Work

Research on Optimal Fabrication of High-Quality Ceramic by Process Analysis Technology

Year: 2025

Type: conference-paper

Abstract: We developed a composite recognition method combining hybrid sensor recognition and artificial intelligence image recognition techniques and optimized quality monitoring of the ceramic production process. By integrating deep learning models and image preprocessing techniques, appearance defects (such as cracks and color differences) were detected in ceramic products, and key parameters in the sintering process using temperature, pressure, and gas-sensitive sensors were monitored in real-time. The developed composite recognition method significantly improved the quality control level of ceramic production, reduced production energy consumption and wastes, and improved production efficiency.

Source: IEEE International Conference on Knowledge Innovation and Invention (ICKII)

DOI: 10.3390/engproc2025089022

Authors: Jianhua Cheng, Minhui Tong

Institution: Jingdezhen Ceramic Institute

Language: English

Topic: Industrial Vision Systems and Defect Detection

Subfield: Industrial and Manufacturing Engineering

Field: Engineering

Domain: Physical Sciences

SDGs: Industry, innovation and infrastructure, Responsible consumption and production

Open Access status: hybrid

OpenAlex ID: W4408001598

FWCI:

Cites: 2

Cited by:

Related to: 10