Designing data warehouses for equipment management system with genetic algorithms

Effective equipment management is becoming one of the key factors in keeping a competitive advantage in the dynamic business environment since equipment is an important asset for manufacturing companies. Nowadays, maintenance administration has become one of the most important tasks in equipment management, particularly in manufacturing industries. Equipment management system (EMS) aims at reducing maintenance cost and production loss caused by machine breakdown. In addition, EMS can assist equipment engineers to make the right maintenance decisions at the right time, and at the right shop floor. Traditional computerized maintenance management systems (CMMS) have helped equipment engineers to deal with maintenance operations, but they lack decision support capability. In this paper, we design a data warehouse (DW) for EMS to help equipment engineers make maintenance decisions with various equipment related dimensions to improve effectiveness. A set of cubes can be built from EMS DW for the purpose of decision-making. In order to achieve a reasonable query response time under the memory space limit, a mechanism of partial materialization based on genetic algorithms (GAs) is adopted to design data cubes in the EMS DW. From the computational results the proposed GA-based approach for cube design can be applied to effectively select the appropriate multi-dimensional views for equipment management.     

Evaluating order picking performance trade-offs by configuring main operating strategies in a retail distributor: A Design of Experiments approach

Warehouse design has become important due to its impact on service to customers and total logistics costs. Order picking is the key activity of a warehouse and an appropriate design will directly affect its overall performance. The increasing complexity of warehouses means that the main operating strategies such as storage location assignment, batching and routing need to be considered simultaneously. A Design of Experiment approach aided by Discrete Event Simulation could help to meet these new picking design process requirements, especially when various performance measures need to be compared. Some of the trade-offs that managers must keep in mind when designing order picking systems are shown, describing a single-case study carried out at a retail distributor.     

Robotics in order picking: evaluating warehouse layouts for pick,place, and transport vehicle routing systems

Motivated by recent technological advances in mobile robotics, this paper explores a novel approach for warehouse order picking. In particular, this work considers two types of commercially available mobile robots – one that can grasp items from a shelf (a picker) and another (a transporter) that can quickly deliver all items from the pick list to the packing station. A new vehicle routing problem is defined which seeks to minimise the time to deliver all items from a pick list to the packing station, a problem termed the pick, place, and transport vehicle routing problem. A mixed integer linear programming formulation is developed to answer three related research questions. First, what combination of picker and transport robots is required to obtain performance exceeding traditional human-based picking operations? Second, how should the composition of the robot fleet be altered to affect the greatest performance improvements? Finally, what are the impacts of warehouse layout designs when coordinated mobile robots are deployed? An extensive numerical analysis reveals that, (1) increasing the number of cross aisles decreases system performance; (2) centrally located packing stations improve system performance; and (3) the average distance from each pick location to the packing station and the average distance between pick locations are effective metrics for identifying specific fleet modifications that are likely to yield system improvements.     

数据仓库及数据挖掘技术在证券客户关系管理系统中的应用研究

论文提出了中小型券商如何在客户关系管理系统中实现数据仓库和数据挖掘的应用方法,首先根据FS—LDM模型建立企业数据模型并进行主题域的划分,完成多层次的数据仓库架构设计及星型结构的客户纬度建模;然后使用聚类技术和逻辑回归技术实现客户分类的动态细分模型和客户流失概率预测模型。     

ETL在超市大数据量中的应用研究

数据抽取、转换和装载（Extract,Transform and loading,简称ETL）是数据仓库、数据挖掘以及商业智能等技术的基石.文中首先简单介绍了ETL概念及其意义,然后设计和开发了应用于超市行业商业智能的ETL程序,已在超市行业管理信息与决策支持系统中得到应用.     

Seismic analysis of an asymmetric fixed base and base-isolated high-rack steel structure

Since, in the case of plan-eccentric, externally-braced, high-rack storage structures made of steel, damage to the central part of the structure can cause damage to the stored goods, and thus higher earthquake-induced costs, an investigation has been performed into the seismic performance of such structures. An actual structure was analysed both as a fixed base variant, and as a base-isolated variant. The extended N2 method (pushover analysis) was used, and the results obtained were compared with selected results obtained by nonlinear-dynamic analysis. The response of several different mass-asymmetric structural variants, corresponding to different occupancy levels of the structure, was analysed, and the results obtained are presented as floor plan projection envelopes of the top, relative and base displacements, as well as the storey drifts. An interesting result obtained in the research was that asymmetry can increase the damage in the supporting structure on the flexible side, and that the central part of the rack structure remains in the elastic region only when the eccentricity is small. In fact, from the seismic point of view, full occupancy is not the most critical condition, but rather lower occupancy, which could cause eccentricities ranging up to 10% or 15% of the larger floor plan dimension; this could lead to damage propagation in some of the columns. The application of base isolation has a positive effect on the management of seismic performance, even in the case of higher levels of occupancy and larger mass eccentricities. It is pointed out that an eccentricity of 5%, which is prescribed in Eurocode 8, might not be sufficient in such structural types, and that similar concerns could be present in other types of industrial structures with a similar ratio between live and dead loads.     

大跨度复杂屋盖结构风荷载的大涡模拟

应用一种新的湍流脉动流场产生方法DSRFG(Discretizing and Synthesizing Random Flow Generation)[1]模拟风场实际的湍流边界条件,采用一种新的大涡模拟(Large Eddy Simulation,LES)的亚格子模型[2],基于Linux系统下软件平台Fluent6.3的并行计算技术,对深圳新火车站进行了数值风洞模拟。并将屋盖的平均风压、脉动风压计算结果与风洞试验数据进行了比较,表明数值模拟很好地反映了大跨度屋盖表面风压的分布情况,由其得到的风压系数与风洞试验数据有较好的吻合。表明本文的DSRFG方法以及新的大涡模拟亚格子模型的数值模拟技术是一种很好的预测大型、复杂结构表面风荷载的有效方法。并为进一步发展在复杂湍流环境下大跨度屋盖结构的风荷载数值风洞技术提供参考。     

大跨径隧道双上侧壁导坑法施工技术

大跨径隧道双上侧壁导坑法是根据隧道软硬围岩相间的情况,将双侧壁导坑法与上下台阶法相结合的一种技术.以开挖断面的起拱线为界,将隧道横断面分为上下两部分,上部采取双侧壁导坑法施工,下部分左右幅先后开挖,适用于上部围岩较差、下部围岩较好的单向三车道及三车道以上隧道.详细介绍了洞身超前支护、洞身开挖、洞身初期支护与临时支护的施工方法与注意事项.工程应用结果表明,与传统的双侧壁导坑法相比,该方法安全可靠、灵活多变、经济社会效益明显.     

布谷鸟算法求解组装车间仓储调度优化问

为提高产品组装效率,对影响产品组装效率的因素进行了分析,将仓储作业与组装作业作为组装任务,以其完工时间总和最小为目标,建立了组装车间仓储调度模型,并提出一种改进的布谷鸟算法对其进行求解。该算法通过自适应调整发现概率,避免了在搜索过程中陷入局部最优,通过动态调整步长,提高了收敛速度。为验证该算法的性能,结合工业现场实例与原始布谷鸟算法及遗传算法进行了仿真对比,结果表明本文提出的算法在收敛精度及收敛速度上都取得了较好的效果。     

基于云存储技术的经营分析系统建设

本文基于数据仓库和云存储技术,从江苏有线的经营分析系统实际出发,分别介绍了整个经分系统的软件架构,包括基本内容、技术方案以及特色,云存储在经营分析系统中的应用架构及特色。