Constructability Analysis: Machine Learning Approach

Abstract

Computerized constructability analysis, using knowledge-based tools, is the key to effective construction process automation. However, the development of such tools requires a prior acquisition of constructability knowledge. In this paper, results of a feasibility study of automated constructability knowledge acquisition are reported. In the conducted research, constructability of a beam in a reinforced-concrete frame has been investigated. For this problem, a knowledge representation space has been developed, relevant constructability data has been acquired from industry, and a collection of examples has been prepared. In this collection, each example represents a structural design concept evaluated from the point of view of its constructability. The collection of examples has been used by a learning system to acquire from them constructability knowledge in the form of decision rules. The experience gained while conducting the automated knowledge acquisition process has been used to develop initial methodological conclusions regarding the use of learning systems in constructability analysis and to determine the future research directions.