Modeling and Automation of Industrial Construction Operations

工业建筑运营的建模和自动化

• 批准号: RGPIN-2017-05078
• 负责人: Mohamed, Yasser
• 金额: $ 2.48万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2020
• 资助国家: 加拿大
• 起止时间: 2020-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=711337
• 关键词: Modeling; Automation; Industrial; Construction; Operations

Industrial construction projects represent a significant sector of the Canadian economy. These projects involve large investments from the energy sector and support thousands of jobs and are subject to competition from overseas construction companies. Modular construction is a common practice for industrial construction especially on Canadian oil-sand projects. In modular construction, most of the project is assembled from pre-fabricated components that are custom built off-site according to unique designs. These components include thousands of pipe spools, equipment and vessels, and structural steel elements. They are shipped to site either separately or pre-assembled in modular units for final installation. Industrial construction projects are often fast tracked and involve millions of man-hours provided by several parties along the engineering, procurement, fabrication, and site installation phases. The performance of operations in these phases is affected by the unique designs of the different components, design changes that happens during construction, deviations in material delivery by different suppliers, and availability of resources. This results in a fairly complex supply chain that can easily cause project cost and schedule overruns if not properly managed and optimized. Optimizing these operations is of great importance to retain the best value for investors in this sector and to maintain an advantage for Canadian contractors to be able to compete and export their know-how in an increasingly competitive global market. The objective of this proposed research is to investigate and develop models to represent operations in key industrial construction project delivery phases and suggest alternative solutions to optimize the performance during these phases. More specifically it will focus on 1) the analysis and representation of components data structures. These components are uniquely designed for each project but share some degree of repetition between projects. We aim at representing the data structures of these components in a way that allows us to analyze the similarities between projects and thus have better estimates of resource requirements and schedule expectations and develop methods for optimizing the packaging of these components into modules to minimize field work. The research will also target 2) the development of new process modeling approaches suitable for capturing the dynamics of site installation operations where out-of-sync component delivery, variation in trade man-hours availability, and congestion constrains are usually present and cannot be easily handled by traditional planning tools. Finally, the research will 3) suggest and test alternative methods for planning and predicting delivery dates during off-site fabrication and assembly operations using select data mining algorithms.

工业建设项目是加拿大经济的重要组成部分。这些项目涉及能源部门的大量投资，支持数千个就业岗位，并面临海外建筑公司的竞争。模块化建造是工业建筑的常见做法，尤其是加拿大油砂项目。在模块化建设中，大部分项目都是由预制组件组装而成，这些组件是根据独特的设计在场外定制的。这些组件包括数千个管段、设备和容器以及钢结构元件。它们要么单独运送到现场，要么预先组装成模块化单元以进行最终安装。工业建设项目通常进展迅速，在工程、采购、制造和现场安装阶段涉及多方提供的数百万工时。这些阶段的运营绩效受到不同组件的独特设计、施工期间发生的设计变更、不同供应商的材料交付偏差以及资源可用性的影响。这会导致供应链相当复杂，如果管理和优化不当，很容易导致项目成本和进度超支。优化这些运营对于为该行业的投资者保留最佳价值以及保持加拿大承包商在竞争日益激烈的全球市场中竞争和出口其专业知识的优势非常重要。 这项研究的目的是调查和开发模型来代表关键工业建设项目交付阶段的运营，并提出替代解决方案来优化这些阶段的绩效。更具体地说，它将重点关注 1）组件数据结构的分析和表示。这些组件是为每个项目专门设计的，但在项目之间共享一定程度的重复。我们的目标是以某种方式表示这些组件的数据结构，使我们能够分析项目之间的相似性，从而更好地估计资源需求和进度预期，并开发优化将这些组件打包到模块中的方法，以最大限度地减少现场工作。该研究还将目标 2) 开发新的流程建模方法，适用于捕获现场安装操作的动态，其中组件交付不同步、可用工时的变化以及拥塞约束通常存在且不易解决由传统的规划工具处理。最后，该研究将 3) 建议并测试使用选定的数据挖掘算法在场外制造和装配操作期间规划和预测交付日期的替代方法。