Building information modeling for construction and demolition waste minimization

2020 ◽  
pp. 101-120 ◽  
Author(s):  
Alexander Koutamanis
Keyword(s):  
Building Information Modeling ◽  
Information Modeling ◽  
Construction And Demolition Waste ◽  
Waste Minimization ◽  
Demolition Waste ◽  
Building Information

scholarly journals Design for Deconstruction Using Integrated Lean Principles and BIM Approach

2021 ◽  
Vol 13 (14) ◽  
pp. 7856
Author(s):  
Mohamed Marzouk ◽  
Ahmed Elmaraghy
Keyword(s):  
Building Information Modeling ◽  
National Level ◽  
Information Modeling ◽  
Construction And Demolition Waste ◽  
Practical Implementation ◽  
Continuous Change ◽  
Demolition Waste ◽  
Lean Principles ◽  
Building Information ◽  
Building Elements

Existing buildings are characterized by the continuous change in the functional requirements of their end-users. As such, they are subjected to renovation or reconstruction, which is associated with total or partial demolition of the buildings, leading to an increase in construction and demolition waste. In addition, the materials abandoning the circular loop leave an adverse impact on the environment. This research integrates the building information modeling (BIM) approach and lean principles to ensure the early involvement of key participants in the decision-making process. This approach aids in planning the sequencing of deconstruction planning phases required before actual demolition activities take place. The paper presents the practical implementation of a BIM plug-in Tool. The assumptions and the scope based on which the plug-in was designed are briefly discussed. A case study for a mechanical, electrical, and plumbing (MEP) BIM model is introduced to illustrate the practical features of the proposed BIM plug-in Tool. The results encourage the selective dismantling of building elements based on the customers’ needs. Building information modeling capabilities in deconstruction planning were also investigated. The proposed tool aids in decreasing the uncertainties involved in demolition projects. The tool can be implemented on a national level to automate the deconstruction projects and optimize the extraction of salvaged building elements. The recovery option for such elements and their final destiny can be secured with sufficient time before their dismantling from their original locations.

scholarly journals Building Information Modeling (BIM) for Construction and Demolition Waste Management in Australia: A Research Agenda

2021 ◽  
Vol 13 (23) ◽  
pp. 12983
Author(s):  
Dongchen Han ◽  
Mohsen Kalantari ◽  
Abbas Rajabifard
Keyword(s):  
Waste Management ◽  
Research Agenda ◽  
Building Information Modeling ◽  
Ecological Impacts ◽  
Information Modeling ◽  
Construction And Demolition Waste ◽  
Full Potential ◽  
Demolition Waste ◽  
Ongoing Research ◽  
Building Information

Construction and demolition waste (C&DW) contribute to approximately 30% of the total waste generation worldwide, by which heterogeneous ecological impacts, such as resource depletion, global warming, and land degradation, are engendered. Despite ongoing research efforts to minimize construction waste via the Building Information Modeling (BIM)-aided design, there is a paucity of research on integrating BIM in demolition waste management (DWM). This study investigates prominent barriers and future research directions toward the wider adoption of BIM in C&DWM by conducting a systematic literature review. First, this study identifies the barriers that hinder the implementation of C&DWM in Australia; then, it explores the benefits and challenges of leveraging BIM applications for C&DWM. The findings suggest that, for existing buildings without up-to-date design drawings, it is imperative to improve the accuracy of data capturing and object recognition techniques to overcome the bottlenecks of BIM-DWM integration. Moreover, the development of regional-oriented material banks and their harmonization with life cycle assessment databases can extend the potential of BIM-based sustainability analysis, making it applicable to the DWM domain. This study proposes a research agenda on tackling these challenges to realize BIM’s full potential in facilitating DWM.

An estimation framework for building information modeling (BIM)-based demolition waste by type

2017 ◽  
Vol 35 (12) ◽  
pp. 1285-1295 ◽  
Author(s):  
Young-Chan Kim ◽  
Won-Hwa Hong ◽  
Jae-Woo Park ◽  
Gi-Wook Cha
Keyword(s):  
Classification System ◽  
Building Information Modeling ◽  
Construction Materials ◽  
Building Design ◽  
Management Plan ◽  
Information Modeling ◽  
Design Stage ◽  
Demolition Waste ◽  
Building Information ◽  
Building Level

Most existing studies on demolition waste (DW) quantification do not have an official standard to estimate the amount and type of DW. Therefore, there are limitations in the existing literature for estimating DW with a consistent classification system. Building information modeling (BIM) is a technology that can generate and manage all the information required during the life cycle of a building, from design to demolition. Nevertheless, there has been a lack of research regarding its application to the demolition stage of a building. For an effective waste management plan, the estimation of the type and volume of DW should begin from the building design stage. However, the lack of tools hinders an early estimation. This study proposes a BIM-based framework that estimates DW in the early design stages, to achieve an effective and streamlined planning, processing, and management. Specifically, the input of construction materials in the Korean construction classification system and those in the BIM library were matched. Based on this matching integration, the estimates of DW by type were calculated by applying the weight/unit volume factors and the rates of DW volume change. To verify the framework, its operation was demonstrated by means of an actual BIM modeling and by comparing its results with those available in the literature. This study is expected to contribute not only to the estimation of DW at the building level, but also to the automated estimation of DW at the district level.

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