A Note on The Exact Control Chart for Monitoring Multinomial Processes - Gan, Shengjin; Yang, Su-Fen (International Journal of Industrial Engineering: Theory, Applications and Practice, 2026)
Statistical process control charts play a vital role in industrial manufacturing and service operations. While most existing control charts are designed for monitoring continuous data, methods for discrete data—particularly categorical data—remain relatively underdeveloped. In this paper, a sign-based EWMA multinomial control chart is proposed for monitoring multinomial processes. The properties and detection performance of the proposed chart are systematically compared with those of existing exact EWMA and CUSUM multinomial control charts. Numerical studies, together with a real data application, demonstrate that the exact EWMA multinomial control chart consistently exhibits the best and most robust detection performance, whereas the proposed sign-based EWMA multinomial control chart performs the worst among the charts considered.