摘要
研究目的:我国铁路事业虽取得巨大发展,但同时也出现一系列问题,例如多信息系统交叉,业务数据分散、共享不充分;数据不完整、质量不高,大数据治理体系不完善;数据量急速膨胀而数据思维能力缺乏,知识应用不足等。为深刻分析这些问题的根本原因,本文提出完整的一套铁路工程信息化建设方案,以解决当前遇到的问题,也为日后铁路工程信息化的发展提供有益探索。研究结论:(1)要明确"培养核心竞争力、保持战略一致性、以需求为导向、建设服务型平台"的建设思路;(2)要深入应用知识体系梳理、知识模板和知识库构建、隐性知识显性化、数据资源标准化等方法论;(3)要开展知识体系建设、知识推送应用等工作,并建立一整套的围绕铁路工程信息化的标准、规范和评价体系;(4)本研究成果可用于铁路工程施工的信息化建设。
Research purposes:China’s railway industry has made tremendous progress,but at the same time a series of problems have arisen,such as multi-information system crossing,scattering business data and inadequate sharing;incomplete data,low quality,imperfect large data management system;rapid expansion of data volume and lack of data thinking ability,insufficient application of knowledge.The purpose of this paper is to deeply analyze the root causes of these problems and put forward a complete set of railway engineering informatization construction plan,which does not only solve the current problems,but also provides useful exploration for the future development of railway engineering informationization.Research conclusions:(1)The central idea of"cultivating core competitiveness,maintaining strategic consistency,demand-oriented and service-oriented platform"should be clearly defined.(2)The methods of knowledge system combing,knowledge template and knowledge base construction,tacit knowledge dominance and data resource standardization should be applied in depth.(3)Knowledge system construction,knowledge push and application should be carried out,and a set of standards,norms and evaluation system should be established in relation to railway engineering informationization.(4)The research results can be used in railway engineering informationization construction.
作者
郑心铭
ZHENG Xinming(China Railway,Beijing 100844,China)
出处
《铁道工程学报》
EI
北大核心
2019年第9期90-97,共8页
Journal of Railway Engineering Society
基金
中国铁路总公司重大课题(2017X003)
中国铁路总公司重点课题(N2018G036)
中国铁道科学研究院集团有限公司重大课题(2017YJ007)
中国铁道科学研究院集团有限公司重点课题(2018YJ108)
关键词
管理模型
大数据
工程建设
知识工程
精益管理
management model
big data
engineering construction
knowledge engineering
lean management