Data-driven demand analysis and design reliability study of critical components of complex products

Area of Science:

• Engineering
• Product Design
• Quality Management

Background:

• Digital intelligence transforms complex product design with rapid iteration and integration.
• Traditional design lacks consideration for sustainability, resources, and economy in critical components.
• Ensuring critical component reliability requires aligning quality with customer needs.

Purpose of the Study:

• To develop a method for analyzing demands and ensuring design reliability of critical components in complex products.
• To integrate product design parameters, manufacturing processes, and quality characteristics.
• To validate the proposed method using automotive engine critical components.

Main Methods:

• Utilized the Kano-Quality Function Deployment (QFD) model for requirement identification.
• Constructed a Design Manufacturing Analysis (DMA) model integrating multi-dimensional characteristics.
• Applied the DMA model for design reliability analysis of critical components.

Main Results:

• The Kano-QFD model effectively clarified the requirement identification path for critical components.
• The DMA model successfully integrated design, manufacturing, and quality dimensions.
• The proposed method demonstrated high compatibility with early-stage complex product design and manufacturing.

Conclusions:

• The developed method ensures critical component quality characteristics align with customer requirements.
• The approach provides a valuable reference for product design and quality management in complex product development.
• The method supports R&D and manufacturing personnel in meeting evolving complex product demands.