A Dynamic Just-in-Time Component Delivery Framework for Off-Site Construction

被引:12
|
作者
Si, Tongguang [1 ,2 ]
Li, Hong Xian [2 ]
Lei, Zhen [3 ]
Liu, Hexu [4 ]
Han, SangHyeok [5 ]
机构
[1] Shandong Jianzhu Univ, Sch Management Engn, 1000 Fengming Rd, Jinan 250101, Peoples R China
[2] Deakin Univ, Sch Architecture & Built Environm, Geelong, Vic 3220, Australia
[3] Univ New Brunswick, Dept Civil Engn, Fredericton, NB E3B 5A3, Canada
[4] Western Michigan Univ, Dept Civil & Construct Engn, Kalamazoo, MI 49008 USA
[5] Concordia Univ, Dept Bldg Civil & Environm Engn, Montreal, PQ H3G 1M8, Canada
关键词
CONCRETE PRODUCTION; OPTIMIZATION; MANAGEMENT; PERFORMANCE; SIMULATION; OFFSITE; SYSTEM; TRANSPORTATION; IDENTIFICATION; COORDINATION;
D O I
10.1155/2021/9953732
中图分类号
TU [建筑科学];
学科分类号
0813 ;
摘要
Off-site construction entails various advantages compared with the traditional construction method; however, the fragmentation of the prefabrication and assembly results in a complex supply chain. Both general contractors and factories often encounter production deviation, making the original component delivery plan nonoptimal. Traditionally, both parties tend to rely on internal resources or third-party resources to manage schedule changes, paying little attention to the optimisation of the component delivery process. The static compensation mechanisms reported in existing literature require factories to manage demand fluctuations but fail to encourage general contractors to control schedule deviations. Therefore, a dynamic compensation mechanism is proposed to achieve just-in-time component delivery, with which a factory shares possible changes for each component's delivery date to its clients on an inverse Kanban system. First, unfavourable changes for the factory schedule are allocated with surcharges, and the general contractor should compensate the factory if it accepts the date changes; secondly, schedule changes that are beneficial for the factory are assigned as incentives, and the general contractor receives the factory's incentive upon agreeing to the changes. Based on these two scenarios, genetic algorithm-based optimisation models are developed to achieve optimal delivery planning solutions. General contractors can obtain an optimal component delivery date to reduce the additional cost when they have changed the assembly schedule. General contractors can also optimise their component delivery schedule to trade their duration flexibility for incentives offered by factories. The models can help both parties to reduce component delivery waste when either side has the motivation to change the original component delivery schedules.
引用
收藏
页数:19
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