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.

重工业建设项目一般结构复杂、场地规模大、涉及土木、机械、化工等不同学科的大量工人。这些学科可能需要类似或完全不同的脚手架系统，以便工人不仅可以进入他们的工作区域，而且可以水平和垂直移动材料。在这些复杂场地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脚手架系统。然而，脚手架工程的规划和估算是一个无论在学术界还是在实践中都很少受到关注的话题。在实践中，脚手架工程的估算和规划取决于专家经验、历史数据和公司的风险政策，尽管脚手架作为临时工程占项目总成本的 60% 以上或约 30%。直接工作总工时的-40%。为了应对这一挑战，本研究提出以下任务：（i）确定影响脚手架活动工时的因素（例如学科和工作分类）； (ii) 计算脚手架间接工时与直接工时之间的比率（每个学科）； (ii) 将脚手架工程的工时划分为现场的子区域（例如模块、容器等）； (iii) 使用机器学习技术开发预测模型，以提高脚手架估算过程的准确性和效率； (iv) 开发数据挖掘后 3D 可视化，用于项目管理，例如进度冲突和监控与项目进度相对应的施工现场脚手架工作的严重性和利用率。因此，本研究将为建筑行业带来以下好处：（i）提高脚手架工时估算的准确性和效率，减少经济损失； (ii) 提高脚手架规划的准确性； (iii) 提高加拿大建筑承包商在国际市场的竞争力。