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中文翻译成形模具设计中的板料成形数值模拟与试制模具的比较A. ANDERSSON , , _当今，金属板料成形数值模拟是一种用于预测汽车零部件成形能力的强有力的技巧。与传统的方法比如使用试制模具，金属板料成形数值模拟在模具设计中应用程度的巨大的增加使实体模具在制造之前被测试成为可能。另外一种金属板料成形模拟的优点在于其可利用于工艺设计早期阶段，例如在最初的设计阶段。如今，金属板料成形数值模拟的结果的精确度在很大程度上已足够高，以致于可代替试制模具的使用。在沃尔沃汽车公司，车身部件工厂，该项研究已经被启动，金属板料成形模拟以集成的模块形式在模具设计与模具生产的工艺中被使用。1 引言传统地，试制模具被用于验证某种模具设计能否生产满足要求质量的零件。试制模具通常由比生产用模具更便宜的材料制成。这是一种很省时且节约成本的方式。但是，如今另外一种更为行之有效的技术可以使用金属板料成形模拟。这种新技术基于成形工艺的数值模拟，并且对于每套实用模具可以降低10%的成本和15%的生产时间。金属板料成形数值模拟技术不断的发展，并且模拟的结果越来越精确。在将来，或许可以使用金属板料成形数值模拟用于分析更多的工艺。如今，金属板料成形数值模拟的结果的精确度在很大程度上已足够高可代替试制模具的使用。2 方法该研究的目的在于分析和比较金属板料成形数值模拟和试制模具在成形模具设计中的优缺点。此研究中使用的方法基于专为该研究开发的产品可靠性模板（PSM) (Rundqvist and Stahl 2001年)和工艺一致性模板 (PCM)。PSM是一种把工艺中的不同因素（参数）按目录编入不同因素组的模板。然后每种因素（参数）的影响被评定为03等级。基于模板的结果，对产品工艺有最大影响的参数可以被筛选出来，然后可以制作折中或是最小化这些影响的优先表。PCM是通过高级专家测试在实际生产中对汽车元器件成形的连续测试来分析金属板料成形数值模拟、试制模具的结果，生产零件的质量3 设计成形模具的工艺图1所示，一种在沃尔沃汽车公司车身部件工厂（VCBC）的开发一种成形模具的简化生产工艺流程。一种成形模具设计的工艺包括试制阶段，该阶段各种不同的模具设计被测试。这是一个在模具设计工艺中很重要的阶段，目的在于验证零件将会满足所要求的质量。预测一种成形操作的结果是很困难的，但是通过使用金属板料成形数值模拟方法使得对成形操作的结果有价值的预测成为可能。零件/工艺最初的设计零件设计硬质模具/工艺设计试制模具金属板料成形数值模拟图1 VCBC设计成形模具的工艺方法3.1 金属板料成形数值模拟的使用金属板料成形数值模拟可以被利用到模具设计工艺的几个阶段。 起初设计的早期阶段，能够快速验证汽车元器件设计的不同的方案 预测并且验证成形工艺 改善现有的工艺3.1.1 金属板料成形数值模拟的需求 数值模拟软件 零件布局的CAD模型或模具成形表面的CAD模型 描述特定金属板料材料的参数 工艺参数 工作站（现今个人计算机的发展快速的提升以致于个人计算机在将来会成为一种强有力的替代） 一名有能力可以操作该软件并能够分析数值模拟结果的员工数值模拟软件。现今市场有各种各样的商业软件可供使用。为找到合适的软件，必须分析所使用的领域。考虑到用户界面友好性与软件柔性，软件包是不同的。在进行该项研究的VCBC，两种不同的软件包得以使用。一种是用户友好的可快速提供结果的AUTOFORM（2001）。该软件用于获取合理的模具集合形状的反复的分析工艺。另外一种软件是LSDYNA（2001），被用于验证AUTOFORM的结果。 CAD模型。为使用金属板料成形数值模拟方法分析零件或者模具设计，就需要该零件或者模具的CAD模型。这种模型可以在大多数CAD软件中构造。例如，在VCBC使用的CATIA软件。不同的数值模拟软件需要不同类型的CAD模型。 材料参数。单向拉深实验被用于描述材料参数。同样有必要描述材料内部断裂的风险。描述断裂的数据是通过创建成形极限曲线来获取的。成形极限曲线是一种显示在断裂发生前最大许用应力数值的描绘在基准应力平面上的曲线。更为透彻的描述由Pearce于1991年提出。 工艺参数。金属板料成形数值模拟需要核实的工艺参数。 工作站。用于进行金属板料成形数值模拟的模型通常很大以致于为获得核实的运算时间而需要使用工作站。但是，个人计算机技术的发展使几台PC联网成为可能，这有可能会是工作站的替代。 有能力的员工。为读懂金属板料成形数值模拟的结果，能够输入正确的数据并且拥有理解结果的能力是狠必要的。这就需要有能力的员工。这种能力应该包括成形知识和数值模拟知识这由于考虑到生产工艺与翻译结果二者的联系。表1 V-1158.的材料数据壁厚(mm)Rp0.2屈服强度(Mpa)Rm抗拉强度极限(MPa)n 值(平均值)R 值(平均值)0.81403200.2431.763.2 金属板料成形数值模拟的结果金属板料成形数值模拟式如下的研究成为可能： 壁厚的分配 断裂的几率 拉深线 起皱 拉深/冲孔的压力 表面缺陷 表面的稳定性 弹性回复 材料行为 工艺监测 内部拉深 成形视窗 力（凸模、冲孔）图2 壁厚的分配蓝色区域显示变薄20%，红色10%为验证可能的结果对VolvoS80的车身外侧的数值模拟进行了研究。用于该种汽车元器件的材料是一种有着良好成形能力的中碳钢(V1158)。材料的参数如表1所示。3.2.1 壁厚的分配。金属板料成形数值模拟可以为部件壁厚的分配提供一个良好的近似值。在汽车工业对于考虑到壁厚减少的最大的许用量有要求，以确保在碰撞事故中的安全区域。3.2.2 断裂的几率成形工艺过程中可以使用成形极限曲线的方法评定断裂的几率，该几率已在此部分的最初时间被描述好。图3 断裂的几率。图中，裂纹以红色显示。右侧黑线代表成形极限曲线。同样显示数值模拟的结果（蓝色点）图4 图中的深蓝色线显示材料在成形操作时的流动情况。如果材料流过圆角，零件上就会出现拉深线。如果拉深线出现在外观零件的可见表面，该零件就会因质量原因而废掉。3.2.3 拉深线拉深线发生于当一个可见的零件外部区域通过圆角滑入当成形时。零件表面一点流动方式的曲线在数值模拟器件即出现这些线。拉深线在外部零件的可见表面是不应该出现的。在描述成形能力的图5，有足够应变的表面可以看到。通过共同研究这些使预测这些表面的稳定性成为可能。这是一种简化的分写。一种更为细致分析将会包括最终零件的应力与应变的联系。图5该图显示对工艺监测的一个实例。很容易理解成形工艺期间起皱的扩展情况3.2.4 起皱可见的起皱在零件上市不允许的。这些可以通过金属板料成形数值模拟来监测。3.2.5 力为以一种精确的方法测量工艺，必须要知道哪些力对成形该零件是必要的。这些力的数据可以从金属板料成形数值模拟的结果中获取。3.2.6 表面缺陷汽车外部零件对可能发生于成形期间的表面的翘曲很敏感。这些翘曲可能很小但是零件喷涂后仍然可见，这就意味着这个零件必须被废弃。这种缺陷可以通过人工检查到当它在表面轻微移动的时候。金属板料成形数值模拟通过对盈利应变分配的分析可以被用于监测危险区域3.2.7 表面的稳定性稳定的表面的获得目的为增大零件的刚度以阻止零件的不稳定和振动。金属板料成形数值模拟可以通过对应变分配的分析用于监测危险区域。图6 上图显示成形能力。上图中的灰色区域暗指不稳定的区域，粉红色区域则为起皱区域。在下图中指示受压小约束表面标记为蓝色。如果这些区域位于外观零件的可见表面，则存在产生不稳定区域的可能性。3.2.8 弹性回复弹性回复可以被用于描述在制件被取出成形模具后发生的一种几何形状的变化。这种几何形状的变化导致该零件与其他零件进行装配式的不匹配。3.2.9 工艺监测在金属板料成形数值模拟中，这种工艺可以通过动画的方式细致地而执行。3.2.10 拉深为使材料的消耗最小，优化毛坯的外形是很重要的。金属板料成形数值模拟可以通过分析内拉深工艺最大程度的充分利用坯料。3.2.11 成形视窗成形视窗可以被描述为工艺参数的许用变动范围。目的在于保证生产零件的质量。3.3 试制模具的使用试制模具当工艺方法设计需要验证时被使用（如图1）。基于这种设计试制模具用锌合金铸造。例如，快速原型零件从这种试制模具中生产出来。试制模具与生产模具制件有几点不同。因此，在试制模具中生产如此多的零件是不可能的。另外一点不同在于试制模具比生产模具要便宜更多。但是，由于两种形式模具件的区别的存在，对于在这两种形式模具中生产处的零件有同样的质量没有保证。图7 蓝绿色线显示坯料闭合后的板料位置。拉深线即可以通过与底部区域的线的比较测量。4 产品可靠性模板(PSM)PSM可以用于确定哪个参数对工艺的稳定性有巨大的影响。同样使确定某种影响的程度成为可能。这就为对大多数极其困难的问题提供了数值上的帮助。这些极困难的问题就特别的有趣当他们被解决的时候因为他们是最降低效率的。对PSM更为细致的描述由Rundqvist 和 Stahl 于2001年提出。一个PSM被使用的例子由. Pettersson于1991年提出，在该例子中在VCBCPSM被用于分析不同的工艺。5 结果使用试制模具的技巧已经与金属板料成形数值模拟的技巧从两个方面进行了比较。第一方面是预测生产工艺不同的参数的能力，在第3部分已经提到。第二方面是验证哪个工艺参数应该加以研究的能力。5.1 预测工艺与生产工艺一致性的研究PCM提供试制模具与数值模拟考虑生产工艺的相关性透彻的比较。表2显示应用的不同领域不同的技巧与能力预测在生产工艺中的行为。表2 的数值已经通过与高级成形专家深入的研究而确定。表2中，使用到下面的等级5 结果显示与生产工艺非常一致。44 结果显示与生产工艺良好的一致。个别地方可能有分歧。3 结果显示与生产工艺在大多数地方较好的一致。2 结果显示与生产工艺在某些地方较好的一致。需要对结果进行间接地理解。1 结果显示与生产工艺完全没有一致性。它不能被用于工艺预测或者是检验。对于表2的结论包括如下 断裂的几率与实际断裂间的差异在于断裂几率显示区域没有发生裂纹而是缩颈出现的地方。 参数“材料特点”指的是预测零件质量的能力依赖于材料质量的波动。 工艺监测使控制在工艺过程中不同参数的如何改变成为可能。 成形视窗对于监测工艺对波动的敏感程度是一个辅助工具。 模具冲裁力的数值基于可以测量试制模具中的成形力的假设。表2 工艺一致性模板（PCM）：产品工艺的一致性参数工艺壁厚分配断裂几率断裂拉深线起皱表面缺陷表面的稳定性弹性回复材料性能工艺监测内部拉深凸模冲压力拉深量冲裁力成形视窗数值模拟444442224443224试制模具3343444323434335.2 对于生产工艺中何种因素可以分析的研究依据PSM模型，将对生产工艺有特殊性的不同因素分成不同因素组的放啊已经被运用在此次研究中。在先前的研究中(Andersson et al. 1999年)，关于这两种铝成形的技巧的不同因素已经被研究了。在这项研究中为方便的比较这两种技巧由于预测和验证被考虑这项工作得以修正。在表3中，使用到下面的等级3 结果显示对生产工艺极好的预见性。2 结果显示对生产工艺直接的预见性。1 结果显示对生产工艺间接地预见性。0 结果根本不能预测生产工艺。5.3 测试能力的局限/扩大对表2和表3的分析显示出在模具设计工艺过程中使用金属板料成形数值模拟的几个优点。然而，金属板料成形数值模拟的最大优点之一在于其使对不同零件、模具或是工艺的设计的测试成为可能，从而潜在的节省了时间和金钱。在这个方面，试制模具更为局限和昂贵，这就意味着仅有极少数量的试制模具被生产出来。试制模具的使用对测试有助于可能性的局限，然而，金属板料成形数值模拟的使用有助于测试可行性范围的扩大。表3 利用PSM预测生产工艺中的不同因素（参数）的比较的可能性考虑试制模具中的测量力的可能性因素分组金属板料成形数值模拟试制模具A模具A1模具几何外形22A2微观形状/表面01A3拉深筋12B材料B1壁厚分配22B2断裂的几率22B3拉深线22B4起皱22B5表面缺陷12B7表面稳定性12B8弹性回复12B9材料性能22B10内部拉深22B11表面粗糙度、擦损02C工艺C1冲压速度12C2温度01C3润滑12C4凸模冲压力22C5冲孔冲压力22C8成形视窗22D人为因素D1控制12D2变换频率12E维护E2冲压力维护11F特殊因素F1模具洁净成素02G进口设备G1操控设备136 结论金属板料成形数值模拟的使用与试制模具的使用相比可极大地减少金钱和时间的花费。要点在于研究的数值模拟与实际生产工艺参数之间的良好的一致性。金属板料成形数值模拟对于预测和验证成形工艺也要比试制模具高级。当开始使用金属板料成形数值模拟时，所需投入相对较小。投入工作站和软件是很必要的，这些大概花费500，000SEK。此外，拥有有能力胜任金属板料成形模拟工作的员工同样是比不可少的。与投资一套试制模具（每套50，000SEK）相比，如果在合适的时候使用金属板料成形数值模拟在降低金钱和时间消耗方面的益处是很明显的。正如起初是所提到的，现今金属板料成形数值模拟结果的精确性已足够高可以在很大程度上代替试制模具的使用。模具设计工艺中试制模具的使用对于某些时候对于验证某些工艺参数可能是必要的，但是如下的优点则很紧密的和金属板料成形数值模拟联系在一起。对于极重要的最初阶段工艺的更为深入的研究;对于零件，模具和工艺设计测试的更高的柔性;对于何时应该采用试制模具，使试制模具更具成效的更为深入的理解;对于更大胆的设计汽车提供更大的潜力;对于应用于汽车零部件的新材料的测试的更为可靠;鉴于更前卫的设计，更低的耗费，和更短的交货时间以得到更强的竞争力。7 总结在该项研究得以进行的VCBC，金属板料成形数值模拟现今已经是模具设计工艺的一个自然的部分。金属板料成形数值模拟自从1995年起被使用，并且试验一直很好。现如今所有的工艺如此的复杂以致于基于数值模拟的试验选择成形条件是困难的。在VolvoS80开发期间，该车是第一款全部使用数值模拟技术的汽车项目，当第一次被投入实际生产时在工艺问题上有很大的降低得以完成。致 谢作者想要表达对VCBC的同事，此项工作期间提供大量的数据信息和有趣的讨论。同样的感谢他的导师Jan-Eric Stahl教授（产品与材料工程分院，兰德大学），和他的合作导师Kjell Mattiasson教授（Chalmers University of Technology)，感谢他们的支持以及对该文章的修正。57 英文资料Comparison of sheet-metal-forming simulation and try-out tools in the design of a forming toolA. ANDERSSONToday, sheet-metal-forming simulation is a poAwerful technique for predicting the formability of automotive parts. Compared with traditional methods such as the use of try-out tools, sheet-metal-forming simulation enables a significant increase in the number of tool designs that can be tested before hard tools are manufactured. Another advantage of sheet-metal-forming simulation is the possibility to use it at an early stage of the design process, for example in the preliminary design phase.Today, the accuracy of the results in sheet-metal-forming simulation is high enough to replace the use of try-out tools to a great extent. At Volvo Car Corporation, Body Components, where this study has been carried out, sheet-metal-forming simulation is used as an integrated part in the process of tool design and tool production.1 IntroductionTraditionally, try-out tools are used to verify that a certain tool design will produce parts of the required quality. The try-out tools are often made of a cheaper material (e.g. kirksite) than production tools in order to reduce the try-out costs. This is a very time-consuming and cost-consuming method. However, today another more efficient technique is availablesheet-metal-forming simulation. This new technique is based on the simulation of the forming process, and could result in a cost reduction of factor 10 and a time reduction of factor 15 for each hard tool. Sheet-metal-forming simulation technology is constantly developing and the results of the simulations aremore and more accurate. In the future it will also be possible to analyse more processes using sheet-metal-forming simulations. Today, the accuracy of the results in sheetmetal- forming simulation is high enough to replace the use of try-out tools to a great extent.2 MethodThe purpose of this study is to analyse and compare the benefits and drawbacks of the use of sheet-metal-forming simulation and try-out tools in the design of forming tools. The method employed in this study is based on the Production Reliability Matrix (PSM) (Rundqvist and Stahl 2001) together with a Process Correspondence Matrix (PCM) that has been developed especially for this study. The PSM is a matrix that categorizes the effects of different factors (parameters) in the process into different factor groups. The effect of each factor (parameter) is then assessed according to a scale of 03. Based on the results of the matrix, the parameters that have the most considerable effects on the production process can be extracted, and a priority list for neutralizing or minimizing these effects can be made. The PCM has been developed through extensive interviews of senior experts in automotive component forming to analyse the correspondence between the results of sheet-metalforming simulations, the try-out tool and the quality of produced parts in actual production.3 Process for designing a forming toolFigure 1 shows a simplified flow of the production process of developing a forming tool at Volvo Car Corporation, Body Components (VCBC).The process of the design of a forming tool includes a try-out phase where different designs of the tool are tested. This is a very important stage in the tool design process,in order to verify that the part will fulfil the required quality. It is very difficult to predict the result of a forming operation, but by using sheet-metal-forming simulation there is a possibility to gain valuable insight into the outcome of the forming operation.3.1 Use of sheet-metal-forming simulationSheet-metal-forming simulation can be used in several stages of a tool design process:early in the preliminary design phase, to enable rapid verification of different proposals for the design of automotive componentsto improve an existing process.Preliminarydesign of partPart layoutHard forming tools/Process designTry-outtoolsSheet metal forming simulationFigure 1. Process for designing a forming tool at VCBC.3.1.1. Requirements for sheet-metal-forming simulation. Sheet-metal-forming simulation requires the following:Simulation software.A computer-aided design (CAD) model of the part layout or a CAD model of the forming surfaces of the tool.Parameters for description of the specified sheet-metal material.Process parameters.Workstations (today the development of the personal computer (PC) is rapidly advancing so that PCs will be a strong alternative in the future).A competent staff that can handle the software and analyse the results of the simulation.Simulation software. Today there is a variety of commercial software available on the market. In order to find suitable software, the area of use must be analysed. The software package is different with regard to user-friendliness and flexibility.At VCBC, where this study was performed, two different software packages are used. One is Autoform (2001), which is user-friendly and provides fast results. This software is used for the iterative process of finding the proper tool geometry. The other software is LS-DYNA (2001), which is used at VCBC to verify the results ofAutoform.CAD model. In order to analyse a part or a tool design using sheet-metal-forming simulation, a CAD model of the part or tool is needed. This model can be created in most CAD programs, for instance CATIA, which is used at VCBC. Different simulation software demand different qualities of the CAD models.Material parameters. Uniaxial tensile tests are used to describe the material parameters. There is also a need for describing the risk of fracture in the material. Data regarding risk for fracture are obtained by creating a forming limit curve. The forming limit curve is a curve in the plane of principal strains that indicates the maximum allowed strain values before fracture occurs. A more thorough description is presented in Pearce (1991).Process parameters. Sheet-metal-forming simulation requires proper process parameters (e.g. drawbeads).Workstations. The simulation models that are used in sheet-metal-forming simulation are generally so large that they require a workstation in order to achieve reasonable calculation times. However, the development of PCs enables the clustering of several PCs, which can be an alternative to workstations.Competent personnel. In order to interpret the results of a sheet-metal-forming simulation, it is necessary to enter the correct input data and possess the ability to understand the results. This requires competent personnel. The competence should consist of both forming knowledge and simulation knowledge since that gives a natural connection between the production process and the interpretation of the results.Thickness(mm)Rp0.2yield strength(Mpa)Rm ultimatetensile strength(MPa)n value(average)R value(average)0.81403200.2431.76Table 1 Material data for V-1158.3.2. Results of a sheet-metal-forming simulationSheet-metal-forming simulation enables the study of:Thickness distribution.Risk of fracture.Draw lines.Wrinkles.Drawbeads/ blankholder pressure.Surface defects.Stability of the surface.Springback.Material behaviour.Process surveillance.Draw in.Forming window.Forces (punch, blankholder).In order to demonstrate possible results, a simulation of a Body Side Outer from a Volvo S80 has been studied. The material used for this automotive component is a mild steel with good formability (V-1158). Material data are presented in table . Thickness distribution. The sheet-metal-forming simulation can provide a good approximation of the thickness distribution for a part (see figure 2). In the automotive industry there are requirements concerning the maximum allowable reduction in thickness, in order to ensure safety margins in the event of a crash.Figure 2. Thickness distribution. The scale shows blue for 20% thinning and red for 10% thickening.3.2.2. Risk for fracture. Risk for fracture during the forming process could be evaluated by means of a forming limit curve, which was described earlier in this section.Figure 3. Risk for fracture. In this image, cracks are shown in red. To the right is the forming limit curve represented by the black line. Shown also are the results of the simulations (blue points)3.2.3. Draw lines. Draw lines occur when a visible section of an exterior part has been gliding over a radius during forming. A plot of how a point on the part surface moves during the simulation (see figure 4) illustrates these lines. Draw lines are not acceptable on a visible surface on an exterior part.In figure 5, which describes formability, surfaces with enough strains to be stable can be seen. By studying these images together it is possible to estimate the stability of the surfaces. This is a simplified analysis. A more detailed analysis would include the interaction between stresses and strains for the complete part.Figure 4. The blue dark line in the image shows how the material has flowed during the forming operation. If the material has flowed over a radius, a draw line will appear on the part. If the draw line appears on a visible surface of an exterior part, the part will be rejected for quality reasons.Figure 5. The images show an example of surveillance of the process. It is easy to follow how the wrinkles develop during the forming process.3.2.4 Wrinkles. Visible wrinkles are not allowed on a part. These can be detected with sheet-metal-forming simulation (see figure 6).3.2.5 Forces. In order to dimension the process in an accurate way, it is necessary to know which forces are necessary to form the part. The data for these forces can be obtained from the results of a sheet-metal-forming simulation.3.2.6 Surface defects. Exterior automotive parts are sensitive to deflections of the surface that can occur during forming. These deflections can be very small but can still be visible after the part is painted, which means that the part must be scrapped.The defects can be detected by the human hand as it moves gently across the surface.Sheet-metal-forming simulation can be used for detecting risk areas through analysis of the stress strain distribution.。3.2.7 Stability of the surface. Stable surfaces are required in order to increase the stiffness of the part to prevent the part from becoming unstable and vibrating. Sheet-metal-forming simulation can be used for detecting risk areas through analysis of the strain distribution. Figure 6 describes a simplified analysis. A more detailed analysis would include the interaction between stresses and strains for the complete part.。Figure 6. The upper image shows the formability. The grey areas in the upper image indicate unstable surfaces and the pink area indicates wrinkles. In the lower image the surfaces with small strains are marked blue, which indicates compression. If these areas are located on a visible surface of an exterior part, there is a risk for unstable areas.3.2.8 Springback. Springback is a phenomenon that could be described as a change in geometry that occurs after the parts have been removed from the forming tool. This g eometry change causes mismatch for the part when it is assembled with other parts.3.2.9 Process surveillance. In sheet-metal-forming simulation, the process can be followed in detail by means of animations. Figure 5 illustrates this.3.2.10 Draw in. To minimize material consumption, it is important to optimize the shape of the blank. Sheet-metal-forming simulation can facilitate optimization of the blank by analysing the draw in (see figure 7).3.2.11 Forming window. A forming window could be described as the allowable variation of the process parameters in order to keep the quality of the produced parts.3.3. Use of try-out toolsTry-out tools are used when the design of the process is to be verified (see figure 1).Based on this design the try-out tools are then cast in kirksite, for example. Prototype parts are then produced from this try-out tool. There are several differences between a try-out tool and a production tool. One is that the try-out tool wears out much faster than a production tool. Therefore, it is not possible to produce so many parts in a try-out tool. Another difference is that a try-out tool is much cheaper than a production tool. However, since there are differences between the two types of tools, there is no guarantee that the parts produced in the two types of tools will have the same quality.The PSM can be used to determine which parameters have significant effects on the stability of the process. It is also possible to determine the extent of an effect. This provides valuable help in the identification of the most severe problems. These severe problems are especially interesting since they are the most cost-effective when solved. A more detailed description of the PSM is presented by Rundqvist and Stahl (2001). An example where the PSM is applied is presented in Pettersson (1991), where the PSM is used to analyse different processes at VCBC.Figure 7. The cyan line shows the sheet position after blankholder closing.The draw in can then easily be measured by a comparison with the line in the bottom position.5 ResultThe technique of using try-out tools has been compared with the technique of using sheet-metal-forming simulation from two aspects. The first aspect is a comparison of the ability to predict the different parameters of the production process, mentioned in section 3. The second aspect is the ability to verify which process parameters should be studied.5.1 Study of agreement of predicted process with production processThe PCM allows a clear comparison between try-out tools and simulation regarding correspondence with the production process. Table 2 presents the different fields of applications for the different techniques together with the ability to predict behaviour in the production process. The values in table 2 have been determined through extensive interviews with senior forming experts.In table 2 the following scale is used:5 The results show perfect agreement with the production process.4 The results show good agreement with the production process. Special cases can deviate.3 The results show good agreement in most cases with the production process.2 The results show good agreement in certain cases with the production process. Indirect interpretation of the results is needed.1 The results show no agreement with the production process. It cannot be used for process prediction or verification.Comments on table 2 include the following: The difference between risk for fracture and actual fracture is that risk for fracture shows areas that have not cracked but where necking has appeared.The parameter Material characteristics refers to the ability to predict the quality of the part depending on variation in the material quality. Process surveillance enables the monitoring of how different parameters change during the process.The forming window is an aid for detecting how sensitive the process is to disturbances.The values for the tool forces are based on the assumption that it is possible to measure the forces in the try-out cessThickness distributionRisk for fractureFractureDraw linesWrinklesSurface defectsStability of the surfacespringbackMaterial propertiesProcess surveillanceDraw inForce-punchDraw beadsBlankholder forceForming windowsimulation444442224443224Try-out tool334344432343433Table 2. Process Correspondence Matrix (PCM): correspondence with the production process.5.2 Study of which factors in the production process are possible to analyseThe concept of grouping different factors that are typical for the production process into different factor groups has been used in this study according to the PSM model. In a previous study (Andersson et al. 1999), different factors concerning the forming of aluminium were studied. This work has been modified in order to facilitate a comparison between the two techniques for prediction and verification considered in this study; namely, sheet-metal-forming simulation and try-out tools. See table 3 for the results.In table 3 the following scale is used:3 The results show perfect prediction of production process.2 The results show direct prediction of production process.1 The results show indirect prediction of production process.0 The results cannot predict production process at all.5.3. Restriction /expansion of test possibilitiesAn analysis of tables 2 and 3 shows several advantages of using sheet-metal-simulation in the tool design process. However, one of the biggest advantages of sheetmetal- forming simulation is that it enables the testing of many different designs of the part, tool or process, which generates substantial savings in costs and time. In this respect, try-out tools are more limited and expensive, which means that only a minimum number of try-out tools are produced. The use of try-out tools contributes to a restriction of test possibilities while the use of sheet-metal-forming simulation contributes to an expansion in test possibilitie6. ConclusionsThe use of sheet-metal-forming simulation leads to a significant reduction in both cost and time compared with the use of try-out tools. The requirement is that the respective parameter for study (see section 3.1.2) demonstrates good correspondence between simulation and actual production processes. Sheet-metal-forming simulation is also superior to try-out tools with regard to predicting and verifying the forming process. The investment requirements are relatively small when starting to implement sheet-metal-forming simulation. It is necessary to invest in a workstation and software, which cost about SEK 500,000. In addition, it is necessary to have competent personal for handling the sheet-metal-forming simulation. Compared with the investment for one try-out tool (.SEK 500,000 per tool), it is clear that there is a lot to gain in reducing cost and time if sheet-metal-forming simulation is used when it is suitable.Factor gruupsSheet-metal-formingsimulationThy-out toolsAToolingA1Tool geometry22A2Microgeomertril/Surface01A3Drawbeads12BMaterialB1Thickness distribution22B2Risk for fraction22B3Draw lines22B4Wrinkles22B5Surface defects12B7Surface stability12B8Springback12B9Material properities22B10Draw in22B11Surface roughness/galling02CProcessC1Press velocity12C2Temperature01C3Lubrication12C4Forces-punch22C5Forces-blankholder22C8Forming-window22DHuman factorD1Control12D2Change frequency12EMaintenaceE2Press maintenace11FSpecial factorsF1Tool cleaning02GMisc equipmentG1Handling equipment13Table 3. The possibilities to predict different fact