Applications of Deep Learning Algorithms in Industrial Process Optimization: Proposing a Decision-Making Framework with Focus on Industries in Iran and the West Asia Region

SayyedAhmad Bagheradeh Arjmandi¹

1) Engineer

Publication : National Conference on Information Technology, Nanotechnology, Artificial Intelligence and Technological Futures Studies(itnaf.ir)
Abstract :
Aimed at optimizing industrial processes in the era of the Fourth Industrial Revolution, this paper systematically reviews 92 studies published between 2015 and 2025 on the application of deep learning algorithms in industry. Utilizing a systematic review approach, the study analyzes the application of neural networks in four key areas: quality control, predictive maintenance, energy optimization, and logistics. The results indicate that specific architectures, including Convolutional Neural Networks (CNN) for visual inspection and quality control, Long Short-Term Memory (LSTM) models for time-series forecasting in equipment maintenance, Reinforcement Learning (RL) for energy management and consumption optimization, and Generative Adversarial Networks (GAN) for generating synthetic data and compensating for data scarcity, have demonstrated successful and effective performance. Based on the findings of the systematic review, the present article proposes an operational decision-making framework. This framework assists industrial engineers and managers in selecting the most suitable algorithm or combination of algorithms based on data type, optimization objectives, and implementation constraints. Emphasizing the link between deep learning and smart industry, and designed with a focus on the industries of Iran and the West Asia region, this framework is intended to serve as a practical guide for developing intelligent industrial systems and as a generalizable model at the regional level. The findings of this research pave a new path for the convergence of artificial intelligence and industry in the realm of technological decision-making and the localization of deep learning algorithms in domestic industries.
Keywords : industrial optimization smart industry deep learning cnn (convolutional neural network)