Improving Documentation Process With Data Mining and Machine Learning Methods: A Case Study in the Aviation Industry

Many businesses have to operate within the framework of national and international standards to meet customers' expectations, security requirements, and environmental regulations. Compared to other industries, the aviation industry has high-security requirements. However, the continuous publication of documents has resulted in document inflation over time, document-process structure that deviates from a simple philosophy. Given the problem at hand, this study aims to develop a streamlined document processing system that aligns with the lean philosophy in the aviation company under investigation. Documents with a similarity rate exceeding 50% were examined, and a proposal was made to either combine these documents or establish relationships between them. Various machine-learning algorithms are used in this chapter. The accuracy rate of a hybrid model that included the support vector machine (SVM) and logistic regression techniques increased by 6% to 76%. Python was utilised during the research.