Automotive driveline components require high-dimensional precision and durability due to strict torque-transmission and noise, vibration, and harshness (NVH) performance requirements. Despite this, several manufacturing programs continue to rely on corrective quality practices, which often lead to delayed problem identification, increased rework, and higher production costs. This study investigates the implementation of Advanced Product Quality Planning (APQP) in planetary sun gear manufacturing through a quantitative industrial case study. The work combines APQP phase mapping with Failure Mode and Effects Analysis (FMEA), Statistical Process Control (SPC), Measurement System Analysis (MSA), and process capability assessment to establish a preventive quality planning approach. The implementation led to a considerable reduction in high-risk Process FMEA (PFMEA) issues before process freeze and improved overall manufacturing stability. Critical-to-quality (CTQ) parameters achieved capable and consistent performance, with capability values exceeding accepted industrial benchmarks. In addition, First Pass Yield (FPY) improved considerably, while pilot-stage rework was significantly reduced. Measurement system variation also improved after corrective MSA actions were introduced. The study further proposes an integrated risk-capability-gate scoring framework to strengthen the relationship between project governance and process readiness evaluation. The findings demonstrate that APQP can serve as an effective quality management methodology when supported by statistical validation and structured decision-making. Future research may focus on digital APQP systems, AI-assisted FMEA optimisation, and Industry 4.0-based real-time quality monitoring for predictive manufacturing control.