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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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Abstract. We prove some monotonicity results for the incomplete gamma function,from which some inequalities for Γ(a, x) follow.Mathematics subject classification (1991): 33B15.

In light of the International Maritime Organization guidelines, the new Regulation of the European Union urges shipping companies to set up a system for monitoring, reporting and verification of CO2 emissions based on ship fuel consumption. However, in nowadays market, there is a lack of techniques for fuel consumption monitoring that can be adopted in a real environment. The proposed procedure overcomes the use of Speed–Power curves, which are commonly utilized in the Naval Architecture, by means of a multiple linear regression model that exploits the navigation information usually available in modern ships. This procedure can be used both to alert technical management of a shipping company for anomalous fuel consumption and to quantify the fuel consumption reduction connected with any specific policy adopted to improve energy efficiency. Therefore, this can be particularly profitable for shipping companies and operators in order to claim for carbon credits. The proposed approach is currently implemented by the Energy Saving Technical Department of the Grimaldi Group on a Ro‐Ro Pax ship. Copyright © 2015 John Wiley & Sons, Ltd.