Efficiency is supreme in Industrial Engineering. Many advanced AI algorithms are generally used in the industrial environment to monitor, identify, and detect machinery conditions and other related activities. The primary challenging task is accurate fault detection, which is essential to classifying the defects in manufacturing. Hence, choosing a suitable AI algorithm for monitoring the industrial environment is most important. This paper intends to solve the problem of automatically optimizing specific industrial products’ design, structure, and process; it selects advanced AI models, such as RNN and CNN. The paper will address the optimization issue using neural networks in the Recurrent Neural Network and Convolutional Neural Network architectures. The goal behind the CNN model is to implement fault detection, selection of construction materials, and validation of the design through CAD methods utilizing feature extraction and pattern recognition. The RNN model assists the user by