Jordan Srour, F; Kiomjian, D and Srour, I M (2018) Automating the use of learning curve models in construction task duration estimates. Journal of Construction Engineering and Management, 144(7): 04018055, ISSN 0733-9364
Abstract
Standard scheduling tools for construction projects with repetitive tasks assume that labor productivity remains constant throughout the project lifetime. None of these tools accommodate the dynamics of learning throughout the project. This paper introduces a tool that uses nonlinear optimization to integrate learning curve concepts into task duration estimates for construction project scheduling. The tool, featuring a graphical user interface, mines past data to select the most appropriate learning model from a suite of existing models. Testing the tool on data obtained from five published case studies with varying sizes and locations suggests that the tool offers accurate estimates for task completion times, even when the size or quality of the input data is minimal. Directives for use of this tool and an estimate of potential savings in practice are also provided through an example based on real-world data. These savings amounted to 28% of the overall labor costs within the real-world project. The contribution of this paper is a tool to estimate construction task durations in such a way that learning is incorporated. The tool uses nonlinear optimization to select and calibrate the best learning model making the tool of value to practitioners working across a variety of linear and nonlinear repetitive projects in a range of geographical regions.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | automated scheduling; construction scheduling; learning curves |
| Index terms: | completion time, practitioner, construction project, user interface, scheduling, estimate, duration, testing, labour productivity, labour cost, dynamics, savings, case study, construction scheduling, repetitive project |
| Subjects: | professional practice, financial and cost management, economic analysis, operations research, practitioner, data collection methods, human-computer interaction, cost management, systems engineering, project controls, production management, management |
| Topics: | Roles and Professions, Procurement, Cost Management, Business Strategy, Project Management, Research Practice, Engineering Principles, Site Management, Time Control |
| 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