Work

Process Design of Vinyl-Coated Metal Sheet Stamping for Prevention of Delamination and Wrinkling by DNN-Based Multi-Objective Optimization

Year: 2025

Type: article

Abstract: The increasing use of vinyl-coated metal (VCM) sheets in home appliances requires robust forming processes to prevent defects such as delamination and wrinkling, especially under elevated temperatures and humidity. This study presents a deep neural network (DNN)-based multi-objective optimization framework to determine optimal stamping parameters for VCM sheets. A delamination limit diagram (DLD) is experimentally established by combining limit dome height tests with immersion tests, defining the critical strain boundary under environmentally conditions. A finite element (FE) based dataset of four process variables was then used to train a DNN surrogate model with high predictive accuracy. Using the trained DNN model, Pareto-based optimization identifies nondominated solutions balancing delamination and wrinkling. The optimal condition was validated by FE simulation, confirming simultaneous suppression of both defects within the DLD. The proposed DNN-Pareto framework provides and efficient and reliable tool for defect prediction and optimization in VCM stamping, ensuring high surface quality and environmental durability.

Source: Materials

DOI: 10.3390/ma18245589

Authors: Min-Gi Kim, Jae-Chang Ryu, Chan-Joo Lee, Jin-Seok Jang, Dae-Cheol Ko

Institutions: Pusan National University, Korea Institute of Industrial Technology

Language: English

Topic: Metal Forming Simulation Techniques

Subfield: Mechanical Engineering

Field: Engineering

Domain: Physical Sciences

Open Access status: gold

Estimated APC paid: $3,137

Funder: Pusan National University