基于机床超低待机状态的流水车间能耗调度

Energy consumption scheduling in flow shop based on ultra-low idle state of numerical control machine tools

为降低流水车间能源消耗,引入一种数控机床的超低待机状态,相比于将数控机床待机状态切换为停机状态的节能研究,可在不停机情况下降低数控机床加工间隔状态的功率,避免数控机床频繁启停.针对流水车间加工状态、待机状态及超低待机状态三元调度问题,提出基于工序平移的混合遗传算法,分别定义了不同的工序邻域移动操作,实现数控机床待机状态向超低待机状态和停机状态的转化,形成主动节能调度策略,提升遗传算法求解考虑超低待机状态的流水车间调度问题的优化能力.实验研究表明,启用超低待机状态能够降低流水车间10%以上的能耗,且基于工序平移的混合遗传算法求解考虑超低待机状态的流水车间调度问题性能优于遗传算法.

In order to reduce the energy consumption of the flow shop,an ultra-low idle state of the numerical control(NC)machine tools is introduced.Compared with the research on converting the idle state into the shutdown state,the ultra-low idle state can reduce the idle power without stopping the machine and avoiding frequent stopping the numerical control machine tools.A hybrid genetic algorithm based on process translation is proposed to solve the ternary scheduling problem in the flow shop considering the processing state,standby state and ultra-low idle state.The hybrid genetic algorithm defines different process neighborhood movement operations,and realizes the transformation of the NC machine tool from the standby state to the ultra-low idle state or off state.The hybrid genetic algorithm forms an active energy saving scheduling strategy and improves the optimization ability of the genetic algorithm to solve the flow shop energy consumption scheduling problem considering the ultra-low idle state.The experimental results show that the ultra-low idle state can effectively reduce energy consumption of the flow shop by 10%.The performance of the hybrid genetic algorithm is better than that of the genetic algorithm in solving flow shop energy saving scheduling problems considering the ultra-low idle state.