A Dynamic Framework for Construction Scheduling based on BIM using IFC

Tulke, Jan; Nour, Mohamed; Beucke, Karl

doi:10.2749/222137908796292119

Cited by 9 publications

(6 citation statements)

References 5 publications

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“…The information about the work methods, the human resources and the information about the materials and construction machinery are specified by the user. Dynamic 4D BIM-based simulation framework can automatically create and simulate construction schedules the cost calculations associated with the relevant scheduling [135]. Tulke & Hanff [136] on the other hand, have developed a similar 4D system that utilises geometric data and time schedules within the BIM model to estimate the construction sequence.…”

Section: Buildability and Construction Processesmentioning

confidence: 99%

Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities

Eleftheriadis

Mumovic

Greening

2017

Renewable and Sustainable Energy Reviews

213

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The continuous developments of Building Information Modelling (BIM) in Architecture, Engineering and Construction (AEC) industry supported by the advancements in material resourcing and construction processes could offer engineers the essential decision-making procedures to leverage the raising demands for sustainable structural designs. This article brings together the theory of Life Cycle Assessment (LCA) and the capabilities of BIM to survey the current developments in the energy efficiency of structural systems. In addition, the article explores the engineering dimensions of common decision-making procedures within BIM systems including optimisation methods, buildability limitations and safety and code compliance checks. The research presents critical expositions in both the engineering and sustainable energy domains. The article then argues that future innovations in the sustainable decision-making of buildings' structures would require BIM-integrated workflows in order to facilitate the conflicting nature of both energy efficient and engineering performance indexes. Finally, the study puts forward a series of research guidelines for a consolidated decision paradigm that utilises the capabilities of BIM within the engineering and sustainable energy domains in a synergistic manner.

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Section: Buildability and Construction Processesmentioning

confidence: 99%

Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities

Eleftheriadis

Mumovic

Greening

2017

Renewable and Sustainable Energy Reviews

213

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“…Integration of construction schedule planning within a coordinated BIMbased design process is proposed to address these challenges, eliminating redundancies and improving change management. However, existing software packages require adaptation to the collaborative, model-based scheduling approach, lacking adequate access to underlying data and efficient link mechanisms between product and process models [91].…”

Section: G Challenges and Opportunitiesmentioning

confidence: 99%

Building Information Modeling (BIM) for Construction Project Schedule Management: A Review

Nguyen,

Tran

2024

Eng. Technol. Appl. Sci. Res.

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Nowadays, the implementation and application of the BIM process in construction project management is a pressing need. This aligns with the global development trends in the construction sector and project information management in general. Numerous scholars and companies are actively engaged in learning, understanding, and investigating various aspects of BIM to stay up-to-date and meet the inevitable developmental requirements. This study focuses on the role and application of BIM, intending to identify limitations that hinder its fulfillment of expectations in project schedule management. In addition, it explores studies that show how other countries have effectively employed BIM in project management and progress tracking throughout the project lifecycle. The study aims to address three main objectives: (a) comprehensively examine and provide evidence related to the concept of BIM in project schedule management, (b) present the benefits of applying BIM in comparison to traditional methods in project management and operation, and (c) identify limitations stemming from various factors that may pose challenges in the application of BIM in project schedule management.

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“…A planner's survey was also conducted to enable validation of the project risk simulation procedure. The design of the planning survey was a structured questionnaire based on the following key project success-determining features: (1) The design maturity and scope definition at the time of the schedule estimate (Tulke et al 2008), (2) The form of contract and payment mechanism (Assaf and Al-Hejji 2006;Suprapto et al 2016), (3) Experience of the contractors in the relevant field (Chan et al, 2004), and (4) The tender method (including any early contractor involvement) (Suprapto et al, 2016). This information was gathered to help determine to what extent the risk simulations conducted are representative of real construction project complexity and the degree to which the stochastic nature of the simulation process affects simulated outcomes.…”

Section: Fig 14: Anova F-test Scores Of Featuresmentioning

confidence: 99%

Construction schedule risk analysis – a hybrid machine learning approach

Fitzsimmons¹,

Lu²,

Hong³

et al. 2022

ITcon

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The UK commissions about £100 billion in infrastructure construction works every year. More than 50% of them finish later than planned, causing damage to the interests of stakeholders. The estimation of time-risk on construction projects is currently done subjectively, largely by experience despite there are many existing techniques available to analyse risk on the construction schedules. Unlike conventional methods that tend to depend on the accurate estimation of risk boundaries for each task, this research aims to proposes a hybrid method to assist planners in undertaking risk analysis using baseline schedules with improved accuracy. The proposed method is endowed with machine intelligence and is trained using a database of 293,263 tasks from a diverse sample of 302 completed infrastructure construction projects in the UK. It combines a Gaussian Mixture Modelling-based Empirical Bayesian Network and a Support Vector Machine followed by performing a Monte Carlo risk simulation. The former is used to investigate the uncertainty, correlated risk factors, and predict task duration deviations while the latter is used to return a time-risk simulated prediction. This study randomly selected 10 projects as case studies followed by comparing their results of the proposed hybrid method with Monte Carlo Simulation. Results indicated 54.4% more accurate prediction on project delays.

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A Dynamic Framework for Construction Scheduling based on BIM using IFC

Cited by 9 publications

References 5 publications

Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities

Life cycle energy efficiency in building structures: A review of current developments and future outlooks based on BIM capabilities

Building Information Modeling (BIM) for Construction Project Schedule Management: A Review

Construction schedule risk analysis – a hybrid machine learning approach

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