Analysis of Time Drift and Real-Time Challenges in Programmable Logic Controller-Based Industrial Automation Systems: Insights from 24-Hour and 14-Day Tests

Ensuring the reliability and temporal accuracy of real-time data transmission in industrial systems presents significant challenges. This study evaluates the performance of a Siemens Programmable Logic Controller (PLC) transmitting data to a MongoDB database via Node-RED over 24 h and 14-day intervals. Key issues observed include time drift, timestamp misalignment, and forward/backward time jumps, mainly resulting from Node-RED’s internal timing adjustments. These anomalies compromised the integrity of time-sensitive data. A significant disruption on day 8 due to a power outage introduced data gaps and required manual system recovery. Additional spikes in missing data were observed after day 12. The Predictive Missing Value (PMV) model addressed these gaps. The model achieved strong accuracy at larger intervals (e.g., 5 min) but showed reduced performance at finer resolutions (1–2 min) due to the irregularity of data patterns. This research highlights the difficulty of maintaining temporal consistency in long-term, real-time systems. It also evaluates the PMV model’s effectiveness in mitigating data loss while acknowledging its limitations under complex timing disruptions.