The tolerance balancing optimization with multiple constraints on the form and function of the discrete functional...

Area of Science:

• Mechanical Engineering
• Manufacturing Engineering
• Surface Metrology

Background:

• Discrete functional surface performance is significantly influenced by surface form and geometric function.
• Traditional tolerance design often prioritizes geometric function, neglecting the impact on surface form, which is suboptimal for discrete functional surfaces.
• The varying influence of different part tolerances on surface form and geometric function necessitates a more integrated approach.

Purpose of the Study:

• To propose a novel tolerance balancing optimization method for discrete functional surfaces.
• To address the limitations of existing methods that focus solely on geometric function requirements.
• To develop a model that considers multiple constraints on both surface form and geometric function.

Main Methods:

• Extraction of crucial tolerances significantly affecting surface form and geometric function to reduce optimization scope.
• Development of a tolerance optimization model incorporating a penalty function for multiple form and function constraints.
• Integration of tolerance contribution into a nonlinear inertial weight particle swarm algorithm for optimization.

Main Results:

• Identification of critical tolerances that have the most substantial impact on surface form and geometric function.
• Successful establishment of a tolerance optimization model balancing form and function constraints.
• Achievement of optimized part tolerances that satisfy both geometric function and surface form requirements through the proposed algorithm.

Conclusions:

• A tolerance balancing optimization approach is effective for discrete functional surfaces.
• Simultaneously considering surface form and geometric function in tolerance design leads to improved performance.
• The proposed method effectively identifies and optimizes critical tolerances, enhancing the overall manufacturing process.