Abstract
The lack of the expertise and resources, the unavailability of sufficient and complete operations data, and the absence of relevant site information present obstacles to applying combined simulation modeling in practice. Construction modelers are required to make critical decisions in a short turnaround time for planning operations and improving productivity. Thus, a more convenient discrete event simulation-based approach in simulating the production capacity of the continuous plant given limited data availability is desirable and formalized, which essentially discretizes the modeling of continuous elements in a predominantly discrete system without loss of significance or accuracy. As such, a direct application of a discrete simulation method intended for construction applications will offer a straightforward, sufficient solution to model the whole system. A concrete pumping case is used to illustrate the proposed approach. The effectiveness of the proposed approach is further demonstrated to tackle a real-world challenge: modeling iron ore mining operations to achieve efficiency and enhance productivity. Especially, the formula proposed is applied to simplify the modeling of the iron ore processing plant with magnetic separation drums, which constitutes the major plant used for extracting iron sand from the slurry of iron ore. A discrete event simulation model was rapidly developed for the complex mining system and the insight derived from simulation experiments assisted a mining company in (1) configuring the processes of raw sand excavation, iron sand magnetic separation and iron sand shipment at a seaport, (2) optimizing resource allocation and utilization. In conclusion, the proposed approach adds to the usefulness and flexibility of a discrete simulation methodology in modeling complicated construction systems.
Original language | English |
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Article number | 04014032 |
Journal | Journal of Construction Engineering and Management |
Volume | 140 |
Issue number | 8 |
DOIs | |
Publication status | Published - 1 Aug 2014 |
Keywords
- Construction management
- Decision support
- Mining
- Quantitative analysis
- Quantitative methods
- Simulation
ASJC Scopus subject areas
- Civil and Structural Engineering
- Building and Construction
- Industrial relations
- Strategy and Management