




Management requires the execution of algorithm related data for testing in software, including built-in algorithms and customized operation optimization algorithms. Operators have built-in algorithms for steady-state detection, case generation, operation optimization, intelligent warning, and other related algorithms.


Configure expressions, indicator granularity, and statistical cycles, perform secondary calculations on underlying data using specified methods, obtain evaluation indicators such as process, quality, or energy consumption, store and manage them, including query display, addition, editing, import, deletion, and batch deletion. At the same time, classifying indicators according to environmental variables, controlled variables, and controlled variables provides algorithmic support.


Real time comparison of the deviation between the current optimized variable target value and the actual value, and the ability to track the deviation between the replay operation at any time period and the case library, as well as the deviation of the operation target caused by this parameter deviation. Real time calculation of optimization variable target value execution rate. Focus on optimizing the configuration of variables and indicators.


For device level intelligent warning, the intelligent warning algorithm based on big data technology sorts and displays warning information according to warning priority, and provides the function of querying the occurrence of warnings and alarm records. Configure basic warning algorithms and save warning model case libraries.