Travel time models for deep-lane unit-load autonomous vehicle storage and retrieval system (AVS/RS)

Autonomous vehicle storage and retrieval systems use vehicles that move horizontally along rails within the storage racks, while vertical movements are provided by lifts. The solution proposed in this paper addresses a particular system configuration that works with multiple deep storage lanes that are widely used in the food and beverage industry, characterised by large volumes of products of limited variety. The generic deep lane is single item, i.e. one stock keeping unit, and single batch, i.e. one production lot, thereby affecting the performance of the system in terms of storage capacity utilisation and throughput. Determining the number and depth of the lanes is crucial to aid the design and control of such a storage system. The aim of this paper was to support the design of AVS/RSs though a set of original analytic models for the determination of the travelled distance and time for single-command and dual-command cycles given alternative layout configurations. The models are validated by simulation and exemplified with a real-warehousing case study. The paper presents useful guidelines for the configuration of the system layout including the determination of the optimal shape ratio and the length of the lanes.     

A performance analytical model of automated material handling system for semiconductor wafer fabrication system

To effectively analyse and evaluate the performances of closed-loop automated material handling system (AMHS) with shortcut and blocking in semiconductor wafer fabrication system, a modified Markov chain model (MMCM) has been proposed. The system characteristics, such as vehicle blockage and system’s shortcut configuration, are well considered in the MMCM. The state space explosion problem and computational challenge due to the increase of AMHS scale can be effectively eliminated. With production data from Interbay material handling system of a 300-mm semiconductor wafer fabrication line, the proposed MMCM is compared with simulation analysis model. The results demonstrate that the proposed MMCM is an effective modelling methodology for AMHS’s performance analysis at system design stage.     

Automated sampling decision scheme for the AVM system

Reducing the sampling rate to as low as possible is a high priority for many factories to reduce production cost. Automatic virtual metrology based intelligent sampling decision (ISD) scheme had been previously developed for reducing the sampling rate and sustaining the virtual metrology (VM) accuracy. However, the desired sampling rate of the ISD scheme is fixed and set manually. Hence, whenever the VM accuracy gets worse, it cannot adaptively increase the default sampling rate in the ISD scheme. As a consequence, it would take more time to collect enough samples for improving the VM accuracy. Moreover, when the VM accuracy performs well all the time, it cannot automatically decrease the default sampling rate in ISD, which may result in unnecessary waste. Accordingly, this paper proposes an automated sampling decision (ASD) scheme to adaptively and automatically modify the sampling rate online and in real time for continuous improvement. The ASD scheme can monitor the VM accuracy online as well as update the VM models in real time for maintaining the VM accuracy when the VM accuracy becomes poor. Also, the ASD scheme can automatically reduce the sampling rate while the VM accuracy performs well.     

Error estimation for the automated multi‐level substructuring method

In this study, we propose an effective method to estimate the reliability of finite element models reduced by the automated multi‐level substructuring (AMLS) method. The proposed error estimation method can accurately predict relative eigenvalue errors in reduced finite element models. A new, enhanced transformation matrix for the AMLS method is derived from the original transformation matrix by properly considering the contribution of residual substructural modes. The enhanced transformation matrix is an important prerequisite to develop the error estimation method. Adopting the basic concept of the error estimation method recently developed for the Craig–Bampton method, an error estimation method is developed for the AMLS method. Through various numerical examples, we demonstrate the accuracy of the proposed error estimation method and explore its computational efficiency. Copyright © 2015 John Wiley & Sons, Ltd.     

数据库技术的研究现状及发展趋势

介绍了数据库系统设计过程的六个阶段,即需求分析阶段、概念结构设计阶段、逻辑结构设计阶段、物理结构设计阶段、实施阶段、运行与维护阶段;以分布式数据库系统、知识库系统和主动数据库系统为例,阐述了当前数据库系统研究的现状;结合数据仓库、工程数据库、统计数据库、空间数据库等多种数据库,指出了当前数据库技术的研究热点和发展趋势。     

机器人自动对接系统中的定位技术

介绍了普通环境下机器人自动对接系统中应用几种不同定位方式。简单分析了几种技术的原理和特点,并引用了将此技术用于普通对接和自重构机器人对接的相应成功实验加以说明。     

一种双向元数据管理系统

作为企业级数据仓库的路径图,元数据在企业级数据仓库的建设中起着重要的作用。设计一个描述能力强、内容完善的元数据,是有效实现企业级数据仓库功能的重要环节。该文通过对双向体系元数据管理系统的研究,给出了一个企业级数据仓库的元数据管理的解决方案。该方案能够支持从企业级数据仓库子系统抽取元数据存储到元数据管理系统,同时也支持向数据仓库子系统提供其所需的元数据信息,解决诸多企业级数据仓库的运行管理问题,大大减少了企业级数据仓库的管理难度、保证了元数据的准确性、使得各子系统能高效地通信和稳定运行。     

基于SOA和工作流的数据仓库更新系统

针对数据仓库系统中的异构数据源集成问题和数据仓库更新流程的控制问题,提出一个基于SOA和工作流的数据仓库更新系统,把异构环境下的各个系统作为服务提供者或服务消费者,抽象出标准的功能服务接口,实现了异构平台的系统集成。同时把数据仓库更新过程定义为活动的集合,从逻辑上看作为一个工作流过程,可以根据不同的业务需求进行动态组织,高效地满足用户的需求,提高了更新流程的自动化程度和效率。     

操作型商业智能综述

为了为日常工作提供商业智能支持,研究了商业智能自身在发展过程中概念的转变,以及近年商业智能针对企业不同应用层次产生的新分类.研究了操作型商业智能的定义与定位,根据商业智能的通用架构和操作型商业智能的特点提出了通用的操作型商业智能系统的架构.对操作型商业智能组成模块的技术现状进行研究,分别研究了操作型商业智能与企业业务流程融合以及数据加载问题,重点对加快数据加载速度的技术进行了总结与归纳,结果表明了架构在技术上的可行性.