# Optimizing Aviation Maintenance through Algorithmic Approach of Real-Life Data
## 5 Conclusions
The potential for use in the Slovak Republic is promising for air transport, maintenance, and aviation training, but various other processes related to aviation also represent a very attractive area in our field. It is necessary to reach this potential and use it sensibly. Overall, the implementation of progressive technologies in aircraft maintenance has improved safety, reduced downtime, and increased operational efficiency. As the aviation industry continues to grow, it is likely that these trends will continue, and we can expect to see further innovations in this area in the future. The integration of real-life data is essential in making informed decisions and optimizing processes in aviation. By utilizing real-time data, organizations can improve operational efficiency, reduce costs, increase safety, and comply with regulatory requirements. The algorithmization of MRO processes in aviation is a critical component of modern maintenance practices. By leveraging the power of algorithms to optimize maintenance activities, airlines and MRO providers can improve the safety, reliability, and efficiency of their operations. While the theoretical benefits of algorithmization in MRO processes are well-established, the practical implementation of these techniques requires careful consideration and a specialized methodology. The creation of a specified methodology for an algorithmic approach to MRO processes is crucial for ensuring the effectiveness and reliability of these techniques in real-world applications. In this article, we present such methodology developed with a focus on the MRO process for aircraft wheels. Contrary to popular belief, the development and practical application of such an algorithmic approach to maintenance does not require a large investment. After thorough analysis and a careful selection of tools from the broad spectrum of the Industry 4.0 concept, the methodology can be truly cost-effective. It is the financial complexity that usually prevents companies from making such upgrades, especially if they are small- to medium-sized enterprises. One key consideration in the development of such a methodology is the integration of an algorithmic approach into existing MRO workflows and systems. Effective algorithmic approaches should be compatible with existing data sources, databases, and operational procedures to minimize disruption to existing workflows. Integration should also ensure that data privacy and security are maintained, and that sensitive operational data is protected from unauthorized access. The development of a specified methodology for an algorithmic approach to MRO processes also requires the establishment of training and education programs for maintenance technicians and support staff. These programs should emphasize the importance of data quality and management in achieving effective algorithmic approaches. Such programs should ensure that maintenance technicians are equipped with the skills and knowledge needed to implement and manage the methodologies in MRO processes. The methodology emphasizes the importance of continuous improvement and refinement. It should be constantly evaluated and updated based on feedback from maintenance technicians, operational data, and emerging best practices. Continuous improvement efforts should ensure that such techniques remain effective and relevant in a rapidly changing aviation environment. This is exactly what we did in the development phase of the methodology. In the interviews with technicians and managers, we considered and carefully implemented the best practices that emerged from their many years of experience. The entire implementation process was under the careful supervision of management, which played the role of a jury that decided the usefulness of the methodology. In conclusion, the practical application of algorithmic approaches to MRO processes requires the creation of a specified methodology that addresses key considerations, such as integration, training and education, and continuous improvement.