The Indian aviation industry has been one of the fastest growing in the world since the last decade. Aviation experts anticipate it to be the largest in the world by 2030. The accelerated growth in passenger number has been influential enough to encourage more job opportunities in the industry. The anticipated exponential growth also envisions increase in the usage of aviation OOV words and phrases. For communicating the various proceedings and news through the mainstream and social media, these aviation words have become more frequent nowadays. The aviation domain is heavily dependent on the use of OOV words, which, in turn, are structured words molded to fit the aviation domain. This causes a huge problem during the conversion from English to other languages using machine translation (MT). This paper explores the problems encountered during translation of such sentences and suggests how these sentences can be pre-processed before being fed into the MT software for better translations. This paper also investigates how these structured and OOV words can be handled in the English language itself, before being converted to any other language and surveys the prospects of maneuvering this tool to create a bilingual corpus for Machine Translation applications.