A Knowledge-Based Approach to Preliminary Design of Buildings.

Harty, N. M.; Danaher, Maurice

doi:10.1680/istbu.1994.26324

Cited by 8 publications

(2 citation statements)

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“…Irrespective of the design workflow represented by the above terminologies in different countries, it is well recognised that the selection of optimal configuration for a building design involves activities and decisions that are heuristic in nature, and much reliance is placed on experience and judgment than on computation (Harty and Dnanher, 1994). The intricate nature of the preliminary design process entails a complex skill set in the analysis of systems' suitability towards functional and aesthetic requirements, whilst satisfying key constraints (Ballal and Sher, 2003).…”

Section: Buildability Assessment Modelmentioning

confidence: 99%

A scheme design buildability assessment model for building projects

Lam

Wong

Chan

et al. 2012

Construction Innovation

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Purpose -The purpose of this paper is to depict the developmental process of a buildability assessment model for use at the scheme design stage of building projects, which have a priority requirement for functional performance rather than aesthetic performance. Design/methodology/approach -First, major decisions made at the scheme design stage of building projects were identified through pilot interviews and a questionnaire survey on designers. Second, these decisions were rated for their relative importance towards buildability through another questionnaire survey on contractors, analysed using the reliability interval method. Based on these results, a list of buildable and non-buildable features and their impacts is compiled by interviewing major contractors. These findings were incorporated into a modified framework of buildability assessment for complete design, substituting information available at the scheme design stage. Validation was carried out using four sample projects and feedback from practitioners. Findings -The results obtained from the Scheme Design Buildability Assessment Model have been demonstrated as reflective of actual buildability level. Buildable and non-buildable features, as exemplified by typical building projects in Hong Kong Special Administrative Region, have been identified. Originality/value -This is the first model which provides a tool for use by the design team to evaluate the buildability of their designs at an early stage, so that necessary improvements can be made without affecting the development program.

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Section: Buildability Assessment Modelmentioning

confidence: 99%

A scheme design buildability assessment model for building projects

Lam

Wong

Chan

et al. 2012

Construction Innovation

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“…The intricate nature of the preliminary design process is due to the complexity of the skills required to complete this stage. In conceptualising a structure, the selection of its optimal configuration involves activities and decisions that are heuristic in nature and rely more on experience and judgement than on computation (Harty and Danaher, 1994). These design activities and decisions are often based on past experience and therefore are subject to qualitative reasoning rather than quantitative computations.…”

Section: Introductionmentioning

confidence: 99%

Artificial neural network for the selection of buildable structural systems

Ballal

Sher²

2003

Eng, Const and Arch Man

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In this study, artificial neural networks have been developed to acquire construction knowledge from past projects to integrate buildability considerations into the preliminary structural design process. Four artificial neural network models are presented. These allow the generation of an expeditious solution for given sets of design and buildability constraints. Once information is entered into the models, a recommendation of which structural scheme to choose is generated instantaneously. Thus, valuable design time is released, allowing designers the opportunity to invest in other equally important design tasks. The information entered into the models consists of site‐related information including site access; availability of working space; and speed of erection, and conceptual design information including type of building; number of storeys and gross floor area. The results show that artificial neural networks can be successfully used for the implementation of buildability at the preliminary stage of design.

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