A Systematic Review for Quality within the Automotive Industry 4.0

Artificial Intelligence (AI) is exponentially developing within the quality management system (including quality assurance, quality development, customer satisfaction, etc.) within the automotive industry under the model of Industry 4.0. Within this paper, the application of AI technologies is analyzed for the enhancement of the quality processes and big data, so that higher standards of reliability and safety in automotive manufacturing are fulfilled. Machine learning, deep learning, convolutional neural network, computer vision as part of the AI solutions are used for the detection of the defects, to optimize the production parameters, to link the internal data with the external ones, with the final scope of the prediction of potential failures. The real-time data analysis is the most significant benefit for the automation of the big quality data, where AI improves the accuracy, eliminates the human error, and reduces considerably the production downtime. This research presents the major advantages and opportunities that AI solutions grant within the quality management field, underscoring its vital role for the achievement of higher quality standards, reducing costs associated with non-quality, and nurturing innovation. The findings underscore that the continuous integration of AI into quality assurance processes is essential for maintaining competitiveness and meeting the increasingly stringent demands of the global automotive market.