基于物联网的仓储管控一体化系统实现路径
|
摘要
我国的仓库总量很大,但是管理水平和技术水平参差不齐,绝大部分仓库的资源利用率低,信息化、自动化程度不高,安全性差,先进的仓储管理模式应用很少。发展智能仓储是提高仓储作业能力和服务质量、降低仓储风险的有效方法。发展和建设智能仓储系统要应用管控一体化的思想和架构,在信息充分共享的基础上,将仓储环境监控与管理、设备控制与管理、作业调度与管理整合在一起,形成以实时信息采集与处理为核心的智能自动执行系统。目前工业信息化和自动化技术足以支持全自动化仓储系统的工程应用,应尽快制定符合仓储自动化、信息化特点和要求的行业标准和技术规范。构建仓储管控一体化系统,在设备研究制造、控制设备选型以及系统集成等方面遵循广泛使用的工业标准,基于物联网技术全面实施数据共享和统一管理,通过实施多条件约束的作业调度策略,保障仓储作业协调、安全、高效进行,进而提升仓储系统的整体运作效率和安全性。
The total amount of warehouses is huge in China,and the levels of management and technology are uneven,which shows low resource utilization,low level of informatization and automation,poor security,and less application of advanced storage management pattern in most of the warehouses. Developing intelligent warehousing is an effective way to improve warehousing capacity and service quality,and reduce related risks. Developing and constructing intelligent warehousing needs the framework of integrated management and control based on perfect information sharing,the storage environment monitoring and management,equipment control and management,job scheduling and management,and the intelligent automatic implementation system taking real time information collection and handling as the core. The existing industry informatization and automation technologies are sufficient to support the application of automated storage systems. As building the integrated system,the IOT is used to do job scheduling,data sharing and a real-time system,which can improve the efficiency and safety.
The total amount of warehouses is huge in China,and the levels of management and technology are uneven,which shows low resource utilization,low level of informatization and automation,poor security,and less application of advanced storage management pattern in most of the warehouses. Developing intelligent warehousing is an effective way to improve warehousing capacity and service quality,and reduce related risks. Developing and constructing intelligent warehousing needs the framework of integrated management and control based on perfect information sharing,the storage environment monitoring and management,equipment control and management,job scheduling and management,and the intelligent automatic implementation system taking real time information collection and handling as the core. The existing industry informatization and automation technologies are sufficient to support the application of automated storage systems. As building the integrated system,the IOT is used to do job scheduling,data sharing and a real-time system,which can improve the efficiency and safety.
引文
[1]张可薇,王亚成,范红岩,刘军.智能仓储研究与应用进展[J].中国市场,2017(8):166-169.
[2]申悦,王亚成,刘军.仓储环境监控研究与应用进展[J].中国物流与采购,2017(18):72-73.
[3]CHOY K L,et al.A food monitoring system for preventing product deterioration[J].International journal of food safety,nutrition and public health,2014,5(1):54-79.
[4]任晓莉.基于物联网的仓储环境监控系统[J].计算机与数字工程,2017(4):783-787.
[5]刘军.基于无线传感器网络的仓储监控管理系统关键技术研究[J].中国流通经济,2010(7):43-78.
[6]卢尧,任晓明,吴勇志,李继先.智能仓储控制系统的设计与实现[J].自动化仪表,2017,38(2):28-30.
[7]SON D W,CHANG Y S,CHOI H C,KIM W R,HIGUERA A G.A study of building a new warehouse control system architecture[J].International journal of advanced logistics,2015,4(3):145-158.
[8]LAM H Y,CHOYN K L,HO STEPHEN G T S,CHENG W Y,LEE C K M.A knowledge-based logistics operations planning system for mitigating risk in warehouse order fulfillment[J].International journal of production economics,2015,170:763-779.
[9]胡祥培,孙丽君,王征.基于物联网的在线智能调度方法的相关思考[J].管理科学,2015,28(2):137-144.
[10]刘军,阎芳,杨玺.物联网与物流管控一体化[M].北京:中国财富出版社,2017:508-511.
[11]王亚臣,申悦,刘军.基于物联网的仓储管控一体化系统设计策略[J].物流技术,2017,36(5):143-146.
[12]王程安,刘军,申悦.仓储综合监控系统研究[J].物流技术,2015,34(8):239-243.
[13]徐杰,贾利民,秦勇,王艳辉,王卓.城市轨道交通综合监控平台系统集成的研究[J].铁道学报,2007,29(3):107-113.
[14]ERICKSON P,CLINE M,TIRPANKAR N,HENDERSON T.Gaussian processes for multi-sensor environmental monitoring[C]//2015 IEEE International Conference on Multisensor Fusion and lntegration for Intelligent Systems(MFI),San Diego:IEEE,2015:208-213.
[15]LI H T,MU X Y,YANG Y N,Andrew J Mason.Low power multimode electrochemical gas sensor array system for eearable healthand safety monitoring[J].IEEE sensors journal,2014,14(10):3 391-3 399.
[16]苏卫星,朱云龙,刘芳,马连博.基于改进模糊聚类的同构多传感器在线数据融合方法[J].信息与控制,2015,44(5):557-563.
[17]蒋荟.基于信息融合的铁路行车安全监控体系及关键技术研究[D].北京:中国铁道科学研究院,2013.
[18]朱东升,张浩,张昆,崔伟.基于综合监控的设备状态修方案研究[J].计算机测量与控制,2017,25(6):64-67.
[19]胡昌华,施权,司小胜,张正新.数据驱动的寿命预测和健康管理技术研究进展[J].信息与控制,2017,46(1):72-82.
[2]申悦,王亚成,刘军.仓储环境监控研究与应用进展[J].中国物流与采购,2017(18):72-73.
[3]CHOY K L,et al.A food monitoring system for preventing product deterioration[J].International journal of food safety,nutrition and public health,2014,5(1):54-79.
[4]任晓莉.基于物联网的仓储环境监控系统[J].计算机与数字工程,2017(4):783-787.
[5]刘军.基于无线传感器网络的仓储监控管理系统关键技术研究[J].中国流通经济,2010(7):43-78.
[6]卢尧,任晓明,吴勇志,李继先.智能仓储控制系统的设计与实现[J].自动化仪表,2017,38(2):28-30.
[7]SON D W,CHANG Y S,CHOI H C,KIM W R,HIGUERA A G.A study of building a new warehouse control system architecture[J].International journal of advanced logistics,2015,4(3):145-158.
[8]LAM H Y,CHOYN K L,HO STEPHEN G T S,CHENG W Y,LEE C K M.A knowledge-based logistics operations planning system for mitigating risk in warehouse order fulfillment[J].International journal of production economics,2015,170:763-779.
[9]胡祥培,孙丽君,王征.基于物联网的在线智能调度方法的相关思考[J].管理科学,2015,28(2):137-144.
[10]刘军,阎芳,杨玺.物联网与物流管控一体化[M].北京:中国财富出版社,2017:508-511.
[11]王亚臣,申悦,刘军.基于物联网的仓储管控一体化系统设计策略[J].物流技术,2017,36(5):143-146.
[12]王程安,刘军,申悦.仓储综合监控系统研究[J].物流技术,2015,34(8):239-243.
[13]徐杰,贾利民,秦勇,王艳辉,王卓.城市轨道交通综合监控平台系统集成的研究[J].铁道学报,2007,29(3):107-113.
[14]ERICKSON P,CLINE M,TIRPANKAR N,HENDERSON T.Gaussian processes for multi-sensor environmental monitoring[C]//2015 IEEE International Conference on Multisensor Fusion and lntegration for Intelligent Systems(MFI),San Diego:IEEE,2015:208-213.
[15]LI H T,MU X Y,YANG Y N,Andrew J Mason.Low power multimode electrochemical gas sensor array system for eearable healthand safety monitoring[J].IEEE sensors journal,2014,14(10):3 391-3 399.
[16]苏卫星,朱云龙,刘芳,马连博.基于改进模糊聚类的同构多传感器在线数据融合方法[J].信息与控制,2015,44(5):557-563.
[17]蒋荟.基于信息融合的铁路行车安全监控体系及关键技术研究[D].北京:中国铁道科学研究院,2013.
[18]朱东升,张浩,张昆,崔伟.基于综合监控的设备状态修方案研究[J].计算机测量与控制,2017,25(6):64-67.
[19]胡昌华,施权,司小胜,张正新.数据驱动的寿命预测和健康管理技术研究进展[J].信息与控制,2017,46(1):72-82.