Halaweh, M M (2012) System management of construction projects based on industrial engineering prespective with impact on net profit. PhD thesis, State University of New York at Binghamton, USA.
Abstract
According to the economics concepts and principles, the construction projects represent the nucleus of civilizations. The construction projects play a big role to achieve development in economics; the major target of system management of construction projects is to determine the factors which affect negatively on the primary goal which represents Net Profit. The factors were determined by using industrial engineering principles and concepts, these factors are Variation Orders (VO), Additional Works (AW), Mobilization works (M) and Changing Drawings and Quantities (D&Q), these factors are common problems in construction industry and negatively affect the primary goal (Net Profit). Creating the regression model by using design of experiments (DOE) principles to predict the net profit as a primary target in construction industry, this model can be used to optimize the factors for increasing the value of Net Profit. Forecast all factors to improve the performance in construction industry to deal with these factors according to the quality control tools and methods to improve the performance and avoid risk factors. Determine the approach of system management in construction industry according to the cost, time and quality to increase the Net Profit and to achieve the customer satisfaction (owners, consultants and users). In this research the Artificial Neural Network (ANN) was used in order to model complex relationship between the output (primary target) and the inputs which represent the factors that influence the Net Profit.
| Item Type: | Thesis (Doctoral) |
|---|---|
| Thesis advisor: | Lu, S S |
| Uncontrolled Keywords: | artificial neural network; neural network; quality control; regression model |
| Index terms: | owner, regression model, construction industry, quality control, risk factor, customer satisfaction, neural network, drawing, profit, artificial neural network, design of experiment, construction project, variation |
| Subjects: | production management, environmental hazards, economic analysis, contractual condition, service delivery, industry analysis, statistical analysis, sociology, artificial intelligence, project delivery, modelling and simulation, technical documentation |
| Topics: | Digital Applications, Design Practice, Contract Administration, Research Practice, Business Strategy, Stakeholder Management, Quality Management, Project Management, Sustainability |
| 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