Cycle Assessment Method—Estimation of Carbon Dioxide Emission in Eco-Friendly Turing Method—J. JSPE, (in Japanese), Vol.69, No.6 (2003), pp.825–830. Akbari, J., Oyamada, K. and Saito, Y., LCA of Machine Tools with Regard to Their Secondary Effects on Quality of Machined Parts, Proc. of Eco Design 2001, (2001), pp.347–352. Sheng, P., Bennet, D., Thurwachter, S. / von Turkovich, B.F., Environmental-Based Systems Planning for Machining, Annals of the CIRP, Vol.47/1 (1998), pp.409– 414. Japan Meteorological Agency, Climate Change 1995, Science of Climate Change, (1995). Fujimura, Y. and Yasui, T., Machine Tool and Manufacturing System, (in Japanese), (1994), KYORITSU SHUPPAN Co. Ltd. Narita, H., Shirase, K., Wakamatsu, H., Tsumaya, A. and Arai, E., Real-Time Cutting Simulation System of a Milling Operation for Autonomous and Intelligent Machine Tools, Int. J. Production Research, Vol.40, No.15 (2002), pp.3791–3805. Narita, H., Kato, S., Shirase, K., Arai, E., Chen, L.Y. and Fujimoto, H., Machining Error Prediction System of Ball End Mill, Proc. of the 2004 JSPE Spring Annual Conference, (in Japanese), (2004), pp.367–368. e.g. Mizukami, H., Yamaguchi, R., Nakayama, T. and Maki, T., Off-Gas Treatment Technology of ECOARC, NKK Technical Report, (in Japanese), No.176 (2002), pp.1–5. Tokyo Electric Power Company Homepage, The Earth, JSME International Journal.

(8) 1195. (13). (14). (15). (16). (17). People & Energy TEPCO Sustainability Report 2003, <http://www.tepco.co.jp/index-e.html> Environmental Report of Tokyo Waterworks 2002, <http://www.waterworks.metro.tokyo.jp/pp/kh14/index. html> (in Japanese). Nansai, K., Moriguchi, Y. and Tohno, S., Embodied Energy and Emission Intensity Data for Japan Using Input-Output Tables (3EID)—Inventory Data for LCA—, Center for Global Environment Research, National Institute of Environmental Studies, Japan, (2002). The Society of Non-Traditional Technology, Survey Report (Additional Volume) of Basic Survey Research for Construction of Environmental Burden Evaluation System—Material Inventory Data—, (in Japanese), (1995). New Energy and Industrial Technology Development Organization (NEDO), Development of Environment-Conscious Technology Laboratory, First Section Meeting of “Development of Energy Saving Wastewater Treatment Technique”, Program Original Register of Development of Energy Saving Wastewater Treatment Technique, (2003). <http://www.nedo.go.jp/iinkai/hyouka/bunkakai/15h/8/ 1/4-1.pdf> Ministry of Economy, Trade and Industry, About Declaration of Evaluation Report related to Budget Request in Fiscal Year 2002 (Policy Evalua-. JSME International Journal. (18). (19). (20). (21). (22). tion), Section 6 Construction of Industrial Facilities (Regional Economic Industry U), Development of Wastewater Treatment Technique, (2004). <http://www.meti.go.jp/policy/policy management/ 14fy-hyouka/h14fym017.pdf> Ohtsuka, H., Yamaji, I., Nakagawa, H. and Kakino, Y., A Study on End Milling of Hardened Steel for Dies and Molds, Proc. of the 2004 JSPE Spring Annual Conference, (in Japanese), (2004), pp.365–366. e.g. Hirao, M., Terashima, A., Joo, H., Shirase, K. and Yasui, T., Behavior of Cutting Heat in High Speed Cutting, Journal of the Japan Society for Precision Engineering, (in Japanese), Vol.64, No.7 (1998), pp.1067– 1071. e.g. Shirase, K., Sugimoto, T., Wakamatsu, H. and Arai, E., Trial of Tool Wear Estimation in End Milling Operation, Proc. of the 2000 JSPE Spring Annual Conference, (in Japanese), (2000), p.314. Rahman, M., Senthil Kumar, A. and Salam, M.U., Experimental Evaluation on the Effect of Minimal Quantities of Lubricant in Milling, Int. J. Machine Tools and Manufacturer, Vol.42 (2002), pp.539–547. Yoshimura, H., Niwa, K., Nakamura, T. and Itoigawa, F., Study on Eco-Friendly Oil on Drop Cutting Fluid (Water Properties and Machining Performance of Oil on Water Drop Cutting Flulid), Proc. of the Second International Conference on Leading Edge Manufacturing in 21st Century (LEM21), (2003), pp.1059–1063.. Series C, Vol. 49, No. 4, 2006.

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Figure 1 shows an overview of the proposed evalua- evalua-tion system for environmental burden for machining  op-eration
Fig. 2 Electric consumption model of machine tools
Table 3 Machine tool parameters for servo motor torque calculation
Table 8 Detailed results of equivalent CO 2 emission

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