Development of AI Prediction Tool for Fused Deposition Modeling of ABS Material for automobile applications

Additive Manufacturing (AM), notably Fusion Deposition Modeling (FDM), has grown in popularity owing to its ability to create complicated forms from a variety of materials. This research aims to increase the efficiency and accuracy of the FDM process for Acrylonitrile Butadiene Styrene (ABS) material. ABS plastic material is an important material in automotive manufacturing due to its strength, durability, and versatility. It is used extensively for a wide range of components, including dashboard components, bumpers, fenders, exterior trim, and interior trim. The objective will be accomplished by the development of a prediction model using an Adaptive Neuro-Fuzzy Inference System (ANFIS). The research investigates the influence of FDM parameters, including layer height, nozzle temperature, and printing speed, on significant printing characteristics such as dimensional accuracy, surface quality, printing speed, and dimensional deviation. The essential data is derived from empirical experiments of FDM printing, which were carried out using several combinations of parameters. The experimental trials have been designed using Taguchi's methodology. The ANFIS prediction model is constructed by exploiting the collected information, leveraging the combined learning capabilities of neural networks and the interpretability of fuzzy logic systems. The model is trained and tuned to accurately predict printing characteristics by examining input parameters, providing significant insights into the complex interactions inside the FDM process. The performance of the ANFIS prediction model is evaluated using statistical analysis and then compared to the findings obtained from experiments. The model demonstrates its proficiency in properly predicting printing qualities and capturing intricate process dynamics. The suggested Adaptive Neuro-Fuzzy Inference System (ANFIS) prediction model offers a systematic methodology to improve Fused Deposition Modeling (FDM) parameters. Manufacturers may enhance efficiency and quality in additive manufacturing processes by using ABS material. This study improves the understanding of FDM processes and provides a valuable tool for improving the process in many technical and industrial applications.