With six major truck companies holding similar market shares in Europe, advancements and improvements are crucial to avoid falling behind. However, knowing what aspects to improve is paramount, as focusing on the wrong areas can lead to wasted resources and time. At the operational level, collecting accurate data and utilizing it effectively is essential for learning and progress. One effective method is to gather data on process losses and measure effectiveness accordingly. Overall equipment effectiveness (OEE) and overall process effectiveness (OPE), originating from total productive maintenance (TPM), are commonly used metrics for this purpose.   To ensure comprehensive assessment, three main effectiveness measurements are necessary. OEE evaluates machine effectiveness, total effective equipment performance (TEEP) considers planned maintenance, and OPE encompasses all losses, internal and external.   In this thesis, all three effectiveness measurements are applied to Scania's pallet disassembly process. Due to its high variability, traditional TPM methods cannot be directly applied. Therefore, adaptations were made. Time became the common factor for measurement, eliminating the need for cycle times and unit outcomes. Additionally, the aspect of quality was excluded, given the nature of the disassembly process and its minimal quality loss.   The implemented method involves two solutions: one currently in use and one proposed for the future. The current approach involves data entry by an operator into an Excel sheet at the end of each shift. This data is then transformed into OEE, TEEP, and OPE pie charts, allowing for weekly analysis of shift, day, and week effectiveness. As for future recommendations, replacing the programmable logic controller (PLC) would enable real-time effectiveness monitoring and process simulations.