A Data-Driven Framework for Real-Time Decision-Making in Food Safety Quality Assurance: Integrating SPC, AI, and Industrial Process Optimization

Abstract

This article presents a comprehensive framework for implementing real-time decision-making systems in food safety quality assurance. By integrating Statistical Process Control (SPC), Artificial Intelligence (AI), and industrial process optimization techniques, food processors can transform their quality assurance programs from reactive to proactive, data-driven systems. Using Schwan's Company as a case study, we demonstrate how this integrated approach delivers significant improvements in food safety outcomes, operational efficiency, and product quality. The framework outlined provides actionable guidance for food manufacturers seeking to leverage advanced analytics for enhanced quality assurance.