Adaptive elevator kinematics optimization based dual response algorithm for determining proper levels in plaster...

Area of Science:

• Industrial Engineering
• Process Optimization
• Materials Science

Background:

• Plaster milling processes require robust parameter estimation for consistent output.
• Variability in stucco combined water impacts final product quality.
• Conventional methods may struggle to minimize variance while meeting targets.

Purpose of the Study:

• To introduce and evaluate a novel hybrid algorithm, Adaptive/Elevator Kinematics Optimization algorithm based on dual response algorithm (A/EKO-DRA).
• To enhance robust parameter estimation and design in plaster milling.
• To minimize the impact of variance on stucco combined water content.

Main Methods:

• Development of the Adaptive/Elevator Kinematics Optimization algorithm based on dual response algorithm (A/EKO-DRA).
• Comparison of A/EKO-DRA performance against conventional processes.
• Validation through numerical examples and simulations.

Main Results:

• A/EKO-DRA demonstrated the lowest mean absolute errors in parameter estimation.
• The algorithm achieved a response mean of 5.927%, meeting the industrial target of 5.9%.
• Significant reduction in response variance was observed compared to other methods.

Conclusions:

• The A/EKO-DRA method offers a promising approach for optimizing plaster milling parameters.
• It effectively reduces variability and maintains desired output targets.
• This hybrid algorithm enhances robust parameter estimation for industrial applications.