摘要
针对Job Shop作业管理层面的瓶颈识别,改变传统将瓶颈识别独立于调度优化方案的做法,先进行瓶颈充分利用再进行瓶颈系统辨识,不仅保证了瓶颈的有效识别,而且保证了瓶颈的充分利用。笔者给出了工序级瓶颈识别指标,提出了瓶颈分级识别策略,采用遗传算法和优化仿真结合的方法实现瓶颈的充分利用,其中,利用遗传算法优化零件的投料顺序,采用Plant-Simulation建立模拟仿真模型,设置设备故障率、平均故障修复时间、缓冲容量等实际扰动,经过大量的生产过程仿真,基于瓶颈出现率进行瓶颈识别,并输出优化调度方案。算例验证表明了瓶颈识别方法的有效性。
For the machine bottleneck identification problem in job shop operation management,a new machine bottleneck identification method is presented for treating simultaneously bottleneck identification and scheduling optimization solution in order to guarantee the full utilization of the bottleneck machine and the identification validity.First,the indicators for bottleneck identification of job shop operation management are presented.Then,the hierarchical bottleneck identification strategy is given,which consists of full utilization and subsequent identification of bottleneck.Genetic algorithm （GA） is selected to optimize the parts order,and then the job shop manufacturing process is simulated under the Plant-Simulation software environment,in which the parameters such as the machine capacity,failure rate and mean time to repair and the buffer capacity are set.After simulating repeatedly the procedure,the bottleneck machine was identified based on the indicator of bottleneck appearance rate while the scheduling optimization solution was exported.Simulation results show that the presented bottleneck identification method for job shop operation management is valid.
出处
《机械科学与技术》
CSCD
北大核心
2010年第12期1697-1702,共6页
Mechanical Science and Technology for Aerospace Engineering
基金
国家自然科学基金项目(50705077)
国家863/CIMS计划项目(2007AA04Z187)
陕西省自然科学基础研究计划项目(2009JQ9002)资助
关键词
瓶颈识别
作业调度
仿真
bottleneck identification
job shop scheduling
simulation
