【作者】 王让；

【导师】 赵金楼；

【作者基本信息】 哈尔滨工程大学 ， 管理科学与工程， 2011， 博士

【摘要】 在海洋工程装备项目的进度管理中,KPI绩效指标考核方法具有重要的作用。由于影响海洋装备工程项目进度的不确定因素众多,关系错综复杂,工艺过程呈现非线性特征,使其在项目的进度计划和实际管理中存在着较大的进度偏差,这些进度偏差如不能及时发现和快速解决,将对海洋工程装备项目承担单位造成不可估量的经济损失和名誉损失。本文独立设计并提出了海洋工程装备项目KPI进度控制体系,并重点对海洋工程装备项目进度偏差成因及其成因的数据挖掘算法进行了研究,这将对海洋工程装备项目科学有效管理、进度偏差分析学的研究有重要意义。文中首先介绍了课题的立题背景,即海洋工程装备项目承担单位迫切需求从技术手段解决对进度偏差成因的捕捉和科学有效的监控,此项管理问题在国内尚无成熟的技术解决路线。在此基础上,对关键绩效指标理论、项目进度控制管理理论、数据挖掘理论的国内外发展现状进行了综述,发现运用智能数据挖掘算法,并结合进度偏差管理知识进行进度偏差成因分析的技术手段尚无人提出和研究。在对海洋工程装备项目进度控制的整体介绍基础上,本文对引起项目进度偏差的成因进行了分析,可通过因果分析图、排列图对进度偏差进行分析。进而对数据挖掘的基础理论、分类及其在项目管理中的具体应用进行了介绍,重点阐述了基于网格密度空间聚类优化方案的Apriori数据挖掘算法,为进度偏差成因分析奠定了技术解决方案,并最终设计完成了海洋工程装备项目进度偏差分析原型系统。(1)对KPI体系和海工装备项目进度管理的主要内容进行研究,提出了海洋工程装备项目KPI进度控制体系。对海洋工程装备项目进度计划、编制、实施、监控等管理体系进行分析和阐述。(2)介绍了海洋工程装备项目当前的进度控制现状及其存在的问题,提出了进度偏差亟待解决的客观问题。结合专业管理知识,对引起进度偏差的主要成因进行了分析,并阐述了进度偏差引起的后续不良响应,并明确了运用排列图分析方法进行成因分析的技术方案。(3)介绍了经典的数据挖掘算法及数据挖掘分类技术,在对海洋工程装备建造工艺进行充分介绍的基础上,阐述了数据挖掘技术在海洋装备工程项目进度控制阶段,特别是进度偏差监控过程中的作用和使用方法。提出了基于关联规则的Apriori数据挖掘算法,并对算法进行了改进和优化,给出了实证。(4)构建了KPI模式下海洋工程装备项目进度偏差分析决策支持系统。运用所提出的智能数据挖掘技术和排列图分析方法,对实际问题进行了验证,并最终设计了该系统。更多还原

【Abstract】 KPI, the performance indicator assessment method, plays an important role in the schedule management of marine engineering equipment projects. Because there are lots of uncertain factors affecting the progress of marine equipment projects which are intricate, the process shows the characteristics of nonlinear, and the huge deviations exist in the plans and actual management of progress. And, if the progress deviation could not be detected and rapid solved, there would be incalculable economic loss and reputation loss for an organization that undertakes the project of marine engineering equipment.This paper independently designed and put forward the KPI progress control system of marine engineering equipment project, and especially studied on the cause of progress deviations and its data mining algorithms, which is important to management in marine engineering equipment project scientifically and effectively as well as analysis of progress deviation.Firstly, this paper introduced the subject’s background, that’s necessary to capture causes of progress deviations as well as scientific and effective monitoring for the organization undertaking the project of marine engineering equipment in the technical means, for which there is no mature technology system. Based on this, it reviewed development of domestic and foreign on theories of key performance indicators, project progress control and management and data mining, and found that no one had proposed and studied techniques for analysis on causes of progress deviations, with intelligent mining algorithms combined with knowledge of progress deviation management.Based on the overall introduction for schedule control of marine engineering equipment project, this paper analyzed factors leading to progress deviations of the project, in use of Effect Diagram or Pareto analysis. Then it elaborated on the basic theory or classification of data mining as well as concrete application of project management, focusing on the Apriority data mining algorithm based on the mesh density spatial clustering optimization program, which lays on the basis for technical solution project for analysis on causes of progress deviations, and designs the prototype system of progress deviation analysis of marine engineering equipment. The main contents are as follows:This paper studied on the KPI system and the main content of the progress management of marine engineering equipment project which presented the progress control system of marine engineering equipment project KPI. It analyzed and described the planning, preparation, implementation, monitoring and other management systems of the progress of Marine engineering equipment.This paper described the current status of progress-control management and problems of it which existed in the Marine engineering equipment project, besides it presented the urgent objective problem of schedule deviation. This paper combined with professional management knowledge and analyzed the main causes of deviations. The poor response to follow-up caused by the schedule deviation was also included, besides the paper made it clear that the Pareto Analysis would be the technical methods to analyze the causes.This paper introduced the classic data mining algorithms and data mining classification techniques. Based on the full description of the marine engineering equipment construction technology, this paper described the role which the data mining technology played and how to use it in the progress control phase of marine equipment project, especially in the monitoring of schedule deviation. Among them, this paper presented the Apriority data mining algorithms based on the association rules. At the same time this paper also improved and optimized the algorithms.This paper built an analysis and decision support system of the schedule deviation in the marine engineering equipment project which was limited to the KPI mode. What’s more, the actual issues were verified by the intelligent data mining and Pareto analysis and finally the paper got the system designed.更多还原