Grade Change Optimization is an advanced software solution for automatic order changes in the paper industry. It is designed to improve how paper manufacturers transition from one production order to another, especially when changing paper grammage. In conventional production, these transitions are usually performed manually by machine operators, making speed and quality highly dependent on operator experience. This often leads to longer transition times, reduced productivity, and unnecessary losses of energy, water, and raw materials.
The solution addresses these challenges by introducing advanced automatic order change management. It connects key elements of the production line and communicates with the existing DCS via the ERGA OPC DA communication protocol. Using predicted process outputs, it calculates optimal process parameters with high precision. This enables faster and more stable transitions between production orders while reducing the risk of human error.
At the core of the system is model-predictive control, which predicts future system behavior and continuously calculates the optimal control input. The controller works within defined system constraints and minimizes the selected objective function during each sampling interval. This ensures that control actions remain both efficient and reliable throughout the transition process.
Its implementation includes data collection, data processing, system identification, modeling, linearization, controller configuration, and fine tuning. The system can be integrated with production variables such as stock flow, machine speed, steam pressure, grammage, moisture, and QCS-related measurements. It can also be further expanded with cloud-based analysis and neural networks for even more advanced model adjustment and controller optimization.
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