Paper Title
Automation of Conducting A Patentability Search in an Example of Aviation Engines

Abstract
Aircraft engines are the most critical component of any aircraft, ensuring not only its movement but also flight safety. Each aircraft engine is a unique technical solution that has gone through many stages of development, testing and improvement. Automating the process of finding patentability would involve using technology and tools to assist in patent search and analysis. Patentability searches are usually performed to determine whether an invention is novel, non-obvious and industrial application or utility, which are key criteria for obtaining a patent. Patent search is a critical step that precedes the determination of patentability. During the patent search examiner finds relevant documents. Which could affect novelty and non-obvious. Regarding that examiner decides whether the invention should be patented or not. To add a keyword, we need to use the “AND” operation in patent search databases. But again, this is not the only operation that an expert can use. The second most commonly used operator would be "OR". The difference between them is that the “AND” operation combines terms and aggregates the found documents, while the “OR” operation separates the terms and increases the found documents. Automating the process of finding patentability offers several advantages, making the search more efficient and effective. Automation greatly reduces the time required for patent searches. The process of search could be faster with automation. However, there would be levels of automation. The three levels that we would suggest are fully automated systems, semi-automated systems, and partially automated systems. All three automation methods would use AI or machine learning. A fully automated system would scan the application documents and according to that will conduct a patent search. Later on, system itself would create a patent search report. Semi-automated system would again scan the application documents and according to that conduct a patent search. However, this is where the automation would stop. The automation would not create a search report, it would only find some documents and the human examiner would need to check them and create a search report accordingly. A partially automated system would not scan the application documents. It would conduct a patent search according to the keywords provided by the human examiner. This is again where the automation would stop. The automation would not create a search report, it would only find some documents and the human examiner would need to check them. After inspecting the found documents, the human expert would create a patent search report. Before the automation would conduct any patent search, it might be necessary to find if the application is applicable in the said field. This process itself could be done in two ways. The first one would be automation. The automation would scan the documents of the application and find if the invention or utility model is applicable or not. The second one would be a human examiner. Here, the examiners themselves would figure out if the application is applicable or not. Firstly, the automation would check for if the invention is applicable in the industry. If the invention is applicable then the invention would be granted a patent. If the invention is not applicable then the application would be refused. If it isapplicable, then the automation would check the next condition. Then the automation would find if the application is or is not obvious. Then after finding that the invention has the "inventive step", the automation would check novelty. Again, if the invention is not novel the application would be refused. In case it has a novelty, invention would be granted as a patent. Keywords - Patentability, Patent Search, Patent Law, Automated Search, AI, Artificial Intelligence, Patents, Inventions, Machine Learning, Text Mining, Automation, Aviation Engines, Engines, Aviation.