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针对产能损失的生产线瓶颈辨识与转移预测 被引量:1

Production line bottleneck identification and transfer prediction for capacity loss
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摘要 在制造业生产过程中,瓶颈工序并不是一直保持不变的,当各种扰动因素出现时,瓶颈工序可能会随着生产的推进不断发生变化。针对扰动因素引起的工序产能损失导致生产瓶颈发生转移的现象展开研究,用惩罚成本识别了生产线的初始瓶颈。研究了4种主要产能扰动因素耦合对工序可用产能时间造成的损失,并用BP神经网络预测出各工序可用产能时间的损失大小,建立工序产能可用率预测模型,引入新的瓶颈转移指标计算方式间接建立瓶颈转移预测模型。最后采用瓶颈辨识与转移预测流程进行案例分析,并验证了瓶颈转移预测模型的可靠度。 In the manufacturing process,the bottleneck process does not always remain the same.When various disturbance factors appear,the bottleneck process may continue to change with the advancement of production.Research on the phenomenon that the production bottleneck is transferred due to the loss of process capacity caused by disturbance factors was carried out,the initial bottleneck of the production line was identified by the penalty cost method.Considering the loss of the available production time of the process caused by the coupling of the four main capacity disturbance factors,and the BP neural network was used to predict the loss of the available production time of each process,the process capacity availability prediction model was established,and a new bottleneck transfer index calculation method which indirectly established a bottleneck transfer prediction model was introduced.Finally,a case analysis was carried out with the whole set of bottleneck identification and transfer prediction process,and the reliability of the bottleneck transfer prediction model was verified.
作者 陈磊 王相柠 娄恒权 胡雨欣 贾记萌 CHEN Lei;WANG Xiangning;LOU Hengquan;HU Yuxin;JIA Jimeng(School of Energy&Mining,China University of Mining and Technology(Beijing),Beijing 100083,China;Zhengzhou Coal Mine Machinery Group Co.,Ltd.,Zhengzhou 450016,China;Business School,National University of Belarus,Minsk 220030,Belarus;Hebei Hongmao Daily Appliance Technology Co.,Ltd.,Handan 056200,China)
出处 《现代制造工程》 CSCD 北大核心 2022年第4期21-28,共8页 Modern Manufacturing Engineering
关键词 产能损失 惩罚成本 BP神经网络 产能可用率 瓶颈转移预测 capacity loss penalty cost BP neural network capacity availability bottleneck transfer prediction
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  • 1罗兵,黄万杰,杨帅.基于Tan-Sigmoid函数参数调整的BP神经网络改进算法[J].重庆大学学报(自然科学版),2006,29(1):150-153. 被引量:8
  • 2施文武,严洪森.知识化制造系统中生产瓶颈的分析方法[J].计算机集成制造系统,2006,12(2):271-279. 被引量:13
  • 3张菊秀,全书海,王永生.多模态智能控制在磁悬浮轴承系统中的应用[J].武汉理工大学学报(交通科学与工程版),2007,31(2):364-366. 被引量:3
  • 4魏彤,房建成.磁悬浮控制力矩陀螺磁轴承的变工作点线性化自适应控制方法[J].机械工程学报,2007,43(6):110-115. 被引量:21
  • 5Christoph Roser, Masaru Nakano, Minoru Tanaka. Shifting Bottleneck Detection: Software Science Laboratory Toyota Central Research and Development Laboratories Nagakute, Aichi ,480 - 1192. JAPAN
  • 6T. Ramesh Babu. K. S. P. Rao. C, Uma Maheshwaran. Application of TOC embedded ILP for increasing throughput of Production lines [J ] . International Journal of Manufacturing Tech- nology and Management, 2007, 812 - 818.
  • 7ROSER C, NAKANO M, TANAKA M. Shifting Botdeneck Detection [ C ]. Proceedings of the 2002 Winter Simulation Conference, San Diego, Chile,2002.
  • 8FAGET P, ERIKSSON U, HERRMANA F. Appling Discrete Event Simulation and an Automated Bottleneck Analysis as an Aid to Detect Running Production Constraints[ C ]//Proceeding of the 2005 Winter Simulation Conference, Orlando, USA,2005 : 1401 - 1407.
  • 9LI Lin, CHANG Qing,NI Jun,et al. Bottleneck Detection of Manufacturing Systems Using Data Driven Method[C]//Proceedings of the 2007 IEEE International Symposium on Assembly and Manufacturing, Michigan,USA,2007:22 - 25.
  • 10ZHANG Rui, WU Cheng. Bottleneck identification procedures for the Job Shop scheduling problem with applications to genetic algorithms [ J ]. The International Journal of Advanced Manufacturing Technology,2009,42( 11 ).

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