A decision support system for dynamic construction planning and control as a foundation for developing a productivity culture

用于动态施工规划和控制的决策支持系统，作为发展生产力文化的基础

• 批准号: 549210-2019
• 负责人: Hamzeh, FarookF
• 金额: $ 3.64万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Alliance Grants
• 财政年份: 2022
• 资助国家: 加拿大
• 起止时间: 2022-01-01 至 2023-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=748947
• 关键词: decision; support; system; dynamic; construction

With the advancement of technology and computer-based tools, researchers have introduced several systems to measure project performance and guide control as the project progresses. However, construction projects still encounter planning failures and productivity losses as a result of planning deficiencies. This raises concerns regarding the capability of the current control mechanisms in alarming planners or practitioners and generating an early warning system to guide future actions. This research study aims to develop and apply a modern production planning decision-support system based on lean principles and advanced metrics to address several project performance areas that are currently partially measured. The developed planning system is expected to better describe, monitor, and control the various dynamic aspects of construction planning within the Last Planner System for production control. The proposed decision support system can provide a proactive detection of issues and constant visibility of project status so that planning teams can apply earlier control measures to improve reliable planning and reduce milestone delays. To support a productivity culture, this project will also develop a productivity database tracking and an artificial intelligence (AI) decision support system for improving productivity and increasing certainty when estimating project costs and schedule on construction projects, which are essential elements in project planning and control. The productivity database tracking system developed through this project will provide a standard approach for collecting and storing productivity data, measuring and tracking productivity during construction, and predicting productivity for future projects. The artificial intelligence decision support system developed through this project will use the data and expert knowledge stored in the database to support Ledcor Constructors Inc. ("Ledcor") in predicting productivity for future projects and suggesting productivity improvement strategies for ongoing and planned projects.

随着技术和基于计算机的工具的进步，研究人员引入了多种系统来衡量项目绩效并随着项目的进展指导控制。然而，建设项目仍然会因规划缺陷而遭遇规划失败和生产力损失。这引起了人们对当前控制机制能否向规划者或从业者发出警报以及生成预警系统来指导未来行动的能力的担忧。本研究旨在开发和应用基于精益原则和先进指标的现代生产计划决策支持系统，以解决目前部分衡量的几个项目绩效领域。开发的规划系统有望更好地描述、监控和控制用于生产控制的最后规划系统内施工规划的各个动态方面。拟议的决策支持系统可以提供主动的问题检测和项目状态的持续可见性，以便规划团队可以应用早期的控制措施来改进可靠的规划并减少里程碑延迟。为了支持生产力文化，该项目还将开发生产力数据库跟踪和人工智能（AI）决策支持系统，以提高生产力并增加估算项目成本和建设项目进度时的确定性，这是项目规划和控制的基本要素。通过该项目开发的生产力数据库跟踪系统将为收集和存储生产力数据、测量和跟踪施工期间的生产力以及预测未来项目的生产力提供标准方法。通过该项目开发的人工智能决策支持系统将利用数据库中存储的数据和专家知识来支持Ledcor Constructors Inc.（“Ledcor”）预测未来项目的生产力，并为正在进行和计划中的项目提出生产力改进策略。