Grinding and fine finishing of future automotive powertrain components

The automotive industry is undergoing a major transformation driven by regulations and a fast-paced electrification. A critical analysis of technological trends and associated requirements for major automotive powertrain components is carried out in close collaboration with industry – covering the perspectives of OEMs, suppliers, and machine builders. The main focus is to review the state of the art with regard to grinding, dressing, texturing and fine-finishing technologies. A survey of research papers and patents is accompanied by case studies that provide further insights into the production value chain. Finally, key industrial and research challenges are summarized.     

Method for optimizing the cooling design of hot stamping tools

During the past years hot-stamped components have gained considerable importance in the automotive industry. This is due to the advantageous properties involved, such as good crash behavior and high strength. In the production of hot-stamped components the blank is rapidly cooled by the tool. This exerts an important influence on the final properties and the process time. The tool is actively cooled by cooling ducts through which a medium flows. This article will present a newly developed method in which the design of the cooling ducts can be systematically optimized. A test tool is used to show the results of this method. It is easy to realize an optimized tool for the hot stamping process. Research is funded by the German Research Foundation (DFG) within the framework of research project FOR 522 “Basic research of the hot stamping process of ultra high-strength steels”     

基于知识共享的新产品前期质量管理方法

新产品形成阶段的决策对最终产品的质量有显著的影响。介绍了大众汽车公司采用的新零件批量生产前期质量管理方法,通过和供应商建立起较高层次的知识共享和传播机制,对新产品产生质量缺陷的可能性及风险大小进行分析评价,一起合作将缺陷产生的可能性消灭在批量投产之前。对我国汽车生产企业在新项目开发过程中如何进行质量管理有一定的借鉴作用,同时也为供应链质量管理提供了一个新思路。     

Adaptive Control of Supply Chains: Building blocks and tools of an agent-based simulation framework

An adaptive control concept for supply chains is presented. Its background is a complex supply chain scenario originating from the machine building domain with a focus primarily on the development of an agentbased method concerning the adaptive coordination of customer orders along the supply chain. It aims at flexibly handling disturbances in relation to the re-allocation of alternative suppliers to ensure a timely and accurate fulfilment of customer orders. The researched and described building blocks and tools originate from artificial intelligence, decision theory and operations management, which have been implemented in an agentbased simulation framework.     

Coordination policy for production and delivery scheduling in the closed loop supply chain

Coordinating a supply chain necessitates a synchronization strategy for reordering products and a cost-effective production and replenishment cycle time. The aim of this paper is to present an optimization framework for producing and distribution in the supply chains with a cooperating strategy. The main contribution of this paper is to integrate closed loop supply chain with open-shop manufacturing and economic lot and delivery scheduling problem (ELDSP). This integration is applied with the aim of better coordination between the members of the supply chain. This study examines the ELDSP for a multi-stage closed loop supply chain, where each product is returned to a manufacturing center at a constant rate of demand. The supply chain is also characterized by a sub-open-shop system for remanufacturing returned items. Common cycle time and multiplier policies is adopted to accomplish the desired synchronization. For this purpose, we developed a mathematical model in which a manufacturer with an open-shop system purchases raw materials from suppliers, converts them into final products, and sends them to package companies. Given that the ELDSPR is an NP-hard problem, a simulated annealing (SA) algorithm and a biography-based optimization (BBO) algorithm is developed. Two operational scenarios are formulated for the simulated annealing algorithm, after which both the algorithms are used to solve problems of different scales. The numerical results show that the biography-based optimization algorithm excellently performs in finding the best solution to the ELDSPR.     

供应链环境下企业质量管理的案例研究

文章分析了供应链环境下Dell公司实施供应商联合质量管理的案例。首先介绍了联合质量管理的由来，然后运用委托-代理理论分析了联合质量管理是如何产生激励效果和其实施的关键，接着分析了Dell公司如何去辅助供应商将联合质量管理复制到次级供应商，最后，在吸取联合质量管理成功经验的基础上，文章针对国内企业应对供应链时代质量管理的挑战提出了一些建议。     

基于多供应商的供应链契约效率研究

与多数研究供应链契约机制设计的文献不同，文章重点探讨供应链契约存在的必要性及其效率问题。研究结论认为，在不签约条件下，供应商之间的利益难以协调，说明了供应链契约存在的必要性；而在签约条件下，供应商竞争可以提高效率，但受到参与约束条件的限制，供应商之间有时并不存在竞争，也就无法改善效率。     

"畸变工程":从系统的角度探讨零件的畸变现象

在产品的最终加工过程中用精磨去除零件中的畸变是一个既费钱又费时的事情。例如，仅在(车辆)传动技术领域，1995年德国用于最后精磨以消除工件的畸变而增加的成本已达8．5亿欧元。迄今为止，行业人士认为在最后的产品加工过程中导致零件产生畸变的主要原因在于淬火过程，而今大家普遍认为这个观点不是很对，认为淬火过程只是释放了在各个加工环节中积累在工件中的畸变潜能，如铸造、车削加工、铣削、淬火、磨削。由不来梅大学创立及Deutsche Forschungsgemeinschaft资助的合作研究中心SFB570“畸变工程”的研究方针是从系统导向着手，分析零件的畸变。合作研究中心由12个子项目组成，涉及20多位来自材料科学、制造技术、数学及过程控制工程的研究人员。根据系统导向的方法，合作研究中心SFB570“畸变工程”认为，与优化零件整个生产过程(工序链)相比，对零件生产过程中的单个过程的优化是第二位的。为了推广系统导向的方法，保证SFB570“畸变工程”中集中在不同工序和技术的这12个子项目问的一个连续、协调的知识和信息交换，已成立了一个系统模式工作组。这个工作组的焦点在于详细阐述和进一步发展系统导向的方法以及协调应用于这些子项目中的工序和方法。和其它方法相比较，整体方法包括了零件的生命周期分析、因果分析、失效模式和效果分析(FMEA)以及试验设计(DOE)。除畸变潜能这个新概念外，同时还发展了生产过程补偿潜能这一概念。文中讨论并描述了整体步骤(包括相关方法和手段)，以及迄今为止取得的结果。     

Metal-matrix composites in the automotive industry: Opportunities and challenges

Metal-matrix composites offer considerable promise to help automotive engineers meet the challenges of current and future demands for recyclable, fuel-efficient, safe, and low-emission vehicles. These materials can be engineered to match the design requirements of automotive power-train or chassis components. Technological and infrastructural barriers tend to limit the implementation of these materials, but it is believed these barriers can be overcome and that metal-matrix composites can be applied in high-volume vehicle production. Reducing these barriers will require much effort by engineers and scientists, managers and planners at automotive manufacturers, and their suppliers. The result will be the gradual introduction of metal-matrix composites in high-volume vehicle production to satisfy customer desires while meeting regulatory requirements and competitive pressures.     

Dynamic transmission error measurements of a drive train

Due to generally reducing the noise level of machines and automotive applications gear noise optimization becomes more important. To optimize the excitation of the gearing in the development process, tooth contact analysis software is used. The transmission error is most common to characterize the noise excitation of gear sets. Usually in automotive applications gear noise is influenced by the entire drive train system with all its components. Therefore, it is necessary to asses if the transmission error of the gear set correlates to the noise of the drive train. Aim of a project funded by the German Research Foundation (DFG) was to investigate the possibility to measure the transmission error for every step of assembly. The transmission error was measured for a gear set, the transmission and the drive train. The research object was the drive train of a light truck. This report presents the results of the completed project.     

面向产品全生命周期的协同制造模型构建

制造业的发展需要不断创新理念。在分析我国制造业的发展需求后,探索企业在协同制造的发展方向,借助互联网+协同制造的概念,构建面向全生命周期的协同制造方案,建立起由市场信息层、设计数据层、智能制造层、售后服务层、供应链共享层等5个层组成的协同制造平台。在此基础上,分析包含商务、设计、生产、服务、供应链等5个企业工作过程的运行操作模式,获得协同制造的模型。并以装备制造业为例,分析协同制造的操作策略,为相关企业提供操作参考。     

浅谈平／槽轮铸件的试制

结合平／槽轮铸件的试制过程,阐述了运用现代供应链管理理论来指导生产服务型企业采购实践的重要性和必要性。供应商是企业供应链上十分重要的一环,他具有采购者不能具备的资源和优势,只有加强采购者与供应商之间的合作,实现优势互补,才能共享合作成果,实现共赢。     

等温淬火球铁(ADI)在汽车底盘零件上的应用

介绍了ADI的性能特点、汽车底盘铸件对材料性能的要求、ADI在美国汽车上的应用情况以及在我国一汽集团和东风汽车集团公司的试用情况,指出了国内中、重型汽车底盘零件应用ADI所存在的问题是:(1)产品设计人员和主管领导对ADI不了解;(2)ADI产业链尚未完全形成。对汽车ADI底盘零件生产的两种不同工艺流程进行了对比,并提出了以自身机加工厂为主体组建ADI产业链的建议。     

Proactive supply chain management in the forging industry

Forging companies are nearly exclusively embedded into supply chains as suppliers and consequently have to accomplish strict requirements concerning their logistic performance. For providing products flexible and responsive to the market proactive supply chain management systems need to be introduced for a quick and reliable delivery to costumers in-time with low risks of failures. Therefore, this paper describes a comprehensive approach for the implementation of operative logistic risk management in the PPC within flexible supply chains. The method developed applies proven statistical fundamentals (e.g. trend analysis) to logistic risk management with the purpose of identifying potential logistic risks, estimating their impact and ranking them according to their importance. Hence, counter measures can be deduced and tested based on material flow simulation to counter balance the identified potential logistic risks.     

A computer aided chaining approach for predicting the shape accuracy in manufacture of automotive structures

The increasing competition and the urge to reduce costs and shorten product-life-cycles in the automotive industries imply the application of virtual manufacturing mock-ups. Computer aided engineering methods including simulations of the structural behavior during manufacturing and assembly contribute to eliminate trial-and-error along the production chains of vehicle structures. Such digital mock-ups also provide an input for additional tolerance analyses and allow the identification of the pending quality of structure components in advance. In this way large numbers of experiments and adjustments on the existent production lines can be avoided. In this paper an approach is introduced, which allows the replication of the physical effects along manufacturing chains based on thermo-mechanical models. The rendered results after considering successive operational steps provide the basis for initial estimations regarding the shape accuracy of structure assemblies. For a specific example of the automotive body-in-white a first run of a manufacturing process chain is investigated in order to predict the shape quality of a probable production cycle by applying a tolerance chain analysis. The results enable the scrap identification due to non-satisfied quality of assemblies. Finally, based on the achieved results a re-engineering of the manufacturing chain is suggested in order to fulfill quality requirements.     

Formability Investigations of High-Strength Dual-Phase Steels

Car manufacturing is always regarded as the key industry behind sheet metal forming, and thus, the requirements of and developments in car manufacturing play a decisive role in the development of sheet metal forming. The automotive industry is faced with contradictory demands and requirements: better performance with lower consumption and less harmful emissions, more safety and comfort; these are extremely difficult to supply simultaneously with conventional materials and conventional manufacturing processes. The fulfillment of these often contradictory requirements is one of the main driving forces in the automotive industry and thus in the material and process developments in sheet metal forming, as well. In recent years, significant developments can be observed in the application of high-strength steels. In this respect, the application of various dual-phase steels is one of the best examples. However, the application of these highstrength steels often leads to formability and manufacturing problems. One formability problem is the springback occurring after sheet metal forming. In the current research, we have dealt mainly with advanced high-strength steels, primarily with dual-phase steels. When applying them, the springback phenomenon is one of the most critical issues. To reduce the tremendous amount of experimental work needed, we also applied numerical simulation using isotropic–kinematic hardening rules. The isotropic–kinematic hardening behavior of a given material in the applied Auto Form numerical package may be characterized with three independent material parameters c, v and K(a detailed explanation of their meaning will be given in the main part of this paper). However, we found that the material data included in simulation packages for these new high-strength steels are not fully adequate. For the determination of more reliable material parameters and to achieve better simulation results, a new testing device was developed. Numerical simulations were performed using the material parameters determined by the new device to show the sensitivity of springback behavior to these material parameters.     

SRIF Receives 2007 Global Excellent Supplier Award from TOSHIBA CORPORATION

The Shenyang Research Institute of Foundry （SRIF）, the largest foundry institute and a large science and technology enterprise in China, has recently been awarded the 2007 Global Excellent Supplier Award by TOSHIBA CORPORATION Power Systems Company. Out of all the suppliers that supply the products for electrical equipment, 12 were recognized at the event held in Japan, on May 23, 2008, of which nine are from Japan and three are from outside Japan. SRIF was the only company in the foundry field to receive the award. TOSHIBA CORPORATION selects the most competitive suppliers on the total and long term viewpoint.     

夹层钢板冲压的成形机理与缺陷分析

介绍了夹层钢板的材料结构、夹层钢板的冲压成形性及在成形过程中容易产生的缺陷,总结了影响夹层钢板成形性能的因素。介绍了夹层钢板在汽车行业中的应用情况及国内外的研究现状,并指出了当前车用夹层钢板研究的热点难点,对夹层钢板在此行业中应用发展做了展望。     

Text mining for AI enhanced failure detection and availability optimization in production systems

The success of data-driven maintenance is strongly dependant on effective use of AI and multi-structured data sources. Introducing and integrating an AI-enhanced methodology in reliability-centred maintenance study of complex production systems leads to reducing failure rates and optimizing availability. In manufacturing enterprises, information about machine failures and expert knowledge are often stored in digital shift books (DSB). This paper introduces a transferable and scalable AI-enhanced methodology for DSB in automotive industry, which enhances Overall Equipment Efficiency (OEE) by optimizing availability through reducing the Mean Failure Detection Time (MFDT). Experimental investigations in the use-case suggest an OEE increase by over 5%.