School of Mechanical Engineering, Tongji University, Shanghai 201804, China.
Kunming Yunnei Power Co., Ltd., Kunming 650217, China.
Sensors (Basel). 2018 Jul 10;18(7):2224. doi: 10.3390/s18072224.
In complex discrete manufacturing environment, there used to be a poor network and an isolated information island in production line, which led to slow information feedback and low utilization ratio, hindering the construction of enterprise intelligence. To solve these problems, uncertain factors in the production process and demands of sensor network were analyzed; hierarchical topology design method and the deployment strategy of the complexity industrial internet of things were proposed; and a big data analysis model and a system security protection system based on the network were established. The weight of each evaluation index was calculated using analytic hierarchy process, which established the intelligentized evaluation system and model. An actual production scene was also selected to validate the feasibility of the method. A diesel engine production workshop and the enterprise MES were used as an example to establish a network topology. The intelligence level based on both subjective and objective factors were evaluated and analyzed considering both quantitative and qualitative aspects. Analysis results show that the network topology design method and the intelligentize evaluation system were feasible, could improve the intelligence level effectively, and the network framework was expansible.
在复杂离散制造业环境中，过去生产线中存在网络较差且信息孤岛孤立的情况，这导致信息反馈缓慢，利用率低，阻碍了企业智能化的建设。为了解决这些问题，分析了生产过程中的不确定因素和传感器网络的需求；提出了复杂工业物联网的层次拓扑设计方法和部署策略；并建立了基于网络的大数据分析模型和系统安全保护系统。使用层次分析法计算了每个评价指标的权重，建立了智能化评价系统和模型。还选择了一个实际的生产场景来验证该方法的可行性。以柴油机生产车间和企业 MES 为例，建立网络拓扑。从定量和定性两个方面考虑，评估和分析了基于主观和客观因素的智能水平。分析结果表明，该网络拓扑设计方法和智能评价系统是可行的，可以有效提高智能水平，并且网络框架具有可扩展性。
