We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for alloca...We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.展开更多
文摘We present a novel system productivity simulation and optimization modeling framework in which equipment availability is a variable in the expected productivity function of the system. The framework is used for allocating trucks by route according to their operating performances in a truck-shovel system of an open-pit mine, so as to maximize the overall productivity of the fleet. We implement the framework in an originally designed and specifically developed simulator-optimizer software tool. We make an application on a real open-pit mine case study taking into account the stochasticity of the equipment behavior and environment. The total system production values obtained with and without considering the equipment reliability, availability and maintainability (RAM) characteristics are compared. We show that by taking into account the truck and shovel RAM aspects, we can maximize the total production of the system and obtain specific information on the production availability and productivity of its components.
