当前位置：文档之家 › 2. Robust Process Design and Springback Compensation of a Decklid Inner

2. Robust Process Design and Springback Compensation of a Decklid Inner

  • 格式：pdf
  • 大小：509.92 KB
  • 文档页数：5

Robust Process Design and Springback Compensation of aDecklid InnerXiaojing Zhang a*, Peter Grimm b and Bart Carleer aWeimin Jin c, Gang Liu c and Yingchao Cheng ca AutoForm Engineering Deutschland GmbH, Emil-Figge-Strasse 76-80, Dortmund, D-44227, Deutschlandb AutoForm Engineering Deutschland GmbH, Marktstrasse 46, Ravensburg, D-88212, Deutschlandc Shanghai Volkswagen Automotive Company Limited, No 5288 CaoAn Road, Anting, Shanghai 201805 P.R.ChinaAbstract. Springback compensation is one of the key topics in current die face engineering. The accuracy of the springback simulation, the robustness of method planning and springback are considered to be the main factors which influences the effectiveness of springback compensation. In the present paper, the basic principles of springback compensation are presented firstly. These principles consist of an accurate full cycle simulation with final validation setting and the robust process design and optimization are discussed in detail via an industrial example, a decklid inner.Moreover, an effective compensation strategy is put forward based on the analysis of springback and the simulation based springback compensation is introduced in the phase of process design. In the end, the final verification and comparison in tryout and production is given in this paper, which verified that the methodology of robust springback compensation is effective during the die development.Keywords: Finite Element, Sheet Metal Forming, Springback, Springback Compensation, Robust Process DesignPACS: 02.70.Dh, 02.60.Cb, 81.20.Hy, 02.70.RrINTRODUCTIONSpringback is an inevitable issue in the field of die face engineering, which not only influences on the assembly of vehicle, the cost of the tool development, but also influences on the development cycle of new car models. In the past, springback compensation was done manually by doing extensive measurements on prototype or even production tools, and altering tool geometry by hand, which is a highly time consuming and cost-prohibitive process.With the development of finite element technologies, particularly with the recent improvement of springback prediction, a new simulation-based springback compensation technology, so-called “robust springback compensation”, and aims at eliminating the physical compensation loops and reducing the tryout cost, has been developed [1,2].In the present paper, the basic working flow of robust springback compensation is presented, and the key technologies, including robust design and compensation strategy, are discussed and implemented via an industrial part, decklid inner. In the end of the final verification and comparison in tryout and production shops is given.THE DESCRIPTION OF INDUSTRIAL PARTThe industrial part, which is used for discussion of robust springback compensation in this paper, is a decklid inner from car model Skoda Rapid of Shanghai Volkswagen. The aim of this project is to enhance the usage level of CAE technologies along the whole process chain and to implement the new technology of robust springback compensation into Shanghai Volkswagen. Figure 1 a) shows the desired part and the blank shape of decklid inner. The blank material is EN10346 DX56D +Z100MB and the thickness is 0.6mm.The blank width is 1480mm and the blank length is 1023mm. Fig. 1 b) illustrates the process layout of decklid inner, including the operations of drawing (OP20), piercing & trimming (OP30), piercing & trimming (OP40), piercing (OP50) and restriking & flanging (OP60). The blank holder force of drawing operation is 125 ton and the friction coefficient is 0.15. The inspection tool is in car position.THE BASIC WORK FLOW FOR ROBUST SPRINGBACK COMPENSATION To obtain a robust and reliable springback compensation, a work flow of robust springback compensationa) The part shape & blank outline b) The process layoutFIGURE 1. The part shape, blank outline and the process layout of decklid inner(showed in Figure 2), is suggested by AutoForm. Basis of this workflow are the five principles for the successful springback compensation:∙The proper basic full cycle simulation, to ensure no critical changes of the tool in tryout.∙The accurate springback simulation with AutoForm final validation settings [1].∙The well-defined minimum clamping concept, to make sure that no springback is eliminated by overconstraint and the total amount of springback compensation is as small as possible.∙Robust process and springback, to make sure that both process and springback are stable.∙Reliable compensation strategy and the compensation methodology, to make sure that the compensation is effective.The detail explanation of the basic working flow and the principles can be founded in the articles [2, 3].FIGURE 2. The basic work flow of robust springback compensationTHE ROBUST DESIGN AND THE OPTIMIZATION OF METHOD PLANNING Stamping tool development is a challenging process. Any error, which is created in each phase of the process and manufacturing chain, can be accumulated and influences the final result. Moreover, the variation of material properties and process parameters in the manufacturing process is inevitable in practice as well. All these manufacturing noise and manufacturing errors will influence the stability of the final part. Especially for the springback, a stress-sensitive phenomenon can be significantly influenced by these noise and errors, in some cases, even the direction of springback, which introduces great challenge of springback compensation.To ensure the quality of springback compensation, striving for a wide process window during the optimization of method planning, so-called “robust design”, is necessary and strongly recommended. With the help of the robustdesign, the springback and springback compensation can be more stable, the tryout effort can be significantly reduced and the rejection rate of the part in production can be reduced as well.Fig. 3 a) shows the original simulation result in OP20 (above) and OP60 (below) before robust design and optimization. Where, the result shows that the formability is green and no risk will occurs in tryout. However, if we consider the manufacturing noise with the help of robust analysis (based on AutoForm-Sigma), the risks will be clearly determined (marked with orange circles in Fig. 3 b)). This indicates that the process is not stable, and risk of split will exist in the production or tryout. Therefore, tool geometry change in tryout might be unavoidable, and the effort of simulation-based springback compensation might be destroyed. To reduce the risk of the springback compensation, additional optimization of the method planning for a more robust process window, has to be introduced (Fig. 3 c)). Fig 3 d) shows the final result of robust design, which is not only “green”for individual boundary condition, but also “green” responding to manufacturing noise. With the help of robust design, the reliable springback compensation is expected, and less effort of tryout and lower rejection rate of part is expected as well.FIGURE 3. The robust design and optimization of decklid innerTHE COMPENSATION STRATEGYTo define a reliable compensation strategy, the method planning engineer has to first understand where the springback comes from, and then try to reduce the springback as much as possible. Only when the springback can’t be reduced further via the optimization of method planning, should springback compensation be considered. Moreover, the successful springback compensation should not only concentrate on an effectiveness of compensation strategy, but also consider the cost of compensation and the risk of tryout.Due to the fact the springback of decklid inner results from both drawing operation (OP20) and flanging & restriking operation (OP60), and the operation of OP30, OP40 and OP50 involve in only trimming and piercing process, a special compensation strategy, which is showed in Fig. 4, is put forward in this paper. So only the tool geometries of OP20 and OP60 are compensated based on the final springback result. With such kind of compensation strategy, both the cost of compensation and the risk during tryout can be well reduced in practice.FIGURE 4. The compensation strategy of decklid innerFig. 5 illustrates the definition of the compensation region of OP20 and OP60 in AutoForm-Springback compensator. With only 2 iteration loops of compensation, the final geometric deviation between sprung part and desired shape is well-controlled inside ±0.3mm in the simulation, which confirms that the current compensation strategy is reliable.FIGURE 5. The springback compensation of decklid innerTHE VERIFICATION OF TRYOUT AND PART PRODUCTION To ensure an identical approach between engineering and tryout, all the processes of tool development, including process design, milling data preparation and tryout etc. should be adjusted carefully. Only basic polishing & spotting was allowed in tryout and no drawbead and no tool geometry was allowed to be changed in this project.FIGURE 6. The verification of geometric deviation of first full operation part Fig. 6 shows the measurement report of the first full operations part, where, 80 percent of geometrical deviation between sprung part and design shape is well-controlled inside ±0.5mm(green label), 95 percent of geometrical deviation in match surface is inside the tolerance of ±0.5mm, which well-verified that the methodology of the robust springback compensation is effective.a)The comparison of tryout cost b) The comparison of rejection rate of partFIGURE 7. The comparison of the statistical result of tryout cost and rejection rate in production The cost of the tryout and rejection rate of part in production has been tracked as well. Fig. 7 a) shows the comparison of tryout cost of decklid inner between previous car model New Lavida and current project. With the help of the new technology of robust springback compensation, the total amount of tryout sheets has been reduced by 65%, which hints that the similar percent of tryout cost and tryout time has been reduced. Fig. 7 b) shows the comparison of the formability and dimension related rejection rate of decklid inner in production, where, the rejection rate of previous car model is about 0.3%, as for current project, there was nearly no rejected part recorded in production since the car model Skoda Rapid release in April, 2013, which well-verified that the technology of robust design and springback compensation can help to reduce the tryout cost and the rejection rate significantly.CONCLUSIONSpringback compensation is a challenging and cost-prohibitive process in current die industry. With the help of the new technologies of robust design and springback compensation, this process can be easy and effective. Moreover, with the help of these new technologies, both tryout cost and the rejection rate of part in production can be significantly reduced, and the tool development period can be shortened as well, therefore, the win-win target of both “Q uality” and “C ost” can be realized via the new technologies of robust design and springback compensation.ACKNOWLEDGMENTSFinally, the authors would like to thank all engineers and workers of TMM, Shanghai Volkswagen and AutoForm Engineering who were involved in this project.REFERENCES1. Dorel Banabic, Sheet Metal Forming Processes, Constitutive Modelling and Numerical Simulation. Springer HeidelbergDordrecht London New York, 2010, pp. 267-294.2. The advance springback seminar, AutoForm Engineering GmbH, October, 2009.3. Bart Carleer, Peter Grimm, Robust springback compensation, Numisheet2014.4. Schoenbach T, Bauer T (2008) New method to calculate and compensate springback. In: Hora P (ed) (2008) Proceedings ofthe 7th International Conference and Workshop on Numerical Simulation of 3D Sheet Metal Forming Processes-Verification of Simulation with Experiment, Numisheet2008, Interlaken, Switzerland, pp. 515-520.。

合集下载

Spring和MyBatis的外文翻译..

Spring和MyBatis的外文翻译..

本科生毕业设计 (论文)外文翻译原文标题MVC Design Pattern for the multi frameworkdistributed applications using XML, spring and strutsframework译文标题使用XML,Spring和struts以MVC为设计模式的多分布式应用程序框架作者所在系别计算机与遥感信息技术学院作者所在班级B12511作者姓名王硕作者学号20124051117指导教师姓名耿炎指导教师职称院长完成时间2015 年1 月北华航天工业学院教务处制译文标题使用XML,Spring和struts以MVC为设计模式的多分布式应用程序框架原文标题MVC Design Pattern for the multi frameworkdistributed applications using XML, spring and struts framework作者Praveen Gupta 译名普利文·古塔国籍印度原文出处International Journal on Computer Science and Engineering 使用XML,Spring和struts以MVC为设计模式的多分布式应用程序框架摘要：模型-视图-控制器(MVC)是一个基本的设计模式，用来分离用户界面与业务的逻辑。

近些年来，应用程序的规模越来越大，而MVC设计模式可以弱耦合不同应用层的程序。

本文提出了一种基于J2EE平台上的网络,它扩展了MVC、XML 的应用程序框架，易于维护。

这是一个包括表示层、业务层、数据持久层和数据库层的多系统层，由于其代码的具有独立性，可维护性和可重用性大大提升。

在本文中,我们使用MVC实现spring和struts框架。

我们的研究显示，应用多个框架设计应用程序时，使用MVC概念能使应用程序转变为更容易、较单一的框架。

关键字：MVC，Spring，XML一介绍近些年来，web是非常复杂的问题。

Robust Control

Robust Control

Robust ControlRobust control is a field of engineering and control theory that focuses on designing systems that can perform effectively and reliably in the presence of uncertainties and variations. This is particularly important in applications where the environment or operating conditions are unpredictable, such as in aerospace, automotive, and manufacturing systems. The goal of robust control is to ensurethat the system can maintain stability and performance despite these uncertainties, providing a level of resilience that is essential for real-world applications. The development of robust control can be traced back to the early days of control theory, which emerged in the early 20th century with the work of engineers and mathematicians such as Bode, Nyquist, and others. The early focus of controltheory was on developing methods to analyze and design systems that could maintain stability and performance under ideal conditions. However, as control systems began to be applied to real-world problems, it became clear that these methods were not sufficient to address the uncertainties and variations that are inherentin practical systems. In response to this challenge, researchers began to develop new techniques and approaches to address robustness. One of the key developmentsin this area was the concept of H-infinity control, which emerged in the 1980s and provided a framework for designing controllers that could provide guaranteed performance in the presence of uncertainties. This marked a significant shift in the field of control theory, as it provided a rigorous mathematical foundation for addressing robustness in control systems. From a historical perspective, the development of robust control can be seen as a response to the limitations of traditional control methods in addressing real-world uncertainties. This has ledto a rich and diverse set of techniques and approaches for designing robustcontrol systems, ranging from classical methods such as loop shaping and robustPID control to modern approaches based on optimization and convex analysis. These developments have been driven by the need to address practical challenges in awide range of applications, leading to a field that is constantly evolving and adapting to new problems and opportunities. One of the key debates in the fieldof robust control is the trade-off between performance and robustness. Traditional control methods often focus on optimizing performance under ideal conditions,which can lead to designs that are sensitive to uncertainties and variations. In contrast, robust control methods prioritize resilience and stability, often at the expense of performance. This has led to a lively debate within the control community about the best approach to designing control systems, with some researchers advocating for a balanced approach that considers both performance and robustness, while others argue for the primacy of robustness in critical applications. To illustrate the importance of robust control, consider the example of an autonomous vehicle. In this application, the vehicle must be able to navigate safely and effectively in a wide range of conditions, including varying road surfaces, weather conditions, and traffic patterns. A control system that is not robust to these uncertainties could lead to unsafe or unreliable performance, potentially putting lives at risk. By contrast, a robust control system canprovide the level of resilience and stability that is essential for the safe operation of autonomous vehicles, highlighting the critical importance of robust control in modern engineering applications. Despite the clear benefits of robust control, there are also challenges and limitations associated with this approach. One of the key challenges is the complexity of designing robust control systems, which often requires sophisticated mathematical tools and techniques. This can make it difficult for practitioners to apply robust control methods in practice, particularly in applications with limited resources or expertise in control theory. Additionally, there is a trade-off between robustness and performance, as mentioned earlier, which can make it challenging to design control systems that achieve both goals simultaneously. Looking to the future, the field of robust control is likely to continue to evolve and adapt to new challenges and opportunities. With the increasing complexity and interconnectedness of modern engineering systems, the need for robust control will only grow in importance.This will require ongoing research and development to advance the state of the art in robust control methods, as well as efforts to make these techniques more accessible and practical for engineers and practitioners. By addressing these challenges, the field of robust control has the potential to make a significant impact on the safety, reliability, and performance of a wide range of engineeringsystems, ensuring that they can operate effectively in the face of uncertainties and variations.。

Robust Control

Robust Control

Robust ControlRobust control is a field of control theory that deals with designing control systems that are able to maintain their performance despite changes in the system or external disturbances. The goal of robust control is to ensure that the system remains stable and performs as desired, even in the presence of uncertainties and disturbances. In this response, I will discuss the importance of robust control,its key components, and its applications in various fields. One of the main reasons why robust control is important is that real-world systems are often subject to uncertainties and disturbances. For example, in a manufacturing plant, the temperature, humidity, and other environmental factors can vary, leading to changes in the behavior of the system. Similarly, in a flight control system, changes in the wind speed or direction can affect the stability of the aircraft. Robust control techniques are designed to handle these uncertainties and ensurethat the system remains stable and performs as desired. Robust control systems typically consist of three main components: a model of the system, a controller, and a performance specification. The model of the system is a mathematical representation of the system's behavior, which is used to design the controller. The controller is responsible for adjusting the system's inputs in response to changes in the system or external disturbances. The performance specification specifies the desired performance of the system, such as the settling time, overshoot, or tracking error. One of the key challenges in designing robustcontrol systems is dealing with uncertainties in the system. There are two main types of uncertainties: parametric uncertainties and external disturbances. Parametric uncertainties refer to uncertainties in the parameters of the system model, such as the mass, damping, or stiffness of a mechanical system. External disturbances refer to external forces or inputs that affect the system, such as wind gusts or road bumps in a vehicle. To address these uncertainties, robust control techniques typically use a combination of feedback control and feedforward control. Feedback control adjusts the system's inputs based on the system's output, while feedforward control adjusts the system's inputs based on the expected disturbances. By combining these two types of control, robust control systems are able to maintain their performance despite uncertainties and disturbances. Robustcontrol has numerous applications in various fields, including aerospace, automotive, manufacturing, and robotics. In aerospace, robust control is used to design flight control systems that are able to maintain stability and performance in the presence of wind gusts, turbulence, and other disturbances. In automotive applications, robust control is used to design suspension systems that are able to maintain ride comfort and handling performance on rough roads. In manufacturing, robust control is used to design control systems for various processes, such as temperature control, pressure control, and flow control. These systems must be able to maintain their performance despite changes in the environment orvariations in the process parameters. In robotics, robust control is used to design control systems for robots that are able to maintain their performance despite changes in the environment or uncertainties in the robot's kinematics and dynamics. In conclusion, robust control is an important field of control theory that deals with designing control systems that are able to maintain their performance despite uncertainties and disturbances. Robust control systems typically consist of a model of the system, a controller, and a performance specification, and use a combination of feedback and feedforward control to address uncertainties. Robust control has numerous applications in various fields, including aerospace, automotive, manufacturing, and robotics. By designing robust control systems, engineers are able to ensure that systems perform as desired, even in the presence of uncertainties and disturbances.。

Robust Control

Robust Control

Robust ControlRobust control is a crucial concept in the field of engineering and automation. It involves designing control systems that are able to effectively handle uncertainties and variations in the system being controlled. This is particularly important in real-world applications where external disturbances, changes in operating conditions, and other uncertainties can affect the performance of the control system. One of the key challenges in robust control is ensuring that the system remains stable and performs well under a wide range of operating conditions. This requires the use of robust control techniques that can effectively handle uncertainties in the system dynamics and disturbances that may occur during operation. By designing a control system that is robust to these uncertainties, engineers can ensure that the system will continue to operate safely andeffectively in the face of changing conditions. Another important aspect ofrobust control is the ability to achieve good performance in terms of speed, accuracy, and stability. This requires the use of advanced control algorithms and techniques that can optimize the performance of the system while also ensuring robustness to uncertainties. By carefully tuning the control system and incorporating robust control techniques, engineers can achieve the desired performance while also ensuring the system's stability and reliability. Inaddition to performance and stability, robust control also plays a crucial role in ensuring the safety of the system and its surroundings. In applications such as autonomous vehicles, industrial robots, and aerospace systems, the consequences of a control system failure can be catastrophic. By designing control systems thatare robust to uncertainties and disturbances, engineers can minimize the risk of accidents and ensure the safety of the system and its operators. From a practical perspective, robust control techniques are essential for ensuring the successful operation of complex systems in real-world applications. By incorporating robust control principles into the design and implementation of control systems,engineers can improve the performance, reliability, and safety of the system while also reducing the risk of costly failures and downtime. This is particularly important in industries such as automotive, aerospace, and manufacturing, wherethe consequences of control system failures can be severe. In conclusion, robustcontrol is a critical concept in the field of engineering and automation, with wide-ranging implications for performance, stability, and safety. By designing control systems that are robust to uncertainties and disturbances, engineers can ensure the successful operation of complex systems in real-world applications. Through the use of advanced control algorithms and techniques, engineers can optimize the performance of the system while also ensuring its stability and reliability. Overall, robust control plays a crucial role in ensuring the effectiveness and safety of control systems in a variety of industries and applications.。