System Dynamics Modeling: A Prototype Technical-Economic Analyzation Tool for Supporting Sustainable Development in Operational Metal Mines

Abstract

Technical-economic analyzation is critical to increasing a mine's economic benefits and saving mineral resources for its sustainable development. However, since the mining system has many technical-economic indicators that are connected and that respond to each other, it is not easy to determine mining production and operation performance when an indicator changes or when multiple indicators change. Thus, the complicated system of operational metal mining cannot be easily solved in a general way. In this paper, system dynamics (SD), an alternative approach that can qualitatively and quantitatively assess mining production and operation from a system analysis perspective, is employed. Taking the Sanshandao gold mine in China as the industrial research context, we built an SD model based on an integrated stock and flow diagram, which is derived from the identification of technical-economic parameters and the system conceptualization of causal loop diagrams, including four subsystems of geology, mining production, mineral processing, and financial. After establishing the equations and testing the model based on historical data, the SD model simulated with the PLE 6.3 software can be used as a decision support tool to calculate the simulation results in many scenarios. Monte Carlo simulation is also introduced to consider uncertainties in the assessment. In the future, development of the prototype SD model will continue, and it will be verified by many more case studies to be a useful alternative tool for decision-making to improve the actual processes and to support the sustainable development of metal mine production and operation.INDEX TERMS Modeling, sustainable development, mining industry, operational level, and system dynamics.

ESG Investment Scale Allocation of China’s Power Grid Company Using System Dynamics Simulation Modeling

“…Based on the causal logic relationship between various factors, SD can quantify abstract and general systems concretely and is often used to solve nonlinear and complex dynamic system problems [ 17 ]. Thus far, SD has been applied in many fields [ 18 , 19 , 20 , 21 ]. Wen and Bai (2017) built an SD model to simulate the impact of different strategies on urban traffic carbon emissions [ 18 ].…”

“…Nassery et al (2017) established an SD model for water management in semiarid areas [ 19 ]. Xiu et al (2019) applied SD to support the production and operation decisions of metal mines [ 20 ]. Zhang (2022) applied SD to explore the causes of enterprise financial risk and the conduction path of risk sources [ 21 ].…”

Hybrid Decision Models of Leasing Business for Thailand Using Neural Network

“…The result showed that SD can be applied to make better decisions by indicating that hybrid scenarios are in reality not preferable. Research [40] was conducted to seek sustainable ways to utilize low-grade metal resources through technical-economic systems analysis and to ensure both technical feasibility and economic justification for the Sanshandao gold mine in China. The result showed that it is possible for the Sanshandao gold mine to enlarge its throughput to exploit and utilize lower grade mineral resources and, thus, to improve the efficiency of resource utilization and to support sustainable development under the premise of guaranteeing the realization of the production and operation targets.…”