DOCUMENT MINING ON AIRCRAFT MAINTENANCE HUMAN ERRORS AND SKILLSET MISMATCH ISSUES

Aviation incorporates activities which encompass varies mechanical flights and the aircraft industry. The industry grows rapidly as travelers prefer travelling by air due to the concept of world without borders with cheaper fares and global business transactions. Thus, for better aircraft service and safety, the aircraft maintenance repair and overhaul are crucial tasks in aviation industry. Yet, many aircraft incidents are happening because of many reasons such as faulty equipment and hazardous weather conditions, including turbulence, and human error. In this paper, we investigated on a set of online articles and reports related to aircraft incidents and problems using text mining technique. The technique extracts frequent and significant terms existed in the document set. The experiment consists of four (4) modules which are (i) online article and report collections, (ii) document pre-processing (iii) text analytics and (iv) visualization. The outcome of the experiment demonstrates that the gist of majority documents describes on aircraft maintenance, skill mismatch and training gaps.