4D-based automation of heavy lift planning in industrial construction projects

被引:8
|
作者
Han, SangHyeok [1 ]
Lei, Zhen [2 ]
Hermann, Ulrich [3 ]
Bouferguene, Ahmed [4 ]
Al-Hussein, Mohamed [5 ]
机构
[1] Concordia Univ, Ctr Innovat Construct & Infrastruct Engn & Manage, Dept Civil Bldg & Environm Engn, Montreal, PQ, Canada
[2] Univ New Brunswick, Dept Civil Engn, Off Site Construct Res Ctr OCRC, Fredericton, NB E3B 5A3, Canada
[3] PCL Ind Management Inc, Edmonton, AB T6E 3P4, Canada
[4] Univ Alberta, Campus St Jean, Edmonton, AB T6C 4G9, Canada
[5] Univ Alberta, Dept Civil & Environm Engn, Edmonton, AB T6G 2W2, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
heavy industrial project; crane management system; 4D visualization; 3D motion planning; lift path planning; CRANE OPERATIONS; SIMULATION; VISUALIZATION; IDENTIFICATION; ALGORITHM;
D O I
10.1139/cjce-2019-0825
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
In northern Canada, due to the harsh weather and high labor cost, contractors prefer to using modular construction approach to complete heavy industrial projects, where mobile crane are used for onsite module installations. In current practice, module lifts are often planned manually by rigging engineers. With a large number of heavy lifts to be analyzed per project, the planning process is tedious and error prone. This paper represents a data-driven crane management system with three features: (1) identification of design errors in lifting planning; (2) responses to design changes; and (3) dynamic 3D trajectory-based lifting visualization. It covers two types of crane operations: pick from a fixed location, and pick and walking operation. This developed system helps reduce lifting time and improves safety and quality, where various lifting scenarios need to be analyzed. The system has been implemented at a collaborator company for demonstration and validation.
引用
收藏
页码:1115 / 1129
页数:15
相关论文
共 38 条
  • [1] A methodology for mobile crane lift path checking in heavy industrial projects
    Lei, Zhen
    Taghaddos, Hosein
    Hermann, Ulrich
    Al-Hussein, Mohamed
    AUTOMATION IN CONSTRUCTION, 2013, 31 : 41 - 53
  • [2] 3D Visualization-Based Motion Planning of Mobile Crane Operations in Heavy Industrial Projects
    Han, SangHyeok
    Lei, Zhen
    Bouferguene, Ahmed
    Al-Hussein, Mohamed
    Hermann, Ulrich
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2016, 30 (01)
  • [3] Reinforcement learning-based simulation and automation for tower crane 3D lift planning
    Cho, SungHwan
    Han, SangUk
    AUTOMATION IN CONSTRUCTION, 2022, 144
  • [4] Heavy mobile crane lift path planning in congested modular industrial plants using a robotics approach
    Kayhani, Navid
    Taghaddos, Hosein
    Mousaei, Ali
    Behzadipour, Saeed
    Hermann, Ulrich
    AUTOMATION IN CONSTRUCTION, 2021, 122
  • [5] Mathematical model to optimally solve the lift planning problem in high-rise construction projects
    Yazdi, Alireza Jalali
    Maghrebi, Mojtaba
    Bazaz, Jafar Bolouri
    AUTOMATION IN CONSTRUCTION, 2018, 92 : 120 - 132
  • [6] Optimizing Heavy Lift Plans for Industrial Construction Sites Using Dijkstra's Algorithm
    Mousaei, Ali
    Taghaddos, Hosein
    Bagheri, S. Marzieh
    Hermann, Ulrich
    JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2021, 147 (11)
  • [7] Development of a 4D object-based system for visualizing the risk information of construction projects
    Kang, Leen Seok
    Kim, Sung-Keun
    Moon, Hyoun Seok
    Kim, Hyeon Seung
    AUTOMATION IN CONSTRUCTION, 2013, 31 : 186 - 203
  • [8] 4D visualization of highway construction projects
    Liapi, KA
    SEVENTH INTERNATIONAL CONFERENCE ON INFORMATION VISUALIZATION, PROCEEDINGS, 2003, : 639 - 644
  • [9] An evaluation of the applicability of 4D CAD on construction projects
    Mahalingam, Ashwin
    Kashyap, Rahul
    Mahajan, Charudatta
    AUTOMATION IN CONSTRUCTION, 2010, 19 (02) : 148 - 159
  • [10] Physical Distancing Analytics for Construction Planning Using 4D BIM
    Hosny, Abdelhady
    Nik-Bakht, Mazdak
    Moselhi, Osama
    JOURNAL OF COMPUTING IN CIVIL ENGINEERING, 2022, 36 (04)