This contribution presents an extended approach to utilising digital twin (DT) technology to improve sustainability and operational efficiency in assembly systems. Based on the principles of Industry 4.0, the study examines how real-time virtual replicas of manufacturing processes can drive material optimisation, in-line quality assurance and waste minimisation. In the study, two DTs were developed for an actual circular pallet assembly line consisting of three workstations. The first represents the existing assembly process with one control operation at the end of the assembly process, while the second DT includes an improved process with control operations after each workstation. To demonstrate the suitability of the improvements, various 'what-if' scenarios can be run, using the results obtained to show that quality control after each workstation not only increases system efficiency, but also significantly reduces raw material consumption and waste. The results show a reduction in raw material consumption of 8–10%, a reduction in waste generation of 18-23% and consequently energy savings of up to 10% compared to the baseline process. In both cases, the DT framework enables rapid scenario analysis and parameter tuning, thus supporting flexible decision-making while complying with the defined sustainability KPIs. The findings confirm the effectiveness of the described approach in different assembly environments, especially those with high material waste, and demonstrate its applicability to other types of discrete manufacturing. The presented approach can also be adapted for continuous production processes in other industries. Overall, the study provides empirical evidence that monitoring and simulation using the digital twin can deliver measurable environmental and operational benefits and positions DTs as strategic tools for embedding sustainability into industrial operations.