Increasing the efficiency and efficacy of demolition through computerised 4D simulation. Issue 10 (15th July 2019)

• Record Type: Journal Article
• Authors: Kunieda, Yoichiro; Codinhoto, Ricardo; Emmitt, Stephen
• Is Part Of: Engineering, construction and architectural management. Volume 26:Issue 10(2019)
• Page Start: 2186
• Page End: 2205
• Publication Date: 2019-07-15
• Subjects: Construction -- Waste management; Construction industry -- Management -- Periodicals; Engineering -- Management -- Periodicals; Engineering -- Periodicals; Building -- Periodicals; 624.068
• DOI: 10.1108/ECAM-11-2018-0492
• Languages: English
• ISSNs: 0969-9988

Abstract

Abstract : Purpose: The purpose of this paper is to develop a novel tool to support decision making for enhanced demolition process efficiency and material waste sortability through computerised 4D motion workflow simulation. Design/methodology/approach: A time-lapse evaluation model was developed to classify and estimate the impact of building demolition processes and material waste recovery. The dynamic assessment of demolition, collision and mechanical impact was measured through computerised 4D motion game and physics engines. Waste recovery and treatment complemented the simulation algorithm. The simulation of the information workflow was tested through case study using two demolition strategies. Findings: The simulation successfully estimated the efficiency and efficacy of the different demolition strategies. Thus, simulation results can potentially support better decision making related to the definition of demolition strategies associated with recycling and re-use targets. Research limitations/implications: The simulation was limited to a simple machine-led demolition strategy. Further research is required to understand the impact of complex machine mechanic movements and processes on complex building fabrics. Originality/value: Modelling and evaluating the demolition process and its impact on material waste recovery with a time dimension is novel. The comparative analysis of quantitative data allows demolition professionals to find optimal and more sustainable demolition solutions and more efficient and safer implementation on site. It also contributes to a better understanding of the relationship between demolition strategy and waste sortability. This research represents a significant advancement in applied computing for building demolition waste recycling and notably, it improves the quality of information available in the definition of building demolition strategies.