Influence of Sensor Accuracy on Planned Process Times for Lead-Acid Battery Production

To achieve the 1.5-degree climate goal of the Paris Agreement, energy consumption in production must be reduced, particularly for energy-intensive products like lead-acid batteries. In this study, we develop a simulation model for a lead-acid battery real-world case company and integrate the effect of sensor data during the heat treatment process, i.e., maturation and drying of lead plates. The sensor used in this context provides a range for the stochastic minimum required energy at the maturation and drying. Leveraging this data, we develop a heuristic approach to optimize the planned process times for both steps. Moreover, the effect of sensor accuracy, which determines the number of provided ranges, is observed. Simulation results reveal a significant energy reduction compared to optimized planned process times without sensor information. In addition, our findings also highlight the importance of sensor accuracy in achieving lower energy consumption during the heat treatment process.