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.
The modern development of data acquisition technologies in many industrial processes is facilitating the collection of quality characteristics that are apt to be modelled as functions, which are usually referred to as proles. At the same time, measurements of concurrent variables, which are related to the quality characteristic proles, are often available in a functional form as well, and usually referred to as covariates. In order to adjust the monitoring of the quality characteristic proles by the eect of this additional information, a new functional control chart is elaborated on the residuals obtained from a function-on-function linear regression of the quality characteristic prole on the functional covariates. Furthermore, by means of a Monte Carlo simulation study, the performance of the proposed control chart are compared with those of other charts proposed in the literature. Eventually, a real-case study in the shipping industry is presented with the purpose of monitoring ship fuel consumption and thus, CO 2 emissions from a Ro-Pax ship, with particular regard to detecting CO 2 emission reduction after a specic energy eciency initiative.
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