Automated Planning and Scheduling for Industrial Construction Processes

• Author / Creator

  Hu, Di

• 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.
  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.
  
  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%.

• Subjects / Keywords

  • Pipe Spool Fabrication Sequence
  • Dynamic Programming
  • Domain Independent Artificial Intelligence Planning
  • Automated Planning and Scheduling
  • Time Stepped Simulation-based Scheduling
  • Module Installation Sequence
  • Industrial Construction

• Graduation date

  Spring 2013

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/R3V88D

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.