面向生产管控的多源数据处理技术

Multi-Source Data Processing Technology for Production Control

为了解决流程型生产车间数据种类多、数据质量参差不齐影响生产管控的问题,提出了面向多源数据的数据分类处理技术,采用数据分类与滑动窗口相结合的方式进行数据处理.首先,根据生产数据特点建立数据模型,然后进行数据分类.主要分为状态数据、开关数据、逻辑数据3类,不同类型的数据使用不同处理算法;同时采用滑动窗口解决不同任务对数据实时性和完整性要求不同的难点.最后,该数据分类处理模型在实际生产环境投入使用,验证了对生产数据处理的准确性和实时性.结果表明,将处理后的数据应用于生产管控,管控误差率降低至不足1%.

In order to solve the problem that there are multi-source and uneven quality data in process-oriented workshop,which affect production control,the data classification and processing technology for multi-source data is proposed.Data processing is performed using a combination of data classification and sliding windows.First,a data model is established based on the characteristics of the production data,and the data is classified.It is mainly divided into three types:state data,switch data and logical data.Different types of data use different processing algorithms.As the same time,sliding windows are used to solve the difficult that different tasks have different requirements for data real-time and integrity.Finally,the data classification processing model is put into use in the actual production environment,which verifies the accuracy and real-time performance of the production data processing.The results show that by applying the processed data to production control,the control error rate is reduced to less than 1%.