Effective sustainability assessment in aerospace component repair requires detailed, process-specific data, particularly for high-value components like turbine blades. As the industry shifts toward more sustainable practices, repair and remanufacturing are increasingly favoured over replacement, offering reductions in energy use, material consumption, and emissions. However, the fragmented nature of Life Cycle Inventory (LCI) data often limits its practical application in evaluating the environmental performance of these processes. To address this challenge, an interactive dashboard was developed to retrieve, structure, and visualise LCI data associated with turbine blade repair. Using a RESTful API, data from LCI database was extracted and organised into a hierarchical model reflecting the operational workflow. Key sustainability indicators, including energy consumption, task duration, and efficiency, were calculated and presented through dynamic charts and comparison tools. This enabled users to identify energy-intensive stages, bench-mark performance, and export data for further life cycle assessment. Results indicate that structured visualisation of LCI data significantly enhances transparency and supports informed, data-driven decisions in sustainable aerospace maintenance. The dashboard was evaluated positively by domain experts for its usability and practical relevance. While artificial intelligence was not incorporated, the study identifies promising future applications in predictive analytics, anomaly detection, and sustainability forecasting. These findings underscore the value of LCI-based visual tools in advancing circular economy and sustainability goals within aerospace repair operations.