Purpose: The article aims to present elements for analysis systems in industrial and logistics processes. Design/Methodology/Approach: The article presents the preparation of a module for the analysis of production processes and support for logistics processes. The use of time series, randomness test, and correlation test is presented—a comparison of measurement results from various sensors used in industry and transport. Findings: The study's result was the analysis of waveforms from sensors for controlling the operating parameters of production and logistics systems. Preparing such a forecast solution allows you to check many possible measurement process results and support decisions in the system's operation, allowing for better decision-making in conditions of uncertainty. Practical Implications: The presented method of signal analysis for forecasting the system's behavior and operation can support decision-makers in taking appropriate actions, and in the future, it will allow the system to manage itself automatically. Originality/Value: A new feature uses time series, randomness, and correlation tests to review and monitor the performance of various types of sensors in logistics and production systems.

Krzysztof Krol Et Al (2024). Analysis System for Logistics and Production Processes: A Methodological Approach to Signal Analysis for Forecasting, European Research Studies Journal Volume XXVIΙ Special Issue 2, 59-71