Article: Discrete event simulation modelling for ceramic waste recycling using hybrid neural networks Journal: International Journal of Information and Communication Technology (IJICT) 2026 Vol.27 No.54 pp.46 - 64 Abstract: The ceramic industry generates an enormous amount of waste every year. Traditional recycling relies on manual sorting, with an accuracy rate of only about 78%, and the production line scheduling is rigid. To achieve efficient resource utilisation, this paper innovatively integrates convolutional and recurrent neural networks to construct an intelligent waste recognition model, and embeds it into a discrete event simulation system for dynamic optimisation. Experiments show that the new method increases the classification accuracy to 96.7%, the system throughput increases by 32.4% after simulation optimisation, and the utilisation rate of key equipment increases by 22.8%. This research provides an intelligent solution for the precise identification and system regulation of ceramic waste recycling, promoting the implementation of the circular economy. Inderscience Publishers - linking academia, business and industry through research

Title: Discrete event simulation modelling for ceramic waste recycling using hybrid neural networks

Authors: Jingjing Miao

Addresses: Graduate School of Techno Design Graduate, Kookmin University, Seoul, 02812, South Korea

Abstract: The ceramic industry generates an enormous amount of waste every year. Traditional recycling relies on manual sorting, with an accuracy rate of only about 78%, and the production line scheduling is rigid. To achieve efficient resource utilisation, this paper innovatively integrates convolutional and recurrent neural networks to construct an intelligent waste recognition model, and embeds it into a discrete event simulation system for dynamic optimisation. Experiments show that the new method increases the classification accuracy to 96.7%, the system throughput increases by 32.4% after simulation optimisation, and the utilisation rate of key equipment increases by 22.8%. This research provides an intelligent solution for the precise identification and system regulation of ceramic waste recycling, promoting the implementation of the circular economy.

Keywords: ceramic waste recycling; hybrid neural network; HNN; discrete event simulation; DES; resource utilisation rate.

DOI: 10.1504/IJICT.2026.153720

International Journal of Information and Communication Technology, 2026 Vol.27 No.54, pp.46 - 64

Received: 23 Jan 2026
Accepted: 27 Feb 2026
Published online: 21 May 2026 *

Title: Discrete event simulation modelling for ceramic waste recycling using hybrid neural networks

Keep up-to-date