【正文】 facturing and Sustainability (LMAS). The authors would like to thank the UC Berkeley Mechanical Engineering Department’s Student Machine Shop for providing valuable insight and advice . For more information, please visit . 7 REFERENCES [1] Diaz, N.。 Energy Consumption Reduction。畢業(yè)設(shè)計（論文）外文翻譯課題名稱 汽車上油殼加工工藝及夾具設(shè)計 系 別 職業(yè)技術(shù)教育學(xué)院 專 業(yè) 機械工程及自動化 班 級 機自Z081 學(xué) 號 200802201022 姓 名 何 仕 指導(dǎo)教師 鄧 麗 萍 Laboratory for Manufacturing andSustainabilityUC BerkeleyTitle:Energy Consumption Characterization and Reduction Strategies for Milling Machine Tool UseAuthor:Diaz, Nancy, University of California, BerkeleyDornfeld, David, UC BerkeleyPublication Date:05042011Series:Green Manufacturing and Sustainable Manufacturing PartnershipPublication Info:Green Manufacturing and Sustainable Manufacturing Partnership, Laboratory for Manufacturingand Sustainability, UC BerkeleyPermalink:Keywords:Green Machine Tools。Specific Energy Characterization1 INTRODUCTION A product undergoes three lifecycle stages: manufacturing, use and endoflife. Consumer products whose environmental impact is dominated by the use phase include light fixtures, puters, refrigerators, and vehicles, in general products that are used extensively during their functional life. All the while these products consume resources, in particular energy in the form of electricity or fuel. The machine tool is one such product. The use phase of milling machine tools has been found to prise between 60 and 90% of CO2equivalent emissions during its life cycle [1]. This study presents a method for predicting the electrical energy consumed in manufacturing a product for the purpose of reducing its environmental impact. In conducting a life cycle assessment, product designers may choose to opt for a process, economic inputoutput (EIO), or hybrid approach. The drawback of the process LCA, though, is that because this method entails acquiring processspecific data it is time consuming and therefore resource intensive. An alternative to measuring the machine tool’s electrical energy consumption directly, for example, is to use aggregate data as is done with EIOLCA [2]. An EIOLCA, therefore, is not specific to the design of a particular product. The strategies presented herein provide a method for more quickly generating manufacturing energy consumption estimates for a particular product. Cutting load profile As described by Diaz et al. in [3] the power demand of a machine tool is prised of cutting, variable, and constant power ponents. The cutting power is the additional power drawn for the removal of material. The machine tool used in this analysis, the Mori Seiki NV1500 DCG, is a micromachining center with a relatively low standby power demand when pared to large machining centers. Therefore, the cutting power can prise a large portion of the machine tool’s total power demand. Energy consumption for high tare machine tools was found to be primarily dependent on the processing time of the part, which is dictated by the part geometry, tool path, and material removal rate. One such method for optimizing the tool path for minimum cycle time was presented in [4]. This paper is concerned with the effect of the material removal rate on energy consumption. The material removal rate for a 3axis machining center can be varied by changing the feed rate, width of cut, or depth of cut. Since increasing the feed rate was found to have dire consequences on the cutting tool life [5], the experiments conducted herein varied material removal rate through width of cut and depth of cut experiments for the purpose of analyzing the material removal rate’s effect on cutting power and more importantly, energy consumption. Although increases in the material removal rate translate to faster machining times, the loads on the spindle motor and axis drives increase as well, resulting in higher power demand. Since our main interest is energy consumed in product manufacture, the tradeoff between power demand and machining time was analyzed to confirm that the increased loads due to faster material removal was not increasing the total energy consumed. 2 POWER DEMAND FOR VARIED .’S Since machine tool programmers and operators have an array of options when defining the process plan for part production, this analysis strives to reduce energy consumption by process parameter selection of a machine tool. Specifically, the parameters concerning material removal rate (.) were varied on a Mori Seiki NV1500 DCG while selecting appropriate tooling. The power demand was measured with a Wattnode MODBUS wattmeter. In previous work, experiments we re conducted in which spindle speed, feed rate, feed per tooth, and cutter type were varied to analyze the change in energy consumption while milling a low carbon steel, AISI 1018 steel [5]. Also, [6] conducted experiments on face milling, end milling, and drilling operations in which the energy consumption, machining cost, and tool wear were pared for increased cutting speeds. Tool wear and, consequently, cutting tool cost increased significantly when the process parameters veered away from the remended cutting conditions. So in the following experiments the cutting tool type was changed to maintain the remended process parameters, but reduce energy consumption while machining, nonetheless. Width of Cut Experiments Given the energy savings from changing the cutter type this project focused on varying material removal rate. First the width of cut was increased while machining with a: 1. 2 flute uncoated carbide end mill, 2. 2 flute TiN coated carbide end mill, and 3. 4 flute TiN coated ca