汽车生产企业如何构建DFMEA平台

随着全球化进程的推进,制定一个国际通用的汽车行业质量管理体系认证标准已经成为广大汽车生产厂家的共同呼声,在此背景下,ISO/TS16949在1999年应运而生。经过适应性更改,2003年ISO/TS16949:2002正式发布并沿用至今。五大工具是ISO/TS16949:2002推荐的产品策划、过程控制、实现预防为主及其测量系统评定的重要手段,是集世界汽车制造企业专家管理经验之大成而总结的产品质量管理方法,其在企业生产经营的过程中表现出来的质量控制的有效性已经经过实践再三检验。五大工具之一——设计潜在失效模式及后果分析(DFMEA)是ISO/TS16949:2002推荐的实现预防为主的重要手段。应用DFMEA可以识别、评价产品设计中潜在的失效及其后果,找到能够避免或减少这些潜在失效发生的措施。将这些分析过程文件化,这是对设计过程的完善。成功实施DFMEA的重要因素之一是及时性,它是一个"事前的行为",而不是"事后的处置",为达到最佳效益,DFMEA必须在产品设计失效模式被纳入到产品设计之前进行。ISO/TS16949:2002中有大小15个条款涉及DFMEA,其质量控制思想贯穿于TS16949标准全过程。如何快速应用DFMEA工具,在汽车产品设计过程中有效的进行质量控制,成为各大汽车生产厂家应该重点关注的问题。     

动态信号采集分析仪(CY-1型)系统及原理

介绍了动态信号采集分析仪（CY-1型）的原理。该系统适用于多种物理模型试验，如船舶性能、船舶在风浪流自然载荷条件下对港口设施的影响（码头受到的撞击力与缆绳受到的拉力等）、桥墩防撞设施以及水工结构物等。实践表明，该系统精度高且操作方便，所以在物理模型试验中是不可或缺的。最后指出了可进一步完善该系统的若干方法。     

浅谈数控编程软件图形数据的转换

本文在CAM数控编程软件使用的基础上,介绍了图形数据转换的制定目的、格式,并通过示例来说明典型软件的图形数据转换的基本方法。     

四阶段交通预测模型基础数据库设计

基础数据是交通模型的根本，一个好的基础数据库也是交通模型可靠性的有力保障。本文分析了建立四阶段交通规划模型的数据需求，并对其来源进行了分析，提出了最基本的交通模型数据库结构。     

基于DEA的物流产业发展能力评估模型

以数据包络分析的方法建立物流产业发展能力的评估模型,以此为物流产业发展的优化与调整、物流产业的投资规模和投资政策、产业发展政策方面提供科学的依据。     

基于ARM单片机的汽车模拟驾驶器设计

在汽车驾驶模拟器中,传感控制系统的性能直接影响到整个汽车驾驶模拟系统的交互性和实时性,是衡量汽车驾驶模拟器实用性能的重要指标,而数据采集和处理系统又是整个传感控制系统的核心。文章介绍了汽车模拟驾驶系统的工作原理和单片机系统的设计思路。结果表明,由于单片机的数据采集系统成本相对较低,接口的可扩展性好,模拟量和开关量的预处理工作也可以由单片机来完成,因此系统完全可以满足汽车驾驶模拟器的交互性和实时性要求,在实际应用中取得了较好的效果。     

一种基于GPS和IC卡数据的城市公交出行分布推算方法

城市公交规划、管理工作迫切需要信息化技术给予定量的决策数据支持.公交出行分布数据通常基于居民出行调查获得,然而因其调查代价巨大不能作为常态化调查手段.短期的公交线网调整工作更依赖于现状的公交出行分布需求,本文由此提出了一种利用公交GPS和IC卡(含老年卡)数据推算现状公交出行分布的实用方法.当前在大城市常住人口使用IC卡作为公交支付手段已得到相当普及,采用基于车载GPS和乘客IC卡记录能够推断得到全日公交OD数据并用于公交出行量回归模型的标定.模型检验通过后,可结合人口数据和就业岗位资料用标定模型计算以投币作为主要付费方式的流动人口公交OD;叠加两部分OD得到完整的城市公交出行分布结果.该模型的有效性通过2010年郑州市综合交通调查实践得以验证,对其它城市具有借鉴意义.     

Decision Support Systems for Public Transport Management: The Athens Public Transport Authority Project

This article reports on an implementation study of a computerised decision support system for public transport management for the Athens Public Transport Authority (APTA). The study analysed the current situation, specified user requirements, determined system functionality, designed the system architecture, organised the project and, finally, planned dissemination activities. The decision support system covers the main public transport management activities of APTA - transport service provision, economic and financial planning, passenger complaints and suggestions, and personnel management - offering its users the possibility to study the potential effects of their decisions before implementation. To achieve this, the system will consist of a data warehousing system, for the integrated management of a wide variety of data sources, and of online analytical processing tools, for information analysis and scenario testing. The system architecture has been designed to offer robustness, flexibility, rich functionality and open connectivity. The system aims to help APTA reduce operational costs and provide a better transport service, attracting more passengers to public transport and reducing, in the process, congestion and pollution.     

Speed variation during peak and off-peak hours on urban arterials in Shanghai

Increased speed variation on urban arterials is associated with reductions in both operational performance and safety. Traffic flow, mean speed, traffic control parameters and geometric design features are known to affect speed variation. An exploratory study of the relationships among these variables could provide a foundation for improving the operational and safety performance of urban arterials, however, such a study has been hampered by problems in measuring speeds. The measurement of speed has traditionally been accomplished using spot speed collection methods such as radar, laser and loop detectors. These methods can cover only limited locations, and consequently are not able to capture speed distributions along an entire network, or even throughout any single road segment. In Shanghai, it is possible to acquire the speed distribution of any roadway segment, over any period of interest, by capturing data from Shanghai’s 50,000+ taxis equipped with Global Positional Systems (GPS). These data, hereafter called Floating Car Data, were used to calculate mean speed and speed variation on 234 road segments from eight urban arterials in downtown Shanghai. Hierarchical models with random variables were developed to account for spatial correlations among segments within each arterial and heterogeneities among arterials. Considering that traffic demand changes throughout the day, AM peak, Noon off-peak, and PM peak hours were studied separately. Results showed that increases in number of lanes and number of access points, the presence of bus stops and increases in mean speed were all associated with increased speed variation, and that increases in traffic volume and traffic signal green times were associated with reduced speed variation. These findings can be used by engineers to minimize speed differences during the road network planning stage and continuing through the traffic management phase.     

A mathematical programming technique for matching time-stamped records in logistics and transportation systems

Time-stamped data for transportation and logistics are essential for estimating times on transportation legs and times between successive stages in logistic processes. Often these data are subject to recording errors and omissions. Matches must then be inferred from the time stamps alone because identifying keys are unavailable, suppressed to preserve confidentiality, or ambiguous because of missing observations. We present an integer programming (IP) model developed for matching successive events in such situations and illustrate its application in three problem settings involving (a) airline operations at an airport, (b) taxi service between an airport and a train station, and (c) taxi services from an airport. With data from the third setting (where a matching key was available), we illustrate the robustness of estimates for median and mean times between events under different random rates for “failure to record”, different screening criteria for outliers, and different target times used in the IP objective. The IP model proves to be a tractable and informative tool for data matching and data cleaning, with a wide range of potential applications.