新产品开发中的物资采购决策

在新产品开发中，物资采购的作用不可低估，特别是在采用新材料方面。物资采购人员只有早期介入，充分发挥在新产品开发全过程中的作用，不断更新采购方式，加强采购过程控制，增强决策的战略意识，企业才能及时向用户提供设计趋于完美、价格适宜、具有竞争力的产品。     

发动机冲气缸垫故障的预防

汽车发动机气缸垫被冲坏,是驾驶员较为苦恼的经常性故障之一.气缸垫冲坏后,不仅维修装配麻烦,严重时汽车无法行驶,造成途中"抛锚",影响运输任务的完成.因此,掌握缸垫被冲坏现象的判断,对预防故障的发生和及时排除故障都十分必要.     

Constrained Run-to-Run Optimization for Batch Process Based on Support Vector Regression Model

Introduction Batch and semi-batch processes are very im-portant in the fine chemicals industry to manufac-ture the low-volume and high-value products suchas biochemicals, crystals and speciality chemicals.In the control of batch process, the major objectiveis to improve the end-of-batch product properties.When the control objective is to optimize a perfor-mance index at the end of batch cycle, the problemis called the end-point optimization problem. Tosolve the problem,the traditional approach…     

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广深线城际列车乘务组排班计划编制方法探讨

针对广深线城际列车开行及动车组运用情况,在确定了乘务组数量的基础上,按照乘务组排班计划的编制原则,对乘务组排班计划问题进行了描述,并设计了相应的SE算法．通过该方法得到的乘务排班计划,目前正应用于广深线城际列车的实际乘务组织中。     

半刚性与半柔性基层材料性能及适用性对比

针对目前半刚性基层沥青路面使用早期就发生破坏,导致路面使用寿命缩短的现象,通过半刚性材料和半柔性材料优缺点及结构适用性的对比分析,提出采用复合式基层和半柔性基层作为结构层的路面结构能很好地解决中国沥青路面早期损坏问题。     

Nonlinear Statistical Process Monitoring Based on Control Charts with Memory Effect and Kernel Independent Component Analysis

A novel nonlinear combination process monitoring method was proposed based on techniques with memory effect (multivariate exponentially weighted moving average (MEWMA)) and kernel independent component analysis (KICA). The method was developed for dealing with nonlinear issues and detecting small or moderate drifts in one or more process variables with autocorrelation. MEWMA charts use additional information from the past history of the process for keeping the memory effect of the process behavior trend. KICA is a recently developed statistical technique for revealing hidden, nonlinear statistically independent factors that underlie sets of measurements and it is a two-phase algorithm: whitened kernel principal component analysis (KPCA) plus independent component analysis (ICA). The application to the fluid catalytic cracking unit (FCCU) simulated process indicates that the proposed combined method based on MEWMA and KICA can effectively capture the nonlinear relationship and detect small drifts in process variables. Its performance significantly outperforms monitoring method based on ICA, MEWMA-ICA and KICA, especially for long-term performance deterioration.