Operational Validation of an Integrated PLC–Vision System for Pre-Analytical Tube-Box Classification Using Simulation

Abstract

Pre-analytical laboratory processes are highly susceptible to operational errors due to manual handling and visual identification of blood collection tube boxes, negatively affecting efficiency, reliability, and workflow consistency. Although commercial automation solutions exist, their high acquisition and integration costs limit adoption in small and medium-sized laboratories, particularly in resource-constrained environments. This paper presents the operational validation of an integrated system combining machine vision and programmable logic control (PLC) for automated pre-analytical tube-box classification, using industrial simulation as the primary validation environment. The proposed approach follows the VDI 2206 methodology for mechatronic system development and implements a three-level architecture inspired by IEC 62264, including a field level with virtual sensors and actuators, a control level based on a Siemens S7-1200 PLC programmed in Ladder logic, and a supervision level using a human–machine interface (HMI). A vision module based on HSV color-space processing classifies tube boxes according to color-coded attributes. High-fidelity simulation enables controlled experimentation without physical deployment. Operational validation includes performance evaluation, robustness analysis, and extreme condition testing. The system achieves a classification accuracy of 97.3%, a sustained throughput of 219.5 boxes/h, and an average cycle time of 1.375 s. Integration feasibility is confirmed through a Vision–PLC latency compliance of 99.3% (≤200 ms). Reliability analysis via Monte Carlo simulation estimates an MTBF of 2,347 h, and stress tests confirm stable behavior under adverse scenarios.