The industry remains highly dependent on human labor and due to high turnover rates, supportive systems are necessary to maintain efficiency and quality. The basis of every process is the work instruction, but in many cases these instructions are overly complicated and contain excessive information, which can overwhelm operators. This research focuses on observing operators’ learning curve, particularly in terms of improvements in time and quality, and how they interpret and engage with the provided work instructions and abstractions of it. We aim to track how the time spent focusing on instructions decreases as operators become more proficient. This allows the creation of more abstract and simplified work instructions that highlight only essential information. By emphasizing key elements, operators can work better after the initial training phase. An experiment was designed, targeted measurements were performed, and the results were analyzed. The learning curves were recorded during a disassembly process to find the critical elements in the created work instruction and later simplify it. The results indicate that simplified instructions, introduced after an initial learning phase, led to shorter task completion times without increasing error rates. These findings suggest that instruction abstraction can support operator efficiency during repetitive tasks. Future research will explore adaptive instruction systems and their integration in industrial environments with larger and more diverse participant groups.