Process versus data oriented techniques in pile construction productivity assessment

Zayed, T M and Halpin, D W (2004) Process versus data oriented techniques in pile construction productivity assessment. Journal of Construction Engineering and Management, 130(4), pp. 490-499. ISSN 0733-9364

Abstract

A large number of problems faces the installation of pile (drilled shaft) foundations: unseen subsurface obstacles, lack of contractor experience, site planning, etc. These problems make it difficult for the estimator to assess the pile construction productivity and cost. Several techniques might be good candidates for this assessment problem. A fundamental question arises: which technique is the most appropriate to solve this assessment problem? This study focuses on answering this fundamental research question. Data were collected through designed questionnaires, site interviews, and telephone calls to experts in different construction companies. Four different techniques were listed as candidates to solve this problem: deterministic, simulation, multiple regression, and artificial neural network (ANN). They were categorized into two groups: process oriented techniques, deterministic and simulation; and data oriented techniques (DOT), regression and ANN. All techniques were used to assess productivity and cost of pile construction. Their results were compared to determine the closest assessment to real world practice. Research results show that the DOT techniques were the most appropriate whereas they had the lowest deviation from real world practice.

Item Type: Article
Uncontrolled Keywords: data analysis; neural networks; piles; predictions; productivity; simulation; statistical analysis
Index terms: questionnaire, neural network, artificial neural network, foundations, productivity, construction company, data analysis, estimator, face, construction productivity, deviation, statistical analysis, multiple-regression, interview
Subjects: financial and cost management, organization, operations management, artificial intelligence, modelling and simulation, profession, statistical analysis, psychology, data science, structural engineering, management, data collection methods, data analysis and analytics
Topics: Engineering Principles, Cost Management, Organizational Design, Business Strategy, Research Practice, Project Management, Roles and Professions, Digital Applications
Descriptive scope: 4 PCEA

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