英文原文Automated surface finishing of plastic injection mold steel with spherical grinding and ball burnishing processesAbstractThis study investigates the possibilities of automated spherical grinding and ball burnishing surface finishing processes in a freeform surface plastic injection mold steel PDS5 on a CNC machining center. The design and manufacture of a grinding tool holder has been accomplished in this study. The optimal surface grinding parameters were determined using Taguchi’s orthogonal array method for plastic injection molding steel PDS5 on a machining center. The optimal surface grinding parameters for the plastic injection mold steel PDS5 were the combination of an abrasive material of PA Al2O3, a grinding speed of 18 000 rpm, a grinding depth of 20 μm, and a feed of 50 mm/min. The surface roughness Ra of the specimen can be improved from about 1.60 μm to 0.35 μm by using the optimal parameters for surface grinding. Surface roughness Ra can be further improved from about 0.343 μm to 0.06 μm by using the ball burnishing process with the optimal burnishing parameters. Applying the optimal surface grinding and burnishing parameters sequentially to a fine-milled freeform surface mold insert, the surface roughness Ra of freeform surface region on the tested part can be improved from about 2.15 μm to 0.07 μm.Keywords Automated surface finishing · Ball burnishing process · Grinding process · Surface roughness · Taguchi’s method1 IntroductionPlastics are important engineering materials due to their specific characteristics, such as corrosion resistance, resistance to chemicals, low density, and ease of manufacture, and have increasingly replaced metallic components in industrial applications. Injection molding is one of the important forming processes for plastic products. The surface finish quality of the plastic injection mold is an essential requirement due to its direct effects on the appearance of the plastic product. Finishing processes such as grinding, polishing and lapping are commonly used to improve the surface finish.The mounted grinding tools (wheels) have been widely used in conventional mold and die finishing industries. The geometric model of mounted grinding tools for automated surface finishing processes was introduced in. A finishing process mode of spherical grinding tools for automated surface finishing systems was developed in. Grinding speed, depth of cut, feed rate, and wheel properties such as abrasive material and abrasive grain size, are the dominant parameters for the spherical grinding process, as shown in Fig. 1. The optimal spherical grinding parameters for the injection mold steel have not yet been investigated based in the literature.Fig.1. Schematic diagram of the spherical grinding processIn recent years, some research has been carried out in determining the optimal parameters of the ball burnishing process (Fig. 2). For instance, it has been found that plastic deformation on the workpiece surface can be reduced by using a tungsten carbide ball or a roller, thus improving the surface roughness, surface hardness, and fatigue resistance. The burnishing process is accomplished by machining centers and lathes. The main burnishing parameters having significant effects on the surface roughness are ball or roller material, burnishing force, feed rate, burnishing speed, lubrication, and number of burnishing passes, among others. The optimal surface burnishing parameters for the plastic injection mold steel PDS5 were a combination of grease lubricant, the tungsten carbide ball, a burnishing speed of 200 mm/min, a burnishing force of 300 N, and a feed of 40 μm. The depth of penetration of the burnished surface using the optimal ball burnishing parameters was about 2.5 microns. The improvement of the surface roughness through burnishing process generally ranged between 40% and 90%.Fig. 2. Schematic diagram of the ball-burnishing processThe aim of this study was to develop spherical grinding and ball burnishing surface finish processes of a freeform surface plastic injection mold on a machining center. The flowchart of automated surface finish using spherical grinding and ball burnishing processes is shown in Fig. 3. We began by designing and manufacturing the spherical grinding tool and its alignment device for use on a machining center. The optimal surface spherical grinding parameters were determined by utilizing a Taguchi’s orthogonal array method. Four factors and three corresponding levels were then chosen for the Taguchi’s L18 matrix experiment. The optimal mounted spherical grinding parameters for surface grinding were then applied to the surface finish of a freeform surface carrier. To improve the surface roughness, the ground surface was further burnished, using the optimal ball burnishing parameters.Fig. 3. Flow chart of automated surface finish using spherical grinding and ball burnishing processes2 Design of the spherical grinding tool and its alignment deviceTo carry out the possible spherical grinding process of a freeform surface, the center of the ball grinder should coincide with the z-axis of the machining center. The mounted spherical grinding tool and its adjustment device was designed, as shown in Fig. 4. The electric grinder was mounted in a tool holder with two adjustable pivot screws. The center of the grinder ball was well aligned with the help of the conic groove of the alignment components. Having aligned the grinder ball, two adjustable pivot screws were tightened; after which, the alignment components could be removed. The deviation between the center coordinates of the ball grinder and that of the shank was about 5 μm, which was measured by a CNC coordinate measuring machine. The force induced by the vibration of the machine bed is absorbed by a helical spring. The manufactured spherical grinding tool and ball-burnishing tool were mounted, as shown in Fig. 5. The spindle was locked for both the spherical grinding process and the ball burnishing process by a spindle-locking mechanism.Fig.4. Schematic illustration of the spherical grinding tool and its adjustment deviceFig.5. (a) Photo of the spherical grinding tool (b) Photo of the ball burnishing tool3 Planning of the matrix experiment3.1 Configuration of Taguchi’s orthogonal arrayThe effects of several parameters can be determined efficiently by conducting matrix experiments using Taguchi’s orthogonal array. To match the aforementioned spherical grinding parameters, the abrasive material of the grinder ball (with the diameter of 10 mm), the feed rate, the depth of grinding, and the revolution of the electric grinder were selected as the four experimental factors (parameters) and designated as factor A to D (see Table 1) in this research. Three levels (settings) for each factor were configured to cover the range of interest, and were identified by the digits 1, 2, and 3. Three types of abrasive materials, namely silicon carbide (SiC), white aluminum oxide (Al2O3, WA), and pink aluminum oxide (Al2O3, PA), were selected and studied. Three numerical values of each factor were determined based on the pre-study results. The L18 orthogonal array was selected to conduct the matrix experiment for four 3-level factors of the spherical grinding process.Table1. The experimental factors and their levels3.2 Definition of the data analysisEngineering design problems can be divided into smaller-the better types, nominal-the-best types, larger-the-better types, signed-target types, among others [8]. The signal-to-noise (S/N) ratio is used as the objective function for optimizing a product or process design. The surface roughness value of the ground surface via an adequate combination of grinding parameters should be smaller than that of the original surface. Consequently, the spherical grinding process is an example of a smaller-the-better type problem. The S/N ratio, η, is defined by the following equation: η =?10 log10(mean square quality characteristic)=?10 log10 ????????niy12where:yi : observations of the quality characteristic under different noise conditions n: number of experimentAfter the S/N ratio from the experimental data of each L18 orthogonal array is calculated, the main effect of each factor was determined by using an analysis of variance (ANOVA) technique and an F-ratio test. The optimization strategy of the smaller-the better problem is to maximize η, as defined by Eq. 1. Levels that maximize η will be selected for the factors that have a significant effect on η. The optimal conditions for spherical grinding can then be determined.4 Experimental work and resultsThe material used in this study was PDS5 tool steel (equivalent to AISI P20), which is commonly used for the molds of large plastic injection products in the field of automobile components and domestic appliances. The hardness of this material is about HRC33 (HS46). One specific advantage of this material is that after machining, the mold can be directly used for further finishing processes without heat treatment due to its special pre-treatment. The specimens were designed and manufactured so that they could be mounted on a dynamometer to measure the reaction force. The PDS5 specimen was roughly machined and then mounted on the dynamometer to carry out the fine milling on a three-axis machining center made by Yang-Iron Company (type MV-3A), equipped with a FUNUC Company NC-controller (type 0M). The pre-machined surface roughness was measured, using Hommelwerke T4000 equipment, to be about 1.6 μm. Figure 6 shows the experimental set-up of the spherical grinding process. A MP10 touch-trigger probe made by the Renishaw Company was also integrated with the machining center tool magazine to measure and determine the coordinated origin of the specimen to be ground. The NC codes needed for the ball-burnishing path were generated by PowerMILL CAM software. These codes can be transmitted to the CNC controller of the machining center via RS232 serial interface.Fig.6. Experimental set-up to determine the optimal spherical grinding parametersTable 2 summarizes the measured ground surface roughness alue Ra and the calculated S/N ratio of each L18 orthogonal array sing Eq. 1, after having executed the 18 matrix experiments. The average S/N ratio for each level of the four actors is shown graphically in Fig. 7.Table2. Ground surface roughness of PDS5 specimenExp. Inner array (control factors) Measured surface roughness value (Ra) Responseno A B C D ??my?12???3S/N(η(dB))Mean??my?_1 1 1 1 1 0.35 0.35 0.35 9.119 0.3502 1 2 2 2 0.37 0.36 0.38 8.634 0.3703 1 3 3 3 0.41 0.44 0.40 7.597 0.4174 2 1 2 3 0.63 0.65 0.64 3.876 0.6405 2 2 3 1 0.73 0.77 0.78 2.380 0.7606 2 3 1 2 0.45 0.42 0.39 7.530 0.4207 3 1 3 2 0.34 0.31 0.32 9.801 0.3238 3 2 1 3 0.27 0.25 0.28 11.471 0.2679 3 3 2 1 0.32 0.32 0.32 9.897 0.32010 1 1 2 2 0.35 0.39 0.40 8.390 0.38011 1 2 3 3 0.41 0.50 0.43 6.968 0.44712 1 3 1 1 0.40 0.39 0.42 7.883 0.40313 2 1 1 3 0.33 0.34 0.31 9.712 0.32714 2 2 2 1 0.48 0.50 0.47 6.312 0.48315 2 3 3 2 0.57 0.61 0.53 4.868 0.57016 3 1 3 1 0.59 0.55 0.54 5.030 0.56017 3 2 1 2 0.36 0.36 0.35 8.954 0.35718 3 3 2 3 0.57 0.53 0.53 5.293 0.543Fig.7. Plots of control factor effectsThe goal in the spherical grinding process is to minimize the surface roughness value of the ground specimen by determining the optimal level of each factor. Since ?log is a monotone decreasing function, we should maximize the S/N ratio. Consequently, we can determine the optimal level for each factor as being the level that has the highest value of η. Therefore, based on the matrix experiment, the optimal abrasive material was pink aluminum oxide; the optimal feed was 50 mm/min; the optimal depth of grinding was 20 μm; and the optimal revolution was 18 000 rpm, as shown in Table 3.The optimal parameters for surface spherical grinding obtained from the Taguchi’s matrix experiments were applied to the surface finish of the freeform surface mold insert to evaluate the surface roughness improvement. A perfume bottle was selected as the tested carrier. The CNC machining of the mold insert for the tested object was simulated with Power MILL CAM software. After fine milling, the mold insert was further ground with the optimal spherical grinding parameters obtained from the Taguchi’s matrix experiment. Shortly afterwards, the ground surface was burnished with the optimal ball burnishing parameters to further improve the surface roughness of the tested object (see Fig. 8). The surface roughness of the mold insert was measured with Hommelwerke T4000 equipment. The average surface roughness value Ra on a fine-milled surface of the mold insert was 2.15 μm on average; that on the ground surface was 0.45 μm on average; and that on burnished surface was 0.07 μm on average. The surface roughness improvement of the tested object on ground surface was about (2.15?0.45)/2.15 = 79.1%, and that on the burnished surface was about (2.15?0.07)/2.15 = 96.7%.Fig.8. Fine-milled, ground and burnished mold insert of a perfume bottle5 ConclusionIn this work, the optimal parameters of automated spherical grinding and ball-burnishing surface finishing processes in a freeform surface plastic injection mold were developed successfully on a machining center. The mounted spherical grinding tool (and its alignment components) was designed and manufactured. The optimal spherical grinding parameters for surface grinding were determined by conducting a Taguchi L18 matrix experiments. The optimal spherical grinding parameters for the plastic injection mold steel PDS5 were the combination of the abrasive material of pink aluminum oxide (Al2O3, PA), a feed of 50 mm/min, a depth of grinding 20 μm, and a revolution of 18 000 rpm. The surface roughness Ra of the specimen can be improved from about 1.6 μm to 0.35 μm by using the optimal spherical grinding conditions for surface grinding. By applying the optimal surface grinding and burnishing parameters to the surface finish of the freeform surface mold insert, the surface roughness improvements were measured to be ground surface was about 79.1% in terms of ground surfaces, and about 96.7% in terms of burnished surfaces. 中文譯文基于注塑模具鋼研磨和拋光工序的自動化表面處理摘要這篇文章研究了注塑模具鋼自動研磨與球面拋光加工工序的可能性，它可以在數控加工中心完成注塑模具鋼 PDS5 的塑性曲面。這項研究已經完成了磨削刀架的設計與制造。 最佳表面研磨參數是在鋼鐵 PDS5 的加工中心測定的。對于 PDS5 注塑模具鋼的最佳球面研磨參數是以下一系列的組合：研磨材料的磨料為粉紅氧化鋁，進給量 50 毫米/分鐘，磨削深度 20 微米，磨削轉速為 18000RPM。表面粗糙度 Ra 值可由大約 1.60 微米改善至 0.35微米，通過用優(yōu)化的參數進行表面研磨。 如果用球拋光工藝和參數優(yōu)化拋光，還可以進一步改善表面粗糙度 Ra 值，一般從 0.343 微米至 0.06 微米左右。而在模具內部曲面的測試部分，用最佳參數的表面研磨、拋光，曲面表面粗糙度就可以提高約 2.15 微米至 0.07 微米。關鍵詞: 自動化表面處理 拋光 磨削過程 表面粗糙度 田口方法 一、引言由于塑膠工程材料的重要特點,比如耐化學腐蝕性、低密度、易于制造,并且已經日漸取代了金屬部件在工業(yè)中廣泛應用。 在注塑成型領域，其對于塑料制品是一個重要工藝。設計的本質要求是注塑模具的表面質量,因為它直接影響了塑膠產品的外觀和性能。 加工工藝如球面研磨、拋光常用于改善表面光潔度。圖 1 球面研磨過程示意圖研磨工具(輪子) 的安裝的磨削工具（車輪）已被廣泛地用在常規(guī)的模具和模具精加工產業(yè)。安裝的幾何模型的整理工序引入英寸甲球面磨削工具自動化表面精加工處理模式的狀態(tài)下，完成系統(tǒng)開發(fā)英寸磨削速度，切削深度，進給速率，如研磨材料和車輪屬性自動化表面的磨削工具。和磨料顆粒的大小，是用于球形研磨過程的主要參數，如在圖所示。1。的最佳的球形研磨參數用于注射模具鋼中尚未調查是根據在文獻中。步距研磨高度球磨研磨進給速度工作臺在最近幾年中，已經進行了一些研究，在確定球拋光過程（圖 2）的最優(yōu)參數。比如，已發(fā)現，可以減少使用的鎢硬質合金球或輥在工件表面上的塑性變形，從而改善表面粗糙度，表面硬度和耐疲勞性。拋光過程是通過加工中心和車床。主要的拋光參數，具有顯著的表面粗糙度的影響的滾珠或滾子材料，拋光力，進給速率，拋光速度快，潤滑和拋光通行證的數量，等等。最佳的表面的塑料注射模具鋼 PDS5 擠光參數的組合的潤滑脂，碳化鎢球的拋光速度為 200 毫米/ 分鐘，拋光力，300 N，和一個飼料為 40μm。使用的最佳球拋光參數的磨光表面的滲透深度為約 2.5 微米。通過拋光過程中的改進的表面粗糙度一般介于 40％和 90％之間。圖 2 球面拋光過程概略圖本文研究的目的是開發(fā)球面磨削球拋光表面處理工藝的自由曲面，塑料注塑模具加工中心。自動化表面精加工的流程圖中，使用球面磨削和球拋光過程示于圖 3 中。我們開始設計和制造的球面磨削加工中心上使用的工具，其定位裝置。最佳的表面球面磨削參數進行了測定，利用田口正交陣列的方法。四個因素，三個相應的級別，然后選擇為田口 L18矩陣實驗。的最佳安裝球面磨削參數，然后將其應用于自由曲面載體的表面光潔度的表面研磨。為了改善表面粗糙度，地面進一步打磨，使用的最佳球擠光參數。PDS 試樣的設計與制造選擇最佳矩陣實驗因子確定最佳參數實施實驗分析并確定最佳因子進行表面拋光應用最佳參數加工曲面測量試樣的表面粗糙度球研磨和拋光裝置的設計與制造圖 3 自動球面研磨與拋光工序的流程圖二、球研磨的設計和對準裝置要進行可能的球形研磨過程中的自由曲面，球研磨機的中心應與 z-軸的加工中心重合。的安裝的球形研磨工具和其調整裝置的設計，如在圖所示。4。電動研磨機中，安裝在工具保持架有兩個可調的樞軸螺釘。以及研磨機球的中心對準的圓錐槽的取向組分的幫助。對準的粉碎機球，兩個可調節(jié)的支點螺絲擰緊后，對齊組件可以被刪除。中心之間的偏差的坐標球研磨機的柄部的時間是約 5 微米，這是由一個數控三坐標測量機測量。由振動引起的力的機床吸收由一個螺旋彈簧。所制造的球形研磨工具和球磨光工具被安裝，如圖所示 5。主軸被鎖定的球面研磨過程和球拋光由主軸鎖定機構的方法。圖 4 球面研磨工具及其調整裝置圖 5 a 球面研磨工具的圖片. b.球拋光工具的圖片三、矩陣實驗的規(guī)劃3.1 田口正交表幾個參數的影響，可以有效地進行矩陣實驗田口直交。要與上述球形研磨參數相匹配，研磨機的球（直徑為 10 毫米） ，進給速度，磨削深度，和革命的電動研磨機的研磨材料被選定為四個實驗因素（參數）并指定為因子 A 到 D（見表 1） ，在本研究中。每個因子的三個層次（設置）被配置為覆蓋感興趣的范圍內，并確定了數字 1，2，和 3。三種類型的研磨材料，即，白色氧化鋁（Al2O3，WA） ，碳化硅（SiC）和粉紅色的氧化鋁（Al2O3，賓夕法尼亞州） ，選擇和研究。每個因子的三個數值的預研究結果的基礎上確定的。 L18 直模柄彈簧工具可調支撐緊固螺釘磨球自動研磨磨球組件交被選中的 4 個 3 級因素的球面磨削過程中進行矩陣實驗。表 1 實驗因素和水平水平因素1 2 3A. 碳化硅 白色氧化鋁 粉紅氧化鋁B. 50 100 200C.研磨深度（ μm） 20 50 80D. 12000 18000 240003.2 數據分析的界定 工程設計問題,可以分為較小而好的類型,象征性最好類型,大而好類型，目標取向類型等。 信噪比(S/N)的比值，常作為目標函數來優(yōu)化產品或者工藝設計。 被加工面的表面粗糙度值經過適當地組合磨削參數，應小于原來的未加工表面。 因此,球面研磨過程屬于工程問題中的小而好類型。這里的信噪比（S/N）,η,按下列公式定義: η =?10 log 平方等于質量特性10=?10 log（1）10????????niy2這里，y ——不同噪聲條件下所觀察的質量特性in——實驗次數從每個 L18 型正交實驗得到的信噪比（S/N）數據，經計算后，運用差異分析技術(變異)和殲比檢驗來測定每一個主要的因素。 優(yōu)化小而好類型的工程問題問題更是盡量使 η最大而定。各級 η 選擇的最大化將對最終的 η 因素有重大影響。 最優(yōu)條件可視研磨球而待定。四、實驗工作和結果本研究中所使用的材料是 PDS5 工具鋼（相當于 AISI P20） ，這種材料通常用于大型塑料注塑產品，汽車部件和國內家電領域中的模具。這種材料的硬度是 HRC33（HS46） 。這種材料的一個具體的優(yōu)點是，加工后，模具可直接用于進一步的精加工過程中未經加熱處理的，由于其特殊的前處理。試樣被設計和制造，使他們能夠被安裝在測力計來測量的反作用力。 PDS5 標本粗略加工，然后安裝在底盤測功機上進行精銑陽鋼鐵公司（MV-3A 型），配備一個 FUNUC 公司的 NC-控制器（0M 類型由一個三軸加工中心） 。預加工的表面粗糙度進行測定，使用 HOMMELWERKE T4000 設備，是約 1.6 微米。圖 6 示出了實驗設置的球狀的研磨過程。加工中心刀庫的協(xié)調原產地測量和確定的標本是地面還集成了一個MP10 觸發(fā)式探針由雷尼紹公司。 PowerMILL 的 CAM 軟件生成的 NC 代碼所需要的球擠光加工路徑的。這些代碼可以被發(fā)送到通過 RS232 串行接口的加工中心的 CNC 控制器。圖 6當完成了 L18 型矩陣實驗后，表 2 （PDS5 試樣光滑表層的粗糙度）總結了光滑表面的粗糙度 RA 值，計算了每一個 L18 型矩陣實驗的信噪比（S/N）,從而用于方程（1） 。通過表 2 提供的各個數值，可以得到四種不同程度因素的平均信噪比（S/N） ，在圖 7 中已用圖表顯示。表 2 PDS5 試樣光滑表層的粗糙度實驗 內部排列（控制因素） 測量表面粗糙度值（RA） 反應結果序號 A B C D ??my?12???3S/N(η(dB))Mean??my?_1 1 1 1 1 0.35 0.35 0.35 9.119 0.3502 1 2 2 2 0.37 0.36 0.38 8.634 0.3703 1 3 3 3 0.41 0.44 0.40 7.597 0.4174 2 1 2 3 0.63 0.65 0.64 3.876 0.6405 2 2 3 1 0.73 0.77 0.78 2.380 0.7606 2 3 1 2 0.45 0.42 0.39 7.530 0.4207 3 1 3 2 0.34 0.31 0.32 9.801 0.3238 3 2 1 3 0.27 0.25 0.28 11.471 0.2679 3 3 2 1 0.32 0.32 0.32 9.897 0.32010 1 1 2 2 0.35 0.39 0.40 8.390 0.38011 1 2 3 3 0.41 0.50 0.43 6.968 0.44712 1 3 1 1 0.40 0.39 0.42 7.883 0.40313 2 1 1 3 0.33 0.34 0.31 9.712 0.32714 2 2 2 1 0.48 0.50 0.47 6.312 0.48315 2 3 3 2 0.57 0.61 0.53 4.868 0.57016 3 1 3 1 0.59 0.55 0.54 5.030 0.56017 3 2 1 2 0.36 0.36 0.35 8.954 0.35718 3 3 2 3 0.57 0.53 0.53 5.293 0.543加工中心數控機床電腦圖 7 控制影響因素球面研磨工藝的目標，就是通過確定每一種因子的最佳優(yōu)化程度值，來使試樣光滑表層的表面粗糙度值達到最小。因為? log 是一個減函數，我們應當使信噪比（S/N）達到最大。因此，我們能夠確定每一種因子的最優(yōu)程度使得 η 的值達到最大。因此基于這個點陣式實驗的最優(yōu)轉速應該是 18000RPM。用于表面的最優(yōu)參數球面磨削，從田口的矩陣的實驗中，得到的施加到自由曲面模具，插入到評價的表面粗糙度的，改善的表面光潔度。香水瓶被選定為試驗的載體。數控加工的模具插入被測對象進行了模擬與電源廠 CAM 軟件。模具精銑后，插入進一步地從田口矩陣實驗獲得的最佳球面磨削參數。不久之后，地面的表面磨光的最佳球拋光參數來進一步改善表面粗糙度的測試對象（參照圖 8） 。模嵌件的表面粗糙度的測定與HOMMELWERKE T4000 設備。模具刀片上的精細研磨的表面的平均表面粗糙度值 Ra 為2.15 微米，平均的接地表面上的時間是 0.45 微米左右以及磨光表面上的時間是 0.07 微米左右。地面上被測物體的表面粗糙度（2.15-0.45 ）/2.15= 79.1％，而打磨得锃亮的表面上（2.15-0.07）/2.15= 96.7％。信噪比控制因素圖 8 被測物體表面粗糙度五、結論在這項工作中，在自由曲面上，塑料注塑模具的最佳工藝參數，其在自動球面磨削和拋光球表面后，再整理工藝加工中心而研制成功。安裝球面磨削工具（和其對齊組件）的設計和制造。通過最佳球形平面磨床磨削參數的測定進行矩陣實驗田口 L18。在最佳球面研磨參數的塑料注射模具鋼 PDS5 的磨料的組合材料的粉紅色的氧化鋁（Al2O3，PA）中，以 50 毫米/分鐘的進料，研磨 20μm 的深度，和一個 18000 革命轉。試樣的表面粗糙度 Ra可從約 1.6 微米至 0.35 微米，通過使用最優(yōu)球面的表面研磨的研磨條件來改善。通過采用最佳的表面研磨和拋光自由曲面模具鑲件的表面光潔度的參數，表面粗糙度測量，來改善地面約 79.1％的地面，約 96.7％，錚亮的表面。拋光表面Ra=0.07μm內部表面Ra=2.15μm光滑表面Ra=0.45μm