Yu, W-d (1996) A neuro-fuzzy knowledge-based multi-criterion decision model for constructability analysis and improvement of construction technologies. PhD thesis, Purdue University, USA.
Abstract
Selecting the most appropriate construction technology for a given project scenario is one of the most effective approaches for constructability improvement. Experienced construction engineers and managers are frequently involved in applying their constructability knowledge to technology selection during the early phase of a project's lifecycle in order to achieve cost effective construction. Due to natural attrition and other causes, the constructability knowledge of experienced personnel is diminishing in many construction firms. Moreover, because of the complex nature of construction operations, it is extremely difficult for construction experts to express their constructability knowledge while considering many variable attributes simultaneously. A methodology for automated constructability analysis and knowledge acquisition has yet to be developed. Without such a methodology, timely selection of the most appropriate construction technology and accumulation of knowledge for technology improvement will remain difficult. This research is the first work on both quantifying the conventional descriptive definition of constructability and on exploring the learning ability of neuro-fuzzy networks for automatic constructability knowledge acquisition. The developed methodology differentiates itself from the traditional constructability analysis and improvement approaches in two aspects: 1) the quantitative definition of constructability is adopted instead of the traditional descriptive definition, so that constructability can be measured, estimated, and improved; (2) the self-learning techniques for constructability knowledge acquisition are adopted instead of the traditional manual human-input approaches, so that the automation of constructability knowledge acquisition and accumulation becomes possible. With this generic methodology, construction firms can develop their own decision support systems to analyze and solve specific constructability problems according to their specialized fields. The result of this research is a tool for continuous constructability improvement of construction projects and technologies. A prototype computer implementation of the proposed methodology named COnstrUction techNology SELectOR (COUNSELOR) is developed for constructability analysis and improvement of concrete formwork technologies. The COUNSELOR system has demonstrated its abilities to quantify constructability according to the constructor's characteristics, detect potential constructability problems before the construction phase, and propose solutions for constructability improvement. The result of the research indicates a promising solution for barriers encountered in the implementation of conventional constructability approaches.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Skibniewski, M J |
| Uncontrolled Keywords: | automation; concrete formwork; constructability; construction firms; construction operations; construction phase; construction technology; decision support; formwork; learning; lifecycle; personnel |
| Index terms: | construction phase, automation, constructability, implementation, construction technology, lifecycle, knowledge acquisition, formwork, engineer, construction operation, concrete formwork, construction project, methodology, prototype, construction firm, personnel, manager, decision support |
| Subjects: | practitioner, digital engineering, organization, contractual arrangements, construction operations, construction methods, production management, automation and robotics, research methods, building construction, profession, project delivery, modelling and simulation, construction integration, management, student development, decision analysis |
| Topics: | Research Practice, Business Strategy, Construction Technology, Roles and Professions, Human Resources, Digital Applications, Design Practice, Site Management, Engineering Principles, Project Management, Procurement, Risk Management, Education |
| Descriptive scope: | 3 PCT |
N.B. Descriptive scope is a count of how many of the five facets of empirical research are indicated by the words used in title, abstract and keywords. It is not intended as a judgement on the research; merely a count of the kind of word we would expect to indicate Phenomenon, Concepts, Theoretical framing, Empirical techniques, Analytical techniques. If all five are present, then a code of “5 PCTEA” will indicate this. If you feel the coding for this record is questionable, we welcome discussion around the terms we matched or the way we categorized them. The facet you would expect may not be coded, or a facet may be coded inappropriately. This can also bear on a larger question, of which facets should be treated as defining in construction management research. Please get in touch, and we will look at it. More details here