Improving planning and estimating process for scaffolding operation in heavy industrial construction projects

改进重工业建设项目脚手架作业的规划和估算流程

• 批准号: 536164-2018
• 负责人: Han, SangHyeok
• 金额: $ 2.53万
• 依托单位: Concordia University
• 依托单位国家: 加拿大
• 项目类别: Collaborative Research and Development Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-01-01 至 2020-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=685435
• 关键词: Improving; planning; estimating; process; scaffolding

Heavy industrial construction projects generally involve complex structures, large-scale sites, and large numbers of workers from different disciplines such as civil, mechanical, and chemical. These disciplines may require similar or completely different scaffolding systems in order for workers to not only access their working areas but also move material horizontally and vertically. The variability of scaffolding systems required by the different disciplines operating on these complex sites can be a primary cause of increased project costs since general construction contractors need to have large volumes of scaffolding systems on site. However, planning and estimating of scaffolding works is a topic that has garnered relatively little attention either in academia or in practice. In practice, scaffolding works are estimated and planned in an ad-hoc manner which depends on expert experience, historical data, and a company's risk policy, even though scaffolding as temporary works account for more than 60% of the total project cost or approximately 30-40% of the total man-hours of direct work. To address this challenge, this research proposes following tasks: (i) identification of factors (e.g., disciplines and work classifications) affecting man-hours of scaffold activities; (ii) computation of ratio between scaffolding indirect man-hours and direct man-hours (per discipline); (ii) mapping man-hours of scaffolding works into sub-areas (e.g., modules, vessels, etc.) on-site; (iii) development of a predictive model using machine learning techniques to improve accuracy and efficiency in the scaffolding estimation process; and (iv) development of post-data mining 3D visualization for the purposes of the project management such as scheduling conflicts and monitoring severity and utilization of the scaffolding work on the construction site corresponding to project progress. As a result, this research will provide to the construction industry the following benefits: (i) improving the accuracy and efficiency of estimating scaffolding man-hours which can reduce the economic loss; (ii) improving the accuracy of scaffolding planning; and (iii) enhancing competitiveness in the international markets for construction contractors in Canada.

重型工业建设项目通常涉及复杂的结构，大规模地点以及来自不同学科的大量工人，例如民用，机械和化学。这些学科可能需要类似或完全不同的脚手架系统，以便工人不仅可以访问其工作区域，还可以水平和垂直移动材料。在这些复杂地点上运行的不同学科所需的脚手架系统的可变性可能是项目成本增加的主要原因，因为一般建筑承包商需要在现场拥有大量的脚手架系统。但是，脚手架作品的规划和估计是一个主题，在学术界或实践中，几乎没有引起关注。实际上，脚手架的工作是以临时的方式进行估算和计划的，这些方式取决于专家经验，历史数据和公司的风险政策，尽管作为临时工作的脚手架占项目总成本的60％以上，或者占直接工作总人数总数的30-40％。为了应对这一挑战，这项研究提出了以下任务：（i）识别影响脚手架活动的工时的因素（例如学科和工作分类）； （ii）脚手架间接工时和直接工时（每个学科）之间的比率计算； （ii）将脚手架作品的映射工程映射到次序（例如模块，容器等）的现场； （iii）使用机器学习技术开发预测模型，以提高脚手架估计过程中的准确性和效率； （iv）出于项目管理的目的，开发数据后3D可视化，例如调度冲突和监视严重性和在施工现场的脚手架工作的严重性和利用，与项目进度相对应。结果，这项研究将为建筑行业提供以下好处：（i）提高估计脚手架小时的准确性和效率，从而减少经济损失； （ii）提高脚手架计划的准确性； （iii）在加拿大建筑承包商国际市场上提高竞争力。