【正文】 ng power demand. Since the cutting load is expected to vary with the work piece material, the following experiments were conducted to measure the power demand of the Mori Seiki NV1500 DCG while machining peripheral cuts on 1018 steel, 6061 aluminum, and polycarbonate. A depth of cut and width of cut of 2 mm and 4 mm, respectively, was used. The chip load of mm/tooth was maintained constant across the experiments, to allow for the parison of the Sustainability in Manufacturing Energy Efficiency in Machine Tools results. The process parameters used in the experiment are outlined in Table 3. Table 3: Process parameters for power demand experiments with multiple work piece materials. The remended cutting speed varied with the work piece material. Aluminum was cut at the highest speed, followed by polycarbonate, then steel. The use of coolant while machining aluminum was remended by the cutting tool manufacturer due to the material’ s ductility and its tendency to buildup on the cutting tool. Coolant was also remended for polycarbonate to prevent it from melting because of the high temperature at the cutting tool and work piece interface. Steel can be cut without coolant (which would greatly reduce the total power demand of the machine tool), but since cutting fluid aids with chip exit and this study is primarily concerned with the cutting power demand, coolant was used when cutting all material types. The power demand of the NV1500 DCG is shown in Figure 6 , and is broken down into cutting and air cutting power demand. The air cutting power demand is approximately the same across the three processing conditions. The difference is due primarily to the change in spindle speed, the highest of which was used while cutting aluminum. The difference in the power demanded by the axis drives was found to be negligible even though the feed rate for aluminum is more than two times that of steel. The cutting power demand shows greater variability for the three work piece materials. The cutting power was the greatest while machining the steel work piece. In fact, it was approximately 7% of the total power demand. This may be due to the fact that it has the highest tensile strength, followed by aluminum, then polycarbonate. The cutting power while machining the polycarbonate work piece was the smallest and almost negligible, only 1% of the total power demand. 10 Figure 6: Power demand of NV1500 DCG for steel, aluminum, and polycarbonate work pieces. Sustainability in ManufacturingEnergy Efficiency in Machine Tools A particular work piece material can be machined at a range of process parameters while maintaining minimal tool wear and good surface finish. So future experiments should be conducted in which the material removal rates overlap as much as possible across the work piece materials under study when calculating the cutting power demand for the purpose of parison. Also, the power demand of the spindle motor and the axis feed drives should be measured directly since presently the cutting power demand is obtained by subtracting the air cutting power demand from the total power demand of the machine tool. 5 CONCLUSIONS This study has shown that the machining time dominates energy demand for high tare machine tools. Additionally, it has provided a method for characterizing the specific energy of a machine tool as a function of process rate, which can be extended to other types of manufacturing processes. The specific energy model allows a product designer to estimate the manufacturing energy consumption of their part’ s production without needing to measure power demand directly at the machine tool during their part’ s production. Since the specific energy as a function of . for the micromachining center presented herein varied by as much as an order of magnitude, it is important to use process parameters and machine toolspecific data to determine accurate electrical energy consumption. This model could therefore be used in place of aggregate embodied energy values for manufacturing processes as provided by [9] or to replace process estimates with great uncertainty when conducting hybrid life cycle assessments. 6 ACKNOWLEDGMENTS This work was supported in part by Mori Seiki, the Digital Technology Laboratory (DTL), the Machine Tool Technologies Research Foundation (MTTRF), Kennametal, and other industrial partners of the Laboratory for Manufacturing 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 . 11 7 REFERENCES [1] Diaz, N.。 Dornfeld, D. (2020): Environmental Analysis of Milling Machine Tool Use in Various Manufacturing Environments, IEEE International Symposium on Sustainable Systems and Technology (ISSST2020), Washington, . [2] Carnegie Mellon University Green Design Institute. (2020): Economic InputOutput Life Cycle Assessment (EIOLCA), Available from: [3] Diaz, N.。 Fujishima, M.。 關鍵詞 ： 綠色機床 ， 降低能耗 ， 能量的特征 1 簡介 一個產品的生產 周期要經過三個階段 ：制造，使用和使用終止。參考文獻 [4]給出了 這樣一個優(yōu)化刀具路徑的最低周期時間 的方法。 3. 4齒的錫涂層的硬質合金立銑刀。 圖 2：不同材料去除率所需的總功率 16 切削深度試驗 切削深度實驗同樣是在長度為 101mm 的 1018號鋼的鋼件上進行。 pcutcut21p?? (2) t??? 12t? (3) 公式 (4)為假設兩個方案空切電能消耗不變的前提下，平均電能消耗 P avg1與平均電能消耗 P avg2之間的關系。機床電力需求增長 了 大約三分之二 ， 而能源消耗減少到低于它原來的三分之一。用這一方法測量出來的能耗與切削過程中的能耗聯(lián)系起來，就可以知道在接下來所說的切削能耗了。 2 不同的材料去除率的能耗 由于機床程序員和操作者在制定一個工件的生產工藝是有很多的選擇，所以本文分析努 14 力選取降低能耗的機床加工工藝參數(shù)。 在進行生命周期評估 時， 產品 設計師可以選擇在選擇的過程 、經濟投入產出 (EIO)過程或混合進行。 大衛(wèi) ， 伯克利大學 出版日期： 2020年 04月 05日 系列： 綠色制造與可持續(xù)生產的關系 出版信息 ： 綠色制造與可持續(xù)生產的關系 ， 加州大學伯克利分校 制造與可持續(xù)性