Peran Quality Engineering dalam Optimasi Proses Produksi : (Studi Literatur pada Industri Manufaktur Kontemporer) - Siti Nur Hamidah; Moh. Ayip Fathani; Zulfadlillah Zulfadlillah; Kardita Kardita (Pusat riset dan Inovasi Nasional, 2024)
This systematic literature review examines the evolving role of Quality Engineering (QE) in optimizing production processes within Industry 4.0 contexts. By analyzing 78 peer-reviewed studies (2010–2025), the research identifies critical shifts in QE methodologies, emphasizing integration with artificial intelligence (AI), machine learning (ML), and real-time digital twin technologies. Key findings reveal enhanced robustness through adaptive optimization algorithms (e.g., Bayesian optimization, NSGA-II), improved defect prediction via AI-driven quality control systems, and streamlined process interoperability through Manufacturing Execution Systems (MES) and Quality 4.0 frameworks. The study underscores digital integration as a catalyst for reducing variability, accelerating decision-making, and aligning quality management with Industry 4.0’s demands for agility and interconnected systems. Recommendations include adopting hybrid methodologies combining classical Six Sigma with ML-driven analytics and investing in workforce training for digital QMS adoption.