Shahtaheri, M; Nasir, H and Haas, C T (2015) Setting baseline rates for on-site work categories in the construction industry. Journal of Construction Engineering and Management, 141(5): 04014097, ISSN 0733-9364
Abstract
Labor performance drives construction project performance. Labor performance can be improved by increasing the direct-work rate, which is the time spent by workers on installing materials and equipment. However, setting baseline rates for direct-work rate and determining expectation levels during the construction phase requires further investigation. The focus of the research reported in this paper is to establish a methodology for setting a desirable and realistic baseline rate based on activity analysis, primarily for industrial projects. First, an adaptive neurofuzzy inference system (ANFIS)-based method was developed as a means of estimating baseline rates based on existing knowledge. The method was trained using 272 data points. Its flexibility and functionality validate its usefulness; however, three additional methods of defining baseline rates were also developed based on simpler concepts and demonstrated with data points available from 14 projects, and the experience associated with these projects. As a result, comprehensive methods and a valuable initial dataset for industrial construction projects to better establish baseline rates for direct work and supporting activities were contributed. This should help project managers to estimate appropriate baselines and set realistic goals for direct-work rate which ultimately may lead to improvement of labor performance.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | activity analysis; adaptive neurofuzzy interface system; artificial intelligence; baseline rate; construction automation; continuous improvement; direct-work rate; labor performance; productivity; project planning and design |
| Index terms: | site work, artificial intelligence, estimate, industrial construction, construction industry, automation, construction phase, investigation, continuous improvement, productivity, project manager, estimating, project planning, dataset, methodology, construction project, functionality |
| Subjects: | research methods, management, performance measurement, production management, automation and robotics, building construction, data management, industry analysis, data collection methods, profession, control systems, design features, financial and cost management, project delivery, site logistics, artificial intelligence |
| Topics: | Roles and Professions, Research Practice, Project Management, Engineering Principles, Business Strategy, Cost Management, Site Management, Quality Management, Design Practice, Digital Applications |
| Descriptive scope: | 4 PCTA |
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