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

The Changing Landscape of Energy Management in Manufacturing

The production and use of energy accounts for around 60% of global greenhouse gas (GHG) emissions, providing an intrinsic link between cause and effect. Considering that the manufacturing industry is responsible for roughly one-third of the global energy demand enforces the need to ensure that the manufacturing sector continually strives to reduce its reliance on energy and thus minimise GHG released into the atmosphere. Consequently, efficient management of energy consumption is of paramount importance for modern manufacturing businesses due to well-documented negative impacts regarding energy generation from fossil fuels and rapidly rising worldwide energy costs. This has resulted in a proliferation of research in this area which has considered improvements in energy consuming activities at the enterprise, facility, cell, machine and turret levels. However, there is now a need to go beyond incremental energy efficiency improvements and take more radical approaches to reduce energy consumption. It is argued that the largest energy reduction improvements can be achieved through better design of production systems or by adopting new business strategies that reduce the reliance of manufacturing businesses on resource consumption. This chapter initially provides a review of research in energy management (EM) at various manufacturing focus levels. The inappropriateness of current methods to cater for transformative and radical energy reduction approaches is discussed. In particular, limitations are found at the business strategy level since no technique exists to consider the input of these high level decisions on energy consumption. The main part of the chapter identifies areas of further opportunity in energy management research, and describes a method to facilitate further reductions in energy use and GHG production in manufacturing at the business strategy level

Application of a hybrid MCDM method in construction logistics

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Optimisation and Decision Support during the Conceptual Stage of Building Design

Merged with duplicate record 10026.1/726 on 28.02.2017 by CS (TIS)Modern building design is complex and involves many different disciplines operating in a fragmented manner. Appropriate computer-based decision support (DS) tools are sought that can raise the level of integration of different activities at the conceptual stage, in order to help create better designs solutions. This project investigates opportunities that exist for using techniques based upon the Genetic Algorithm (GA) to support critical activities of conceptual building design (CBD). Collective independent studies have shown that the GA is a powerful optimisation and exploratory search technique with widespread application. The GA is essentially very simple yet it offers robustness and domain independence. The GA efficiently searches a domain to exploit highly suitable information. It maintains multiple solutions to problems simultaneously and is well suited to non-linear problems and those of a discontinuous nature found in engineering design. The literature search first examines traditional approaches to supporting conceptual design. Existing GA techniques and applications are discussed which include pioneering studies in the field of detailed structural design. Broader GA studies are also reported which have demonstrated possibilities for investigating geometrical, topological and member size variation. The tasks and goals of conceptual design are studied. A rationale is introduced, aimed at enabling the GA to be applied in a manner that provides the most effective support to the designer. Numerical experiments with floor planning are presented. These studies provide a basic foundation for a subsequent design support system (DSS) capable of generating structural design concepts. A hierarchical Structured GA (SGA) created by Dasgupta et al [1] is investigated to support the generation of diverse structural design concepts. The SGA supports variation in the size, shape and structural configuration of a building and in the choice of structural frame type and floor system. The benefits and limitations of the SGA approach are discussed. The creation of a prototype DSS system, abritrarily called Designer-Pro (DPRO), is described. A detailed building design model is introduced which is required for design development and appraisal. Simplifications, design rationale and generic component modelling are mentioned. A cost-based single criteria optimisation problem (SCOP) is created in which other constraints are represented as design parameters. The thesis describes the importance of the object-oriented programming (OOP) paradigm for creating a versatile design model and the need for complementary graphical user interface (GUI) tools to provide human-computer interaction (HCI) capabilities for control and intelligent design manipulation. Techniques that increase flexibility in the generation and appraisal of concept are presented. Tools presented include a convergence plot of design solutions that supports cursor-interrogation to reveal the details of individual concepts. The graph permits study of design progression, or evolution of optimum design solutions. A visualisation tool is also presented. The DPRO system supports multiple operating modes, including single-design appraisal and enumerative search (ES). Case study examples are provided which demonstrate the applicability of the DPRO system to a range of different design scenarios. The DPRO system performs well in all tests. A parametric study demonstrates the potential of the system for DS. Limitations of the current approach and opportunities to broaden the study form part of the scope for further work. Some suggestions for further study are made, based upon newly-emerging techniques

Cost Risk Management for a Small to Medium-sized Enterprise in the Cladding Industry

To research the management of risk and cost in the cladding industry, this work has evaluated current practice and deficiencies, concentrating on the lack of integration or standardisation resulting in inaccurate cost estimates, unacceptable risks and loss of profit in cladding manufacture. The research presents an approach for integrating process- and technology-orientated improvements into a knowledge-based model to improve a cladding manufacturing SME’s performance. The research also presents a management method for the selection, integration, control and implementation of this approach. Controlling data transfer between systems produces a knowledge-based model, allowing cladding industry designers and estimators to take more accurate decisions, with the objective of reducing risk and improving company profitability. This model, with the addition of external supply chain elements, is a management framework, which can be termed an agile manufacturing system. The development of this framework has raised the following data certainty questions: • What is the measured uncertainty of that data? • How can the industry control and structure high data volumes transferred between systems to produce more accurate cost models? The answers to these questions were found by applying a structured methodology for the selection, integration and control of technology in the cladding industry, but involving the human factor. In this approach, the principle of entropy was adopted to measure data uncertainty. The structured methodology was made possible by a new categorisation into Innovative, Standard and Semi-Standard cladding projects. The research applied this structured methodology, combining qualitative and quantitative methods for validating assumptions, to a cladding industry SME case-study. The case-study investigated the validity of real cost and project data and calculated data uncertainty for specific projects, categorised as described, using a risk factor percentage predicted on entropy principles, based on historical data fed back from the SME’s ERP system. This risk factor approach was similar to that previously used in the insurance and banking industries. The risk percentage formulae used were based on assumptions extracted from qualitative and quantitative methods applied to the SME, its partner companies and industry specialists. Assumptions about the gross margins for UK metal cladding projects formed part of the risk percentage formulae. The results of this case-study found that gross margins varied from 5% in standard projects to 40% in the Innovative projects. An entropy scale was proposed as a basis for comparing risk calculation results, with the highest entropy equalling 100%, signifying the highest risk possible. It was found that risk rises in the case-study were from 23% for Standard to 93% for Innovative projects. This principle of a risk factor percentage was tested in the UK cladding manufacturer SME case-study and its value to the SME was demonstrated.

A Multicriteria Approach for the Evaluation of the Sustainability of Re-use of Historic Buildings in Venice

The paper presents a multiple criteria model for the evaluation of the sustainability of projects for the economic re-use of historical buildings in Venice. The model utilises the relevant parameters for the appraisal of sustainability, aggregated into three macro-indicators: intrinsic sustainability, context sustainability and economic-financial feasibility. The model has been calibrated by a panel of experts and tested on two reuse hypotheses of the Old Arsenal in Venice. The tests have proven the model to be a useful support in the early stages of evaluation of re-use projects, where economic improvements are to be combined with conservation, as it supports the identification of critical points and the selection of projects, thus providing not only a check-list of variables to be considered, but an appraisal of trade-offs between economic uses and requirements of conservation.Economic Reuse, Historical Building Conservation

Key Performance Criteria Influencing the Selection of Construction Methods Used for the Fabrication of Building Components in the Middle East

There is a lack of an efficient systematic approach to the selection of appropriate construction methods for building projects. Not only various innovative methods are now available, but also established methods may often be adapted inappropriately, without recourse to the necessary scientific foundation of their efficiency. The result is that there is a low level of performance on building projects. This study examines how key performance criteria were used in the selection of construction methods on projects. The study employed an extant review of the literature, cross-section survey of construction managers of building projects and experts interview in the Middle East to identify and evaluate the influencing of the key performance criteria on selecting construction methods for building projects. It emerged from the Pearson Correlation Coefficient and Analytical Hierarchy Process analysis that key performance criteria consisting of time, quality, and cost have strong positive significant roles in the selection of construction methods used on building projects and that these selection criteria differed depending on the building components. The study concludes that the likelihood of a construction method being selected for use on projects in the Middle East depends on its ability to shorten the duration, improving the quality and reduce the cost of projects

Safety Risk Management of LEED Building Construction : A BIM based Approach

Green buildings have been gaining popularity in the construction industry due to their low impact on the environment. Green buildings are aimed at creating energy-efficient, healthy, and environment-friendly buildings. However, OSHA records show that about 48% more accidents occur in green building construction as compared to traditional construction methods. Compromising the workers\u27 health and safety questions the true sustainability of the building. Green buildings have been a popular strategy in institutional sustainability agendas. Globally, LEED is the most popular green buildings rating system. Statistics show that an increasing number of construction projects intend to obtain the LEED certification in the next decade. However, elevated worker health and safety risks have been gradually becoming a concern while pursuing LEED credits. However, there exists a limited study comparing the safety hazards occurring in conventional construction practices and green construction practices.This research explores the major safety risks associated with LEED-certified building construction. Failure Mode Effect, Analysis (FMEA) is used to determine the safety risk associated with each LEED credit. LEED credits were ranked based on safety performance. Safety score and incremental cost of LEED credits were used to identify the optimal credit combination for LEED gold certification that reduces the safety risk and minimizes the cost. Bayesian Belief Networks (BBN) was used to analyze the impact of project factors on safety risk. This analysis identified how the risk level of LEED credits changes based on project parameters. Safety risks identified from FMEA and BBN were used to develop Building Information Modelling (BIM)-based solutions to improve worker safety. The outcomes of this research will address the challenges of LEED construction and inform the construction industry in enhancing the health and safety of construction workers with state-of-the-art technolog