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, Farook
• 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: 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=701083
• 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.

随着技术的进步和基于计算机的工具，研究人员已经引入了几个系统来衡量项目绩效，并随着项目的进展进行指导控制。然而，由于规划缺陷，建筑项目仍然遇到规划失败和生产力损失。这引起了人们对现有控制机制是否有能力向规划者或从业者发出警报并建立一个预警系统来指导今后行动的关切。本研究的目的是开发和应用一个现代化的生产计划决策支持系统的基础上精益原则和先进的度量，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，预计将更好地描述，监测和控制的各个动态方面的施工计划在最后的计划员系统的生产控制。拟议的决策支持系统可以提供对问题的主动检测和对项目状况的持续可见性，以便规划团队可以应用早期控制措施，以改进可靠的规划并减少里程碑延误。 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决策支持系统，以提高生产力，并在估计建筑项目的项目成本和时间表时增加确定性，这是项目规划和控制的基本要素。通过该项目开发的生产率数据库跟踪系统将提供一个标准方法，用于收集和存储生产率数据，测量和跟踪施工期间的生产率，并预测未来项目的生产率。通过该项目开发的人工智能决策支持系统将使用存储在数据库中的数据和专家知识来支持Ledcor Constructors Inc.（“Ledcor”）在预测未来项目的生产力和为正在进行的和计划中的项目提出生产力改进策略方面的作用。