Building Information Modelling (BIM) is increasingly deployed as part of the processes in Architecture, Engineering and Construction (AEC) industry projects. While the benefits of BIM have been extensively proclaimed, explicit justification in terms of direct cost savings for BIM implementation on real-life projects, particularly for clash detection BIM workstream, are not well documented. This paper proposes and demonstrates a methodology to prove how BIM-based clash detection leads to cost savings. A schema is developed based on literature review and industrial expertise to quantify cost savings achieved by the utilisation of BIM-based clash detection and resolution. This paper provides validation of the proposed schema on a major infrastructure project. The developed schema includes the categorisation of identified clashes based on stakeholder involvement and required actions. The validation used the estimated cost of clashes were those not resolved before site operations took place. This schema simplifies both the categorisation and cost estimation of clashes in design. Estimated savings yielded 20% of contract value using the schema, for the multi-million-dollar project case study, thus extending evidence of BIM savings and benefits. The schema improves the existing process and valorises clash detection, thus allowing stakeholders to conduct a cost-benefit analysis. In addition, the categorisation methodology allows prioritising on the most costly clashes, and draw lessons learnt for further projects. This schema opens the path towards a systematic methodology to appraise the benefits of different BIM uses or processes.

This article describes a construction activity execution space analysis approach and a decision support tool for resolving execution space interference and conflict between work-face construction activities. Lack of execution space planning interrupt and badly affect the progress of construction activities. Also, in real situations, spatial congestion can severely reduce the productivity of workers sharing the same workspace, and may cause health and safety hazard issues. The aim of this article is to present a critical space-time analysis (CSA) approach that was developed to model and quantify workspace congestion and was encapsulated in a computerized tool dubbed PECASO (patterns execution and critical analysis of site-space organization) that was developed to assist site managers in the assignment and identification of workspace conflicts. A new concept of "visualizing workspace competition" between the construction activities is presented based on a unique representation of the dynamic nature of activities within the execution workspace, in 3D space and time. PECASO embraces 4D visualization and highlights the critical space control aspect to formulate an innovative 4D space planning and visualization tool. The CSA methodology and PECASO were validated using a real case study and the article concludes that the PECASO system has the potential to reduce the number of competing workspaces, as well as the conflicting volume/space between occupied workspaces. This in turn produces better assessment of the execution strategy for a given project schedule. Additionally, the PECASO system has introduced a new way of communicating the program of work in a high level of detail for space planning purposes

Bespoke precast concrete products are particularly designed and custom made for a construction project. The production planning of these products is complicated that considers important concerns, i.e. the reliability of the product delivery programme, the short lead‐time competitiveness, and the effective utilization of purpose‐built precast moulds. The planning has a high impact on the success of the production. The characteristics of the bespoke precast production are formulated with the flowshop scheduling technique so that an effective production plan can be arranged to meet these concerns. Genetic algorithm is used in the scheduling optimization. Its multi‐objective function includes total flowtime, total machine idle time, and total tardiness and earliness. After the model formulation, sensitivity analyses are conducted on the three model's parameters namely the number of mould availability, the processing time changes, and the weighting of the multi‐objective function. The proposed model is anticipated to support the planners to arrange economic and efficient production plans. Also, it can be used to determine the suitable number of moulds, the accuracy of the processing time estimation, and the weighting strategy of the multi‐objective optimization.