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Automated Planning and Scheduling for Industrial Construction Processes.

机译:工业建设过程的自动化计划和计划。

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摘要

Cost overrun and schedule slippage are common problems for mega industrial construction projects. Lack of effective planning and scheduling tools is identified as a major contributing factor to poor project performance. Planning and scheduling tools should be custom designed to address the characteristics of mage industrial projects: unique components, modularized execution strategy and its extremely accelerated project delivery. The main objective of this research is to investigate and develop automated solutions for planning and scheduling two essential stages of mega industrial projects, shop fabrication and on-site construction.;The research investigates use of domain-independent Artificial Intelligence (AI) planning to automate the sequence planing for pipe spool fabrication and on-site module installation. Experiment results show that AI planning is not suitable for sequencing spool fabrication due to the limited parsing capability of existing AI planners. However, AI planning is efficient to identify feasible sequence plans for module installation based on the current module availability and installation status.;The research finds Dynamic Programming (DP) is suitable to sequence pipe spool fabrication. A DP algorithm is developed to automatically identify the optimal sequence in terms of the minimum position welds. Simulation experiments were conducted with 29 real-life spools to quantify the performance improvement obtained from the DP algorithm. Results showes that by using the DP algorithm, there is a 45% reduction in the number of position welds, which is translated to a reduction in the total cycle time, ranging from 4.8% to 12%.;This research explores use of discrete event simulation (DES) to automate scheduling of shop fabrication and on-site construction processes. For industrial fabrication shops, a new simulation structuring methodology is developed to address the complex routing issue. Following this methodology, a simulation model is developed for pipe spool fabrication shops, which performs scheduling for shop operations, and mainly evaluates the impact of fabrication sequence on the spool cycle time. For site construction, a time-stepped simulation framework is developed to address congestion and dynamic resource allocation issue. For a real-life industrial construction case, this framework returns a schedule that has 12% shorter duration than those generated from Microsoft Project and Primavera P6.
机译:成本超支和进度延误是大型工业建设项目的常见问题。缺乏有效的计划和进度安排工具被认为是导致项目绩效不佳的主要因素。规划和计划工具应进行定制设计,以解决法师工业项目的特征:独特的组件,模块化的执行策略及其极大加速的项目交付。这项研究的主要目的是研究和开发用于计划和调度大型工业项目的两个基本阶段(车间制造和现场施工)的自动化解决方案;该研究研究了使用领域独立的人工智能(AI)计划来实现自动化阀芯制造和现场模块安装的顺序计划。实验结果表明,由于现有AI计划人员的解析能力有限,因此AI计划不适合顺序卷轴制造。但是,AI规划可以根据当前模块的可用性和安装状态来有效地确定可行的模块安装顺序计划。开发了一种DP算法,以根据最小位置焊缝自动识别最佳顺序。使用29个实际的线轴进行了仿真实验,以量化从DP算法获得的性能改进。结果表明,通过使用DP算法,位置焊缝数量减少了45%,这转化为总循环时间减少了4.8%至12%。模拟(DES),以自动安排车间制造和现场施工流程。对于工业制造车间,开发了一种新的模拟结构方法来解决复杂的布线问题。按照这种方法,为管轴制造车间开发了一个仿真模型,该模型执行车间操作的调度,并主要评估制造顺序对线轴循环时间的影响。对于站点建设,开发了一个分步仿真框架来解决拥塞和动态资源分配问题。对于现实生活中的工业建筑案例,此框架返回的时间表比Microsoft Project和Primavera P6生成的时间表的持续时间短12%。

著录项

  • 作者

    Hu, Di.;

  • 作者单位

    University of Alberta (Canada).;

  • 授予单位 University of Alberta (Canada).;
  • 学科 Engineering Civil.;Engineering Industrial.
  • 学位 Ph.D.
  • 年度 2013
  • 页码 397 p.
  • 总页数 397
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类 老年病学;
  • 关键词

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