六西格玛设计(DFSS)方法创建清晰的经验教训数据库

Siddharth Banerjee, E. Jaselskis, Abdullah Alsharef
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引用次数: 4

摘要

在建筑工地工作的项目人员无法传递宝贵的经验,主要原因是缺乏记录这些信息的正式程序。构建项目在本质上很少是重复的,这突出了组织需要有健壮的数据存储库来促进知识共享。本文描述了为北卡罗莱纳交通部(NCDOT)创建一个名为“交流经验教训,交换建议,记录”(CLEAR)的新的内部仅基于网络的经验教训数据库的工作。采用识别、定义、开发、优化和验证(IDDOV)模型的六西格玛设计(DFSS)方法。这项研究的结果将有助于NCDOT将知识制度化,改善项目成本变化和进度可预测性。与此数据库相结合,数据仪表板将为上层管理人员提供有效的可视化,以便根据数据库中的课程信息做出明智的决策。仪表板将包括成功指标,如检测索赔数量和索赔金额的减少,见证上传到数据库的课程的周期性增长,以及加强专业人员之间的沟通。这种方法对构建应用程序的数据库实现的经验教训中的现有知识体系做出了重大贡献。通过减少索赔、改进设计和施工工作流程以及改进政策和标准,这一新应用程序的预期结果将是一个更高效和有效的公共组织。未来的研究人员可以利用本文提供的信息来构建新的强大的经验教训系统,以提高组织效率。
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Design For Six Sigma (DFSS) Approach for Creating CLEAR Lessons Learned Database
Project personnel working in construction sites fail to transfer invaluable experiences gained mostly due to the absence of a formalized process to record such information. Construction projects are seldom repetitive in nature and this highlights the need for organizations to have in place robust data repositories to facilitate knowledge sharing. This paper describes an effort in creating a new internal-only web-based lessons learned database named Communicate Lessons, Exchange Advice, Record (CLEAR) for the North Carolina Department of Transportation (NCDOT). A Design For Six Sigma (DFSS) approach of Identify, Define, Develop, Optimize, and Verify (IDDOV) model was used. Findings from this study will help NCDOT to institutionalize knowledge and improve project cost variations and schedule predictability. In conjunction with this database, a data dashboard is envisioned to provide effective visualizations for the upper management to make informed decisions based on the lessons information in the database. The dashboard will include success metrics such as detecting reduced numbers of claims and claims amounts, witnessing periodical increase in lessons uploaded into the database, and enhanced communication among specialized staff. This approach is a significant contribution to the existing body of knowledge in lessons learned database implementation for construction applications. The anticipated outcome of this new application will be a more efficient and effective public organization through reduced claims, improved designs, and construction workflows, and improved policies and standards. Future researchers can make use of information presented in this paper to build new robust lessons learned systems to improve organizational efficiency.
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