Akhavian, R and Behzadan, A H (2013) Knowledge-based simulation modeling of construction fleet operations using multimodal-process data mining. Journal of Construction Engineering and Management, 139(11): 4013021, ISSN 0733-9364
Abstract
In order to develop a realistic simulation model, it is critical to provide the model with factual input data based on the interactions and events that take place between real entities. However, the existing trend in simulation of construction fleet activities is based on estimating input parameters such as activity durations using expert judgments and assumptions. Not only may such estimations not be precise, but project dynamics can influence model parameters beyond expectation. Therefore, the simulation model may not be a proper and reliable representation of the real engineering system. In order to alleviate these issues and improve the current practice of construction simulation, a thorough approach is needed that enables the integration of field data into simulation modeling and systematic refinement of the resulting models. This paper describes the latest efforts by authors to design and test a novel methodology for multimodal-process data capturing, fusion, and mining that provides a solid basis for automated generation and refinement of simulation models that realistically represent construction fleet operations. Different modes of operational data are collected and fused to facilitate the discovery of operational knowledge required to create realistic simulation models. The developed algorithms are validated using laboratory scale experiments and analytical results are also provided. The main contribution of this research to the body of knowledge is that it lays the foundation to systematically investigate whether it is possible to robustly discover computer-interpretable knowledge patterns from heterogeneous field data in order to create or refine realistic simulation models from complex, unstructured, and evolving operations such as heavy construction and infrastructure projects.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | construction; data driven; data fusion; data mining; earthmoving; heavy equipment; knowledge discovery; real time; simulation |
| Index terms: | estimating, body of knowledge, integration, methodology, experiment, construction simulation, laboratory, infrastructure project, interaction, heavy construction, earthmoving, duration, simulation modelling, data fusion, dynamics, mining, real time, estimation, judgment, data mining |
| Subjects: | research methods, research management, geotechnical engineering, project controls, organizational analysis, systems engineering, behavioral psychology, infrastructure and transport systems, data collection methods, dispute resolution, modelling and simulation, financial and cost management, analytical methods, construction operations, knowledge management, data science |
| Topics: | Digital Applications, Legal Issues, Time Control, Site Management, Organizational Design, Engineering Principles, Information Management, Research Practice, Cost Management |
| Descriptive scope: | 5 PCTEA |
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