ToolSHeD™: The development and evaluation of a decision support tool for health and safety in construction design

Purpose - The purpose of this paper is to describe an innovative information and decision support tool (ToolSHeD(TM)) developed to help construction designers to integrate the management of OHS risk into the design process. The underlying structure of the prototype web-based system and the process of knowledge acquisition and modelling are described. Design/methodology/approach - The ToolSHeD(TM) research and development project involved the capture of expert reasoning regarding design impacts upon occupational health and safety (OHS) risk. This knowledge was structured using an innovative method well-suited to modelling knowledge in the context of uncertainty and discretionary decision-making. Example "argument trees" are presented, representing the reasoning used by a panel of experts to assess the risk of falling from height during roof maintenance work. The advantage of using this method for modelling OHS knowledge, compared to the use of simplistic rules, is discussed. Findings - The ToolSHeD™ prototype development and testing reveals that argument trees can represent design safety risk knowledge effectively. Practical implications - The translation of argument trees into a web-based decision support tool is described and the potential impact of this tool in providing construction designers (architects and engineers) with easy and inexpensive access to expert OHS knowledge is discussed. Originality/value - The paper describes a new computer application, currently undergoing testing in the Australian building and construction industry. Its originality lies in the fact that ToolSHeD(TM) deploys argument trees to represent expert OHS reasoning, overcoming inherent limitations in rule-based expert systems

Green-building information modelling (Green-BIM) assessment framework for evaluating sustainability performance of building projects: a case of Nigeria

There is a research gap in the use of digital systems to aid the sustainability performance assessment of buildings, which informs the development of the green-BIM assessment (GBA) framework in this paper. The study employed a conceptual framework design, expert surveys, and case studies to identify and establish the different components of the GBA framework. The developed GBA framework incorporates the BSAM scheme as its primary green building rating system and provides a cost-effective solution for sustainability appraisal. The findings revealed that the 4Ws of the information exchange workflows would facilitate the GBA system's implementation and the expert validation confirmed its suitability for the Nigerian context. The C-SDSS served as the digital component of the GBA system towards automating the sustainability performance assessment of buildings. The GBA system provides the construction industry with a useful tool that could ease comparing two or more building projects or its designs for several uses – such as contract bidding, evaluating alternative designs, and the like. The application of the GBA system can be extended to facilitate its adoption in other regions or countries. The study’s deliverables are expected to enhance smart and eco-initiatives in Nigeria and sub-Saharan Africa

Agent-based hybrid framework for decision making on complex problems

Electronic commerce and the Internet have created demand for automated systems that can make complex decisions utilizing information from multiple sources. Because the information is uncertain, dynamic, distributed, and heterogeneous in nature, these systems require a great diversity of intelligent techniques including expert systems, fuzzy logic, neural networks, and genetic algorithms. However, in complex decision making, many different components or sub-tasks are involved, each of which requires different types of processing. Thus multiple such techniques are required resulting in systems called hybrid intelligent systems. That is, hybrid solutions are crucial for complex problem solving and decision making. There is a growing demand for these systems in many areas including financial investment planning, engineering design, medical diagnosis, and cognitive simulation. However, the design and development of these systems is difficult because they have a large number of parts or components that have many interactions. From a multi-agent perspective, agents in multi-agent systems (MAS) are autonomous and can engage in flexible, high-level interactions. MASs are good at complex, dynamic interactions. Thus a multi-agent perspective is suitable for modeling, design, and construction of hybrid intelligent systems. The aim of this thesis is to develop an agent-based framework for constructing hybrid intelligent systems which are mainly used for complex problem solving and decision making. Existing software development techniques (typically, object-oriented) are inadequate for modeling agent-based hybrid intelligent systems. There is a fundamental mismatch between the concepts used by object-oriented developers and the agent-oriented view. Although there are some agent-oriented methodologies such as the Gaia methodology, there is still no specifically tailored methodology available for analyzing and designing agent-based hybrid intelligent systems. To this end, a methodology is proposed, which is specifically tailored to the analysis and design of agent-based hybrid intelligent systems. The methodology consists of six models - role model, interaction model, agent model, skill model, knowledge model, and organizational model. This methodology differs from other agent-oriented methodologies in its skill and knowledge models. As good decisions and problem solutions are mainly based on adequate information, rich knowledge, and appropriate skills to use knowledge and information, these two models are of paramount importance in modeling complex problem solving and decision making. Follow the methodology, an agent-based framework for hybrid intelligent system construction used in complex problem solving and decision making was developed. The framework has several crucial characteristics that differentiate this research from others. Four important issues relating to the framework are also investigated. These cover the building of an ontology for financial investment, matchmaking in middle agents, reasoning in problem solving and decision making, and decision aggregation in MASs. The thesis demonstrates how to build a domain-specific ontology and how to access it in a MAS by building a financial ontology. It is argued that the practical performance of service provider agents has a significant impact on the matchmaking outcomes of middle agents. It is proposed to consider service provider agents\u27 track records in matchmaking. A way to provide initial values for the track records of service provider agents is also suggested. The concept of ‘reasoning with multimedia information’ is introduced, and reasoning with still image information using symbolic projection theory is proposed. How to choose suitable aggregation operations is demonstrated through financial investment application and three approaches are proposed - the stationary agent approach, the token-passing approach, and the mobile agent approach to implementing decision aggregation in MASs. Based on the framework, a prototype was built and applied to financial investment planning. This prototype consists of one serving agent, one interface agent, one decision aggregation agent, one planning agent, four decision making agents, and five service provider agents. Experiments were conducted on the prototype. The experimental results show the framework is flexible, robust, and fully workable. All agents derived from the methodology exhibit their behaviors correctly as specified

An Assessment of Lean Design Management Practices in Construction Projects

[EN] Evidence exists for the application of lean management practices in the design process. However, there is no systematic review of this type of practice that links the design management practices to the lean construction principles. There is no tool to assess the level of use of lean design management practices in construction projects either. Therefore, this paper aims to assess the lean management practices that are performed at the design phase of construction projects. The research was divided into a literature review of design management practices; a validation of lean design management practices with a practice¿principle relationship, based on an expert survey; the devolvement of a tool (questionnaire) to evaluate the lean design management practices; and an assessment in 64 construction projects (coherence, reliability, correlation, and descriptive analysis). It is concluded that evidence exists for the implementation of 19 lean design management practices. These practices are grouped into three categories: stakeholder management, planning and control, and problem solving and decision making. Additionally, in the assessment of the 64 projects, it can be observed that the lean design management practices are at initial levels of implementations, so there is a significant development gap. This research proposes a tool to assess management practices in the design phase of construction projects; then, the study identifies implementations gaps, it provides benchmarks with other projects, and it improves the design process through a taxonomy of lean design management practices.This research was funded by CONICYT grant number PCHA/National Doctorate/2018-21180884 for funding the graduate research of Herrera, and the financial support by FONDECYT (1181648).Herrera, RF.; Mourgues, C.; Alarcon, LF.; Pellicer, E. (2019). An Assessment of Lean Design Management Practices in Construction Projects. 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A framework for integrating syntax, semantics and pragmatics for computer-aided professional practice: With application of costing in construction industry

Producing a bill of quantity is a knowledge-based, dynamic and collaborative process, and evolves with variances and current evidence. However, within the context of information system practice in BIM, knowledge of cost estimation has not been represented, nor has it been integrated into the processes based on BIM. This paper intends to establish an innovative means of taking data from the BIM linked to a project, and using it to create the necessary items for a bill of quantity that will enable cost estimation to be undertaken for the project. Our framework is founded upon the belief that three components are necessary to gain a full awareness of the domain which is being computerised; the information type which is to be assessed for compatibility (syntax), the definition for the pricing domain (semantics), and the precise implementation environment for the standards being taken into account (pragmatics). In order to achieve this, a prototype is created that allows a cost item for the bill of quantity to be spontaneously generated, by means of the semantic web ontology and a forward chain algorithm. Within this paper, ‘cost items’ signify the elements included in a bill of quantity, including details of their description, quantity and price. As a means of authenticating the process being developed, the authors of this work effectively implemented it in the production of cost items. In addition, the items created were contrasted with those produced by specialists. For this reason, this innovative framework introduces the possibility of a new means of applying semantic web ontology and forward chain algorithm to construction professional practice resulting in automatic cost estimation. These key outcomes demonstrate that, decoupling the professional practice into three key components of syntax, semantics and pragmatics can provide tangible benefits to domain use

Querying a regulatory model for compliant building design audit

The ingredients for an effective automated audit of a building design include a BIM model containing the design information, an electronic regulatory knowledge model, and a practical method of processing these computerised representations. There have been numerous approaches to computer-aided compliance audit in the AEC/FM domain over the last four decades, but none has yet evolved into a practical solution. One reason is that they have all been isolated attempts that lack any form of standardisation. The current research project therefore focuses on using an open standard regulatory knowledge and BIM representations in conjunction with open standard executable compliant design workflows to automate the compliance audit process. This paper provides an overview of different approaches to access information from a regulatory model representation. The paper then describes the use of a purpose-built high-level domain specific query language to extract regulatory information as part of the effort to automate manual design procedures for compliance audit

A knowledge-based decision support system for roofing materials selection and cost estimating: a conceptual framework and data modelling

A plethora of materials is available to the modern day house designer but selecting the appropriate material is a complex task. It requires synthesising a multitude of performance criteria such as initial cost, maintenance cost, thermal performance and sustainability among others. This research aims to develop a Knowledge-based Decision support System for Material Selection (KDSMS) that facilitates the selection of optimal material for different sub elements of a roof design. The proposed system also has a facility for estimating roof cost based on the identified criteria. This paper presents the data modelling conceptual framework for the proposed system. The roof sub elements are modelled on the Building Cost Information Service (BCIS) Standard Form of Cost Analysis. This model consists of a knowledge base and a database to store different types of roofing materials with their corresponding performance characteristics and rankings. The system s knowledge is elicited from an extensive review of literature and the use of a domain expert forum. The proposed system employs the multi criteria decision method of TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution), to resolve the materials selection and optimisation problem. The KDSMS is currently being developed for the housing sector of Northern Ireland

A knowledge-based decision support system for roofing materials selection

Varieties of materials are available for roof housing construction but selecting the appropriate material is a complex and ponderous task. In order to choose the right material, a multitude of performance criteria would need to be considered. This research aims to develop a knowledge-based decision support system for material selection (KDSMS) to facilitate the selection of optimal material for different sub elements of roof design. This model consists of a knowledge base and databases to store different types of roofing materials with their corresponding performance characteristics. Knowledge is elicited from domain experts and extensive literature review. The proposed system employs the use of TOPSIS (Technique of ranking Preferences by Similarity to the Ideal Solution) multiple criteria decision making method, to solve the materials selection and optimisation problem where initial cost, maintenance cost, thermal performance and sustainability criteria are considered among others. The proposed system is currently being developed for the housing sector in Northern Ireland. This paper presents and explains the framework of the proposed system

Context guided retrieval

This paper presents a hierarchical case representation that uses a context guided retrieval method The performance of this method is compared to that of a simple flat file representation using standard nearest neighbour retrieval. The data presented in this paper is more extensive than that presented in an earlier paper by the same authors. The estimation of the construction costs of light industrial warehouse buildings is used as the test domain. Each case in the system comprises approximately 400 features. These are structured into a hierarchical case representation that holds more general contextual features at its top and specific building elements at its leaves. A modified nearest neighbour retrieval algorithm is used that is guided by contextual similarity. Problems are decomposed into sub-problems and solutions recomposed into a final solution. The comparative results show that the context guided retrieval method using the hierarchical case representation is significantly more accurate than the simpler flat file representation and standard nearest neighbour retrieval