Enhancing Quality Management through Advanced Statistical Techniques - Nugroho, Cahyo Adi; Perdana, Janatika Putra; Tirtoadisuryo, Dendy; Rachmat, Asep Ferry; Erlangga, Irwan Syah (Management Studies and Business Journal (PRODUCTIVITY), 2024)
Production environments with high variability present challenges in maintaining quality consistency, which are difficult to address using traditional approaches. This research aims to evaluate the impact of machine learning (ML)-based optimization on long-term quality management in industrial sectors that experience high production fluctuations. Using a systematic literature review approach with the PRISMA method, this research analyzes 18 studies related to the implementation of ML in quality process optimization. Results show that ML significantly supports product stability, defect reduction, and sustainable operational efficiency. The implications of this research strengthen the application of ML as a relevant and effective method for improving long-term quality in dynamic production environments.