# Sensor-Data-Driven Prognosis Approach of Liquefied Natural Gas Satellite Plant
## 1 Introduction  
The European Union's Green Paper specifies the need to substitute 20% of conventional fuel consumption with alternative fuels by the year 2020. An alternative energy source (not considering electricity) is natural gas (NG) that is relatively one of the most environmentally friendly as it has an inherently clean combustion process [1]. Natural gas is transported from gas fields to distribution-network systems in two main ways, either by pipeline or by ships in the form of liquefied natural gas (LNG).  
LNG is produced by cooling natural gas below its boiling point (\(-162\)\({}^{\circ}\)C at ambient pressure) at the liquefaction plant located nearby the gas-production source. LNG is transported from production site to receiving terminals through special ships (LNG tankers) that keep LNG in a liquid phase. After the regasification procedure, the gas is input into a local gas-pipeline network. However, recently, some small-scale LNG (SSLNG) facilities have emerged with regional storage hubs and direct gas supply. LNG is transported from the terminal to satellite terminals by smaller LNG ships or trucks. Such terminals are used for receiving and storing LNG for a limited period of time depending on storage capacity. Their capacity ranges from a couple of hundred of m\({}^{3}\) to around 20 m\({}^{3}\). The SSLNG market is developing rapidly, especially for transportation fuel, and to serve end users in remote areas or those that are not connected to the main pipeline infrastructure [2]. In the case of Spain, six regasification terminals are in operation, in Barcelona, Sagunto, Cartagena, Huelva, Bilbao, and Mugardos. In 2015, 869 sites received LNG with a fleet of approximately 35,000 trucks. The largest is Barcelona with 232 destinations [3, 4]. Thus, the supply chain is one of the main problems of SSLNGsatellite terminals. In this case, small-scale supply-chain natural gas must be transported from a large import terminal to consumers through a network of smaller satellite terminals with truck transports. LNG carriers used in this type of system have smaller capacities and must perform multistep voyages.  
Supply-chain planning consists of designing an optimal and feasible distribution plan for the whole supply chain. In the case of satellite terminals, the supply chain must take into account LNG consumption in order to guarantee its safety storage. Since gas consumption strongly fluctuates and follows the weather changes of different seasons, making a good plan is not easy, and even less so in the case of satellite LNG for domestic users.  
Improved information is key for making decisions to guarantee safety operations of LNG regasification satellite plants. Therefore, this paper proposes to predict the remaining time by providing remaining useful life (RUL) to refill the LNG tanks that is very useful for the predictive-maintenance plan of the LNG satellite plants, and for applying the optimal management of a truck service to refill LNG tanks when a company has many plants working simultaneously in the region.  
The article is structured as follows: In Section 2, we present the related work. Section 3 describes the problem under study. Section 4 is dedicated to the description of methodologies used for solving the problem. Section 5 shows detailed experiment results and comparisons. Finally, conclusions are given in Section 6.