Hamed Nozari
Institute of Economics and Politics, University of National and World Economy, Sofia, Bulgaria.

Zornitsa Yordanova
Industrial Business Department, University of National and World Economy, Sofia, Bulgaria.

DOI https://doi.org/10.33889/IJMEMS.2026.11.3.049

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Abstract

Quality control in the pharmaceutical industry has always faced a fundamental challenge in balancing product release speed, safety, operational costs, and regulatory requirements. In many pharmaceutical organizations, the final decision for batch release still relies on extensive human reviews and conservative procedures, which leads to operational bottlenecks and reduced organizational agility. Despite recent advances in digital twin and risk-based approaches, a unified and operational framework for realizing quality control without direct human intervention has not been systematically developed. This research presents, for the first time, a closed-loop framework for touchless quality control (Touchless QC) based on the integration of hybrid digital twin, fuzzy multi-objective optimization model, and human intervention mechanism under exceptional conditions. In this framework, the digital twin of the laboratory flow simulates the propagation of quality risk and resource constraints, and the multi-objective optimization engine simultaneously minimizes the release time, cumulative quality risk, quality control costs, human intervention rate, and laboratory congestion under GMP and SLA constraints. The meta-heuristic algorithms NSGA-II, MOEA/D, and MOPSO are used to extract the Pareto front. Results from real and simulated industrial data show that the proposed framework is able to significantly reduce the release time and quality control costs, while maintaining the quality risk level at an acceptable level or even lower than traditional policies. Also, release decisions are made in a structured and automated manner, and human intervention is activated only when risk or uncertainty thresholds exceeds the defined limits. In addition to improving operational performance, this framework also enhances transparency, traceability, and regulatory robustness of decisions, and is a practical step towards realizing smart, risk-based quality control in the pharmaceutical industry.

Keywords- Non-contact quality control, Digital twin, Risk-based decision making, Batch release, Fuzzy multi-objective optimization.

Citation

Nozari, H., & Yordanova, Z. (2026). Touchless Quality Control in Pharma Using a Digital Twin–Driven Fuzzy Multi-Objective Optimization Framework for Risk-Aware Release Decisions. International Journal of Mathematical, Engineering and Management Sciences, 11(3), 1178-1201. https://doi.org/10.33889/IJMEMS.2026.11.3.049.