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Control charts for monitoring ship operating conditions and CO 2 emissions based on scalar‐on‐function regression
Applied Stochastic Models in Business and Industry ( IF 1.4 ) Pub Date : 2020-01-20 , DOI: 10.1002/asmb.2507
Christian Capezza 1 , Antonio Lepore 1 , Alessandra Menafoglio 2 , Biagio Palumbo 1 , Simone Vantini 2
Affiliation  

To respond to the compelling air pollution programs, shipping companies are nowadays setting‐up on their fleets modern multisensor systems that stream massive amounts of observational data, which can be considered as varying over a continuous domain. Motivated by this context, a novel procedure is proposed, which extends classical multivariate techniques to the monitoring of multivariate functional data and a scalar quality characteristic related to them. The proposed procedure is shown to be also applicable in real time and is illustrated by means of a real‐case study in the maritime field on the continuous monitoring of operating conditions (ie, the multivariate functional data) and total CO2 emissions (ie, the scalar quality characteristic) at each voyage of a cruise ship. The real‐time monitoring is particularly helpful for promptly supporting managerial decision making by indicating if and when an anomaly occurs during the navigation.

中文翻译:

基于函数标量回归监测船舶运行条件和 CO 2 排放的控制图

为了应对引人注目的空气污染计划,航运公司现在正在他们的船队上建立现代多传感器系统,以流式传输大量观测数据,这些数据可以被认为是在一个连续的领域内变化。在此背景下,提出了一种新程序,该程序将经典的多元技术扩展到多元功能数据的监测以及与它们相关的标量质量特征。所提出的程序也显示为实时适用,并通过海事领域关于连续监测操作条件(即多变量功能数据)和 CO2 排放总量(即,标量质量特性)在游轮的每次航行中。
更新日期:2020-01-20
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