SYSTEM AND METHOD FOR INTELLIGENT SCHEDULING OF MANUFACTURING JOBS

The present invention discloses a system for scheduling jobs within a manufacturing environment, integrating a plurality of sensors to capture operational parameters. A processing unit, linked to the plurality of sensors, analyzes datasets to determine the operational parameters. A machine learning module coupled to the processing unit, enhances a scheduling algorithm using the operational parameters. This machine learning module includes a first predictor for estimating job processing times and forecasting operating conditions based on these parameters. A formulator adjusts the scheduling algorithm using the forecasted operating conditions for distinct time intervals. Additionally, a second predictor forecasts subsequent operating conditions based on the modified scheduling algorithm and initial forecasts. The system optimizes job scheduling, enhancing efficiency and productivity within the manufacturing environment.