| description abstract | Engineering design review is the process of assessing a design against codes and standards requirements to validate the accuracy and quality of the design and detecting problems before manufacturing and assembly begin. Building design regulations are normally in the form of texts, charts, tables, and mathematical expressions. These regulations and guidelines usually have legal status. Nevertheless, the cognitive and logical ability of the people is dissimilar to anything executed in computing machines. Consequently, the computerization of this process represents an actual challenge to the architecture, engineering, and construction (AEC) industry. Most of the cited methods for automated rules compliance auditing are either based on proprietary, domain-specific, or hard-coded rule-based representations, which may be useful in their specific applications. However, these methods have the disadvantages of being costly to maintain, cumbersome to modify, and lacking a comprehensive schema of rules and regulations modeling that can adapt to different domains, and thus don’t support an open data standard. They are often denoted as black box or gray box methods. This work offers a new comprehensive framework that reduces the deficiencies of the current approaches. The primary goal is to tackle the problem by concentrating on establishing a generalized adaptive framework (GAF) for a neutral data standard [such as the Industry Foundation Classes (IFC)] that enables automation of building design review processes to achieve design accuracy and efficiency. | |
