Su, Y-Y (2010) Construction crew productivity monitoring supported by location awareness technologies. PhD thesis, University of Illinois at Urbana-Champaign, USA.
Abstract
Construction productivity, which is measured by output per unit of resource input, plays a key role in the success of a construction project. High productivity leads to lower unit cost to carry out a task or operation. Analyzing construction productivity, however, is a challenging task because of the nature of construction field conditions which contain complex resource flows that lack the organized production lines of a manufacturing facility in a controlled and weather protected environment. To study a construction operation, construction engineers typically spend days or weeks just to collect the data needed to conduct basic analysis. Often when data become available, the site condition has changed and the improvement ideas obtained from productivity analysis are already obsolete. Timely productivity monitoring can provide construction engineers with insightful information so that corrective measures can be applied immediately to control on-going construction. In the field of data acquisition, the development of technologies for location awareness provides significant potential for improving the manual processes of collecting construction field data and, as a result, construction decisions can be made in a timely manner which can improve productivity, saving time and money for a construction project. Due to the complexity of construction operations in the field, location awareness technology alone cannot solve the field productivity puzzle readily. A critical breakthrough of transferring the location and time data into meaningful productivity information is needed which requires the investigation of resource interdependencies within a construction operation. This research goes beyond applying location awareness technology to collect construction field data and focuses on integrating the quantatitive positioning and time data with operational reasoning rules to automatically generate qualitative operation information to support timely productivity analysis and decision making. The results of the research include a rule-based position-to-operation (P2O) model and its resulting time-lapse resource utilization.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Liu, L Y |
| Uncontrolled Keywords: | complexity; reasoning; construction project; crew productivity; decision making; manufacturing; monitoring; productivity; weather |
| Index terms: | construction project, decision-making, weather, complexity, unit cost, resource flow, reasoning, investigation, monitoring, data acquisition, construction productivity, crew productivity, resource utilization, construction operation, engineer, productivity |
| Subjects: | systems engineering, cognitive psychology, decision analysis, production management, management, financial and cost management, site logistics, resource management, construction operations, operations management, control systems, air quality, data collection methods, profession |
| Topics: | Site Management, Roles and Professions, Research Practice, Cost Management, Business Strategy, Sustainability, Risk Management, Project Management, Engineering Principles |
| 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