Statistical Method to Model the Quality Inconsistencies of the Welding Process

TL;DR

This paper introduces a statistical approach to model and monitor the quality inconsistencies in Resistance Spot Welding, enabling more efficient quality control and reducing physical testing in automotive manufacturing.

Contribution

A novel statistical method for modeling welding quality variability based on process parameters, improving efficiency and reducing testing costs.

Findings

Effective modeling of welding quality inconsistencies.

Application to real-world welding process demonstrated benefits.

Potential for significant cost savings in quality monitoring.

Abstract

Resistance Spot Welding (RSW) is an important manufacturing process that attracts increasing attention in automotive industry. However, due to the complexity of the manufacturing process, the corresponding product quality shows significant inconsistencies even under the same process setup. This paper develops a statistical method to capture the inconsistence of welding quality measurements (e.g., nugget width) based on process parameters to efficiently monitor product quality. The proposed method provides engineering efficiency and cost saving benefit through reduction of physical testing required for weldability and verification. The developed method is applied to the real-world welding process.