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Generative Design for Constructability improvements with BIM-Lean approach : master thesis
ID Rodríguez Hernández, José Luis (Author), ID Cerovšek, Tomo (Mentor) More about this mentor... This link opens in a new window, ID Janjić, Veljko (Co-mentor), ID Lavrič, Andrej (Co-mentor)

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Abstract
The construction industry suffers from the lack of adoption of advanced technologies. As a consequence, construction is among the least productive industries across various sectors. The researchers often point out that the critical issue is the lack of integration throughout the building project life cycle. Lack of information integration causes reworks unexpected changes, lower construction quality, delays, and on-site conflicts, which could be addressed in advance by a proper constructability study executed already in the design phase. Constructability is a technique that examines the logic of construction from the beginning to the end, seeking technical solutions that reduce project cost, time, and waste. The central part of the thesis provides a comprehensive overview and analysis of non-technical and technical constructability issues. Special attention is given to Lean and BIM approaches, which may serve as driving mechanisms that substantially improve constructability. The presented work tries to identify the value and integration of mechanisms for the improvement of constructability issues. Among the technical issues, the rationalization of the design plays an essential role in improving the execution and reducing project costs and delays. The final part of the thesis focuses on the rationalization of design addressing constructability issues by employing Generative Design. This approach is demonstrated in a case study of a complex building –Stožice Arena. The Arena case study shows the design rationalization techniques using generative design and machine learning, enabling informed shaping and clustering of the building envelope. The presented solution contributes to the evolving field of future architectural-structural design methods.

Language:English
Keywords:Constructability, BIM, Lean, Generative Design, Machine Learning, Parametric Design, Rationalization, Non-Technical problems in construction
Work type:Master's thesis/paper
Typology:2.09 - Master's Thesis
Organization:FGG - Faculty of Civil and Geodetic Engineering
Year:2021
PID:20.500.12556/RUL-131610 This link opens in a new window
COBISS.SI-ID:81443587 This link opens in a new window
Publication date in RUL:30.09.2021
Views:2814
Downloads:140
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Secondary language

Language:Slovenian
Title:Generativno projektiranje za izboljšanje izvedljivosti gradnje pri uporabi pristopa BIM-Lean : magistrsko delo
Abstract:
Gradbena industrija zaostaja pri uvajanju sodobnih tehnologij, zaradi česar gradbeništvo sodi med najbolj neučinkovite industrije z eno najnižjih stopenj produktivnosti med sektorji. Osrednji vidik, ki vpliva na nastalo stanje, je pomanjkanje integracije skozi življenjski cikel gradbenega projekta. Pomanjkanje integracije povzroča ponovno delo na posameznih projektih, brez da bi temeljito preučili zahteve za izvedljivost gradbenih del. Študija izvedljivosti gradbenih del je tehnika, ki sistematično preučuje logiko gradbenih del od začetka do konca, s ciljem, da zniža stroške, potreben čas za izvedbo in količino odpadnega materiala projekta. Vitka proizvodnja in BIM sta mehanizma, ki podpirata proces, ki je nujen, če želimo izboljšati izvedljivost gradbenih del. Pričujoča disertacija integrira te mehanizme, na način, da najprej identificiramo vrednost mehanizmov za reševanje najbolj pogostih težav pri izvedbi gradbenih del in jih nato vgradimo v študije izvedljivosti gradbenih del v fazi načrtovanja. Poleg tega naloga tudi obravnava, kako bi lahko z uporabo vitke proizvodnje in BIM odpravili ne-tehnične težave. Med tehničnimi težavami ima racionalizacija načrtovalskih rešitev ključen pomen pri izboljšanju izvedbe in zmanjšanju stroškov. Pristop je prikazan na študiji primera Arene Stožice, kjer je prikazana optimizacija oblike z uporabo orodij za generativno načrtovanje, ki omogoča iskanje optimalnih načrtovalskih rešitev. V sklepnem delu študije prikažemo tudi uporabnost strojnega učenja za standardizacijo in združevanje konstrukcijskih sistemov fasadnega ovoja.

Keywords:Konstruktivnost, BIM, vitko načrtovanje, generativno načrtovanje, strojno učenje, parametrično načrtovanje, racionalizacija, netehnični problemi pri gradnji

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