A Machine Learning-Based application that predicts the remaining useful life or expected time until the next failure in the current repair cycle. For example, a part has a predicted remaining useful life of 5 days. This implies that 5 days from the current date, the part will most likely fail. Knowing this information can help you place an order or schedule maintenance before the part fails.
Use these
ETLs to get output from Zeppelin Notebooks, transform data if required, and save results in the Servigistics schema.
Input
N/A
Output
◦ QO_ETL_PAI_ML_RUL_TempOutput_ORACLE
◦ QO_ETL_PAI_ML_RUL_TempOutput_MSSQL
◦ QO_ETL_PAI_ML_RUL_Output_ORACLE
◦ QO_ETL_PAI_ML_RUL_Output_MSSQL