As any system runs over time, issues such as the accumulation of redundant data inevitably arise. Any system—especially large-scale systems or core enterprise systems—needs to establish a mechanism for regular data backup and cleaning to ensure sustained efficient operation. In reality, however, it is not always possible to achieve this ideal; we can systematically plan to address and clean up redundant data.

APS System does not exist independently within the overall enterprise business system architecture; it needs to interface with multiple systems such as ERP, MES, and LES. At this point, the data accuracy and account precision of each system can indeed affect the rapid operation of the APS system. While ensuring data validity, when obtaining data from other systems, the APS system can filter the data. Additionally, during computation, parameters such as data intervals can be set to exclude redundant data or historical data. Of course, the best approach is to fundamentally address the issue of data validity.

In the future, to improve data accuracy and timeliness, it is recommended that smart factories widely adopt IoT devices and systems. This will not only enhance data timeliness and accuracy but also reduce manual input and operations.