Computer Aided Assembly of Buildings

Roman Marcinkowski , Maciej Banach

Abstract

This article presents an interactive method of computer‐aided assembly planning. It is estimated that such planning will be more and more desirable due to the increasing use of prefabrication in construction. Prefabrication meets the trends of sustainable development and digitization as it enables the application of intelligent control systems at the stage of highly specialized production, assembly and facility maintenance. The presented planning method is based on the Monte Carlo simulations and logical algorithms for assembly work planning. It was determined on the basis of the literature studied and our own observations. The paper introduces a detailed model of assembly works planning and is an example of using a computer application developed on the basis of the described model. The example confirms the correctness of the algorithm and indicates its usefulness in the scope of analyzing many decision variants. Further research on labor productivity rates for assembly works, implementation of digital databases of assembly machines and prefabricated elements, as well as integration of the proposed application with the BIM environment should make it easier to commercialize the developed application.
Author Roman Marcinkowski (FCEMP / ICEn)
Roman Marcinkowski,,
- Insitute of Civil Engineering
, Maciej Banach (FCEMP / ICEn)
Maciej Banach,,
- Insitute of Civil Engineering
Journal seriesBuildings, ISSN 0007-3725, e-ISSN 2471-3112
Issue year2020
Vol20
No2
Pages1-20
Publication size in sheets0.95
Keywords in Englishassembly works; computer planning; Monte Carlo method; selection; construction; application
ASJC Classification2205 Civil and Structural Engineering; 2215 Building and Construction; 2216 Architecture
DOIDOI:10.3390/buildings10020028
Languageen angielski
Score (nominal)70
Score sourcejournalList
ScoreMinisterial score = 70.0, 15-06-2020, ArticleFromJournal
Publication indicators WoS Citations = 0; Scopus SNIP (Source Normalised Impact per Paper): 2016 = 0.568
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