Big Data in the Aerospace Industry

By Badea, Victor Emmanuell; Zamfiroiu, Alin et al. | Informatica Economica, January 1, 2018 | Go to article overview

Big Data in the Aerospace Industry


Badea, Victor Emmanuell, Zamfiroiu, Alin, Boncea, Radu, Informatica Economica


1 Introduction

The diffusion of digital technologies in people's everyday life has stimulated humanto-human interactions between man and machine-machine. These interactions generate massive volumes of data, commonly referred to as "Big Data" (BD), and characterized by rapid growth of large volumes of complex datasets that exceed the abilities of commonly known data management systems.

Due to the need to give more value to businesses, companies have begun to adopt Big Data as a solution, migrating from classical databases and data stores that lack flexibility and are not optimized enough.

Large data is a collection of such large and complex datasets that it becomes difficult to process using database management tools or traditional data processing applications.

The concept addresses large volumes of data automatically generated from different autonomous data sources. Given that traditional databases have reached limits on analyzing these data, dedicated solutions should be considered. In recent approaches, important data is characterized by principles known as volume, variety, speed and 4V veracity. Challenges include capturing, storing, searching, sharing, analyzing, and viewing. Such data, high volume, high-speed information and / or wide-ranging information requires new forms of processing to enable improved decision-making, knowledge discovery and process optimization.

The IoT implies that data is collected from several types of sources in constrained environments. Large-scale data generated in the IoT offers as an immediate promise realtime responses and predictions and personalized options.

2Aerospace Industry

Big Data represents a new generation of technologies and architectures designed to extract value from the huge data volumes with a large variety, allowing processing and analysis in real time. [1]

Aerospace companies understand better the challenges of Big Data than the rest of the industries.

A clear example of the impact of Big Data in the aerospace industry is the "digital aircraft" from our days, which can collect up to 300,000 parameters, depending on the duration of the flight and the type of aircraft. A major aircraft manufacturer estimates that data transmission will increase by 14 % over the next few years.

A simple and practical example could be the following: An average Boeing 737, twoengine commercial aircraft, takes a six-hour flight between New York and Los Angeles. Each engine generates 20 terabytes of information per hour. By multiplying 20 terabytes of information from a single engine with a 6 hour flight, we will get 240 terabytes of data from the engines. According to the National Association of Air Traffic Controllers in the United States, a total of 87,000 are crossing the sky of the United States of America, of which are 29,000 commercial flights. By multiplying this by 365 days, we will get a real challenge, but also a simplification in terms of Big Data service. [2]

To better understand the magnitude of this amount of data, we will make the following comparison: the number of ten digits represented in the Figure 2 in TB, mentioned above, is converted to 2.7 ZB. This 2.7 ZB is almost equal to the total global traffic data estimated in 2015. [2]

The analysis of this information results in the following questions:

* Why an aircraft manufacturer/ commercial airline operator would like to receive all the data collected and stored?

* What would be the impact if this information were not used?

The answer would be very simple: an aircraft manufacturer / airline operator would normally use this data to maximize operational efficiency, and the impact of not using this information would particularly affect the company's operations, aircraft production, maintenance and management company for the level of the air fleet.

When an airline buys a 100-390 million dollar aircraft for its fleet, the goal is to keep the airplane in service for at least 18 hours a day for the next 15 to 20 years. …

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