面向云制造作业车间的机器能力界定方法  

Capacity partition method of machines in cloud manufacturing-oriented job shops

作　　者：王军强[1,2] 崔福东[1,2] 张承武[1,2] 孙树栋[1,2] 

机构地区：[1]西北工业大学生产与运作系统性能分析中心,陕西西安710072 [2]西北工业大学现代设计与集成制造技术教育部重点实验室,陕西西安710072

出　　处：《计算机集成制造系统》2014年第9期2146-2163,共18页Computer Integrated Manufacturing Systems

基　　金：国家自然科学基金资助项目(51275421);西北工业大学基础研究基金资助项目(JC20120227);西北工业大学研究生创业种子基金资助项目~~

摘　　要：针对面向云制造作业车间,研究不同扰动情形下机器保护能力的设置以及参与云服务能力的划分问题。揭示了系统有效产出随机器能力增长变化的规律。提出了能力松弛率和可用调度时间的概念,建立了面向云制造作业车间的机器能力界定模型。设定了不同的非瓶颈能力松弛率和扰动水平,通过对非瓶颈能力的分级利用,得到了非瓶颈松弛率对系统性能的影响曲线。基于聚类算法提出了非瓶颈能力界定方法,给出了不同扰动水平下每台非瓶颈机器的生产能力、保护能力和云服务能力,为企业自制与云服务能力划分与利用提供了决策依据。Focusing on cloud manufacturing-oriented job shops, the protective capacity of machines for self-manufac- turing and cloud service capacity of machines for cloud service capacity were studied under different disturbed pro- duction environment. The chang law of throughput of manufacturing system with the increase of machine capacity was analyzed. The concepts of capacity slack rate of activation and available scheduling capacity were presented, and a capacity partition model of machinese in cloud manufacturing-oriented job shops was established. The capacity uti- lization of non-bottlenecks was increased gradually to find a curve showing the relation between non-bottleneck slack rate and production system performance under different production conditions through setting different non-bottle- neck capacity slack rates and disturbance levels. A capacity partition method of non-bottleneck based on clustering algorithm was put forward. The productive capacity, protective capacity and cloud service capacity of each non-bot- tleneck machine under different disturbance were determined, which provided a decision-making basis of capacity partition and utilization for self-manufacturing and cloud manufacturing of enterprises.

关 键 词：约束理论 云制造 作业车间调度 非瓶颈 扰动 能力界定 

分 类 号：TP391.9[自动化与计算机技术—计算机应用技术] TH166[自动化与计算机技术—计算机科学与技术]