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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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Published on: August 29, 2025

Rapid optimization of cost-based tolerancing.

¹Consultant, Habichtstrasse 58, 86899 Landsberg, Germany. Akira.yabe@t‐online.de

|March 14, 2012

Summary

This study introduces a fast cost-based tolerancing optimization method. It demonstrates that minimal Monte Carlo simulations can efficiently balance product yield and tolerance costs in practical engineering.

Area of Science:

Engineering
Manufacturing Processes
Statistical Methods

Background:

Cost-based tolerancing is crucial for balancing manufacturing costs and product performance.
Traditional methods can be computationally intensive, requiring extensive simulations.
Optimizing tolerance allocation impacts overall product yield and cost-effectiveness.

Purpose of the Study:

To develop a rapid optimization method for cost-based tolerancing.
To reduce the computational burden associated with traditional tolerancing techniques.
To provide a practical approach for balancing yield and tolerance costs.

Main Methods:

Proposed a novel rapid optimization algorithm for cost-based tolerancing.
Utilized a limited number of Monte Carlo simulation cases.

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Published on: February 16, 2019

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Simulation of a Scaled Assembly Process with Collaboration of a Robotic Arm and Monitoring through a Vision System for Quality Control

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Published on: August 29, 2025

Optimization, Test and Diagnostics of Miniaturized Hall Thrusters

Optimization, Test and Diagnostics of Miniaturized Hall Thrusters

Published on: February 16, 2019

Applied the method to a practical tolerancing problem.

Main Results:

The proposed method significantly speeds up the optimization process.
Achieved the optimal balance between product yield and tolerance cost with few simulations.
Demonstrated the effectiveness of the rapid optimization approach.

Conclusions:

A computationally efficient method for cost-based tolerancing has been developed.
The approach effectively balances product yield and tolerance costs.
This method offers a practical solution for real-world tolerancing challenges.