Nashwan Dawood

DEVELOPMENT OF AN INTEGRATED INFORMATION RESOURCE BASE FOR 4D/VR CONSTRUCTION PROCESSES SIMULATION

Abstract The objective of this paper is to report on the development of an integrated database to act as an information resource base for 4D/VR construction process simulation. A comprehensive database was designed, implemented and populated with the School of Health Construction Project (a £8 million, three-story development at the University of Teesside campus). The database is composed of a core database of building components which is in turn, integrated with a CAD package (AUTOCAD 2000), a Project Management Package (MS Project) and Graphical User Interfaces. The core database was designed using Standard Classification Methods (Uniclass). One of the benefits of using the Uniclass method, a part from providing standards for structuring building information, is that it provides a media for integrating Product Breakdown Structure (PBS) with Work Breakdown Structure (WBS). This is an important aspect for delivering a meaningful 4D model. Integrated interfaces between MS Access Database, AutoCAD Drawings and MS Project Schedules were developed and implemented. Furthermore, the British Standards of layering convention (BS 1192-5) was adapted and implemented and justification for this is given in the part 2 of this document. The database was populated with detailed 2D drawings (whole building and M&E), schedules of work and resources of the School of Health Project. This paper is also addressing object definition, structuring the data, and establishing the relationships and dependencies within the data set, the WBS and building objects as well as modelling the building in 3D in order to capture the essential space- and time-critical attributes of tasks. Practical application of database throughout the construction process has been highlighted and discussed.

Estimating project and activity duration: a risk management approach using network analysis

Variations in the durations of activities are commonplace in the construction industry. This is due to the fact that the construction industry is influenced greatly by variations in weather, productivity of labour and plant, and quality of materials. Stochastic network analysis has been used by previous researchers to model variations in activities and produce more effective and reliable project duration estimates. A number of techniques have been developed in previous literature to solve the uncertain nature of networks, these are: PERT (program evaluation and review techniques), PNET (probabilistic network evaluation technique), NRB, (narrow reliability bounds methods) and MCS (Monte Carlo simulation). Although these techniques have proved to be useful in modelling variations in activities, dependence of activity duration is not considered. This can have a severe impact on realistically modelling projects. In this context, the objective of the present research is to develop a methodology that can accurately model activity dependence and realistically predict project duration using a risk management approach. A simulation model has been developed to encapsulate the methodology and run experimental work. In order to achieve this, the following tasks are tackled: identify risk factors that cause activity variations using literature reviews and conducting interviews with contractors; model risk factors and their influence on activity variations through conducting case studies and identifying any dependence between them; develop a computer based simulation model that uses a modified Monte Carlo technique to model activity duration and dependence of risk factors; and run experimental work to validate and verify the model.

Development of workspace conflict visualization system using 4D object of work schedule

Generally, workspace conflict analysis between construction activities by a 3D or 4D CAD system is performed for checking the conflict between element bodies. However, in case of many projects which consist of diverse activities in limited area, the workspace conflict analysis for reducing interferences caused by labor or equipment work is also an important management factor. In particular, if some activities are constructed adjacent to the overlap period, the workspace for those activities may be conflicting. Workspace conflicts decrease work productivity, and accidents can occur. Therefore, it is desirable that the workspace conflict should be minimized in order to perform efficient work. This paper presents a methodology that generates workspaces using a bounding box model and an algorithm in order to identify schedule and workspace conflict. Additionally, a workspace conflict verification system was developed to analyze the workspace information by integrating algorithms that include the automated generation of workspace models and an automatic check of workspace conflict within a 4D simulator. If a project manager can identify the workspace conflict using the system described, the overlapped activities can be rescheduled to minimize the conflict. A case study of a bridge project has been conducted to evaluate the practical applications and feasibility of the developed system. Therefore, the safety and constructability of a project can be improved by the workspace analysis system.

Developing Crew Allocation System for the Precast Industry Using Genetic Algorithms

: The Precast Concrete Industry (PCI) is one of the major contributors to the national economy and can be categorized as labor-intensive industry. It is currently experiencing shortcomings in terms of delivery products at a competitive cost and time. This is mainly due to the inefficiencies associate with planning and scheduling of skilled operators within crew configurations. This article presents a new strategy for efficient allocation of crews of workers in the precast concrete industry using Genetic Algorithms-based simulation modeling. The aim of this study is to develop a crew allocation system that can efficiently allocate possible crews of workers to precast concrete labor-intensive repetitive processes. Genetic algorithms (GAs) have been developed to solve this type of problem. Process mapping methodologies were used to identify and document the processes involved in producing precast components. Then process simulation was used to model and simulate all these processes and GAs were tailored to be embedded with the simulation model for a better search of promising solutions. GA operators were designed to suit this type of allocation problem. “Class Interval” selection strategy was developed to give a greater opportunity for the promising chromosomes to be chosen for further investigation. Dynamic crossover and mutation operators were developed to add more randomness to the search mechanism. The results showed that adopting different combinations of crews of workers had a substantial impact on reducing the process throughput time, minimizing resources cost, and achieving the required operatives utilization.

BIM in facilities management applications: a case study of a large university complex

Purpose – Building information modelling (BIM) in facilities management (FM) applications is an emerging area of research based on the theoretical proposition that BIM information, generated and captured during the lifecycle of a facility, can improve its management. Using this proposition as a starting point, the purpose of this paper is to investigate the value of BIM and the challenges affecting its adoption in FM applications. Design/methodology/approach – Two inter-related research methods are utilised. The literature is utilised to identify the application areas, value and challenges of BIM in FM. Due to the lack of case studies identified in the literature review, and to provide empirical evidence of the value and challenges of BIM in FM, a case study of Northumbria University’s city campus, is used to empirically explore the value and challenges of BIM in FM. Findings – The results demonstrated that BIM value in FM stems from improvement to current manual processes of information handover; improve...

Development of 4D‐based performance indicators in construction industry

Purpose – Despite its benefits, the uptake of 4D planning in the construction industry is slow and therefore there is a need to demonstrate its value over traditional planning technologies. The aim of this paper is to develop a novel approach that demonstrates the value of 4D tools to the construction industry.Design/methodology/approach – The research strategy utilised draws on several social science research methods. The data collection methods employed included a literature review, an open‐ended questionnaire, surveys, semi‐structured interviews and the analysis of historical site records. The data collected were analysed using qualitative and quantitative techniques in order to identify, develop and quantify 4D‐based key performance indicators.Findings – This paper identifies and quantifies 4D‐based key performance indicators using case study analysis. In the case studies it was found that, on average, a 17 per cent increase in planning efficiency were achieved by the use of 4D technology, while the c...

A capacity planning model for precast concrete building products

Abstract Examples of poor performance of precasters in terms of inefficient resource utilization and overstocking are commonplace in the precast industry. This is partly due to inaccurate planning practices and poor managerial decisions. The object of this paper is to develop a computer-based capacity planning model for precast concrete building products in order to help production managers to make better planning decisions and explore options open to them. The planning model is a factory simulator which automates the process of planning and predicts the effect of several managerial strategies before actual production commences. The performance of the model is examined using both real and hypothetical demand patterns. The paper has concluded that the model is a practical and considerable managerial tool for exploring and testing managerial options open to production managers. The model is suitable for companies which produce variety of concrete products on several plant. The authors welcome any collaboration with the industry to further the knowledge and application of the model. The model can be used to educate managers about the production process, the utilization of plant and the consequence of using certain managerial decisions.

Visualisation of a stockyard layout simulator "SimStock": A case study in precast concrete products industry

Abstract The demand for the concrete products is seasonal and huge stock is built in winter for dispatch in summer. As 1000–2000 products with different sizes, weights, handling and stacking requirements are involved, the process of deciding appropriate locations to stock the products and track them while loading into lorries for dispatch becomes complex. Stockyards in the precast concrete products industry are experiencing space congestion, and long vehicle waiting times for both the storage and retrieval of concrete products due to lack of a proper methodology to manage stockyard layouts and their operations. This paper describes an ongoing research that addresses the stockyard layout management problem through the development of an integrated simulation and visualisation model. The paper focuses on the development of the visualisation and simulation element of the stockyard management system “SimStock”. The simulation model has been developed using ARENA/SIMAN, a general-purpose simulation language. The simulation model integrates production and forecast schedules, evaluates “what-if” scenarios with different layouts, products allocation to storage locations and order picking policies. The output of the simulation model is recorded in a database (Ms Access). The visualisation model was developed through integrating AutoCAD2000 with the database of the simulation model such that the simulated layouts can be studied in greater details and validated in a simpler manner. The visualisation module is used to assist managers in designing stock layouts (one of the major inputs to the simulation model) and visualise the simulation process in 2D (and 3D) perspectives, and manage real time implementation of proposed stockyard solutions.

A visual energy performance assessment and decision support tool for dwellings

BackgroundThe target for carbon dioxide (CO2) emissions reduction in the UK is set at 20% by 2020 and 80% by 2050. The UK housing stock is one of the least energy efficient in Europe. The energy used in homes accounts for more than a quarter of energy use and carbon dioxide emissions in Great Britain. Therefore, it is imperative to improve the energy performance of the existing housing stock and fully exploit energy efficiency and renewable energy interventions. The UK has developed several policies and initiatives to improve the energy performance of the housing stock and there are a number of databases that hold information about the condition of the housing stock. However, existing approaches and tools do not allow decision makers to assess the environmental and economic effectiveness of CO2 reduction strategies at the neighbourhood level.MethodsThis research presents a methodology that integrates these energy databases with visualisation systems and multi-criteria decision analyses to enable the evaluation of the environmental and financial implications of various energy efficiency and renewable energy interventions at both building and neighbourhood levels. The methodology is prototyped in a proof-of-concept tool which is validated and tested in an empirical case study with local authorities and social housing providers.ResultsThe validation study compared the energy performance of the dwellings estimated by the proposed methodology with the energy performance calculated from actual survey and confirmed that the results are consistent. The case study demonstrated that the methodology and the prototype can be reliably utilised to evaluate the environmental and financial implications of various energy efficiency and renewable energy interventions.ConclusionThe findings illustrate that the tool is particularly useful for town planners, local authorities and social housing providers. They can make informed decisions about the implementation of energy policies and initiatives along with energy suppliers, building engineers and architects. The tool developed in the research and presented in this paper can contribute to meeting CO2 emission reduction targets.

Flowshop scheduling model for bespoke precast concrete production planning

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 models 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.