Biagio Palumbo

A Statistical Approach to Ship Fuel Consumption Monitoring

The reduction of the environmental impact imposed by Kyoto Protocol and the growth of competitiveness imposed by the shipping market have urged shipping companies to pay increasing attention to ship energy efficiency improvement and CO2 emission reduction. According to the Ship Energy Efficiency Management Plan (SEEMP) recommended by the International Maritime Organization (IMO), the main scope of this article is in fact to overcome the deterministic limits of the monitoring systems installed in modern ships and support technical management in decision making based on large navigation databases. The proposed statistical approach is founded on a multiple linear regression and allows for both pointwise and interval predictions of the fuel consumption. At the end of each voyage, the model can be used to alert management for a possible change in ship performance in all those situations where the actual fuel consumption lies outside the prediction interval. Moreover, the model can also be utilized to quantify the contribution to the fuel consumption due to the hull and propeller fouling, which is particularly profitable for shipping companies and operators to claim for carbon credits after a specific improvement operation.

Technological scenarios of variation transmission in multistage machining processes

The study of variation transmission in multistage machining processes is a strategic task. It enables us to understand how variation is added and transmitted across the process stages and, therefore, to identify opportunities to reduce variation in key characteristics at the final stage. In this paper, a data-driven technique, based on a first-order autoregressive model, is applied to a multistage machining process of an aero-engine component. Data on 15 key characteristics of 42-tracked components are taken at each of eight sequential process stages. The statistical analysis of data relative to critical key characteristics permits determining the quantity of variation that is added at each stage and the quantity that is transmitted from upstream. This differentiation between added and transmitted variation allows the discovery of which stages contribute most to variation of key characteristics at the final stage. The statistical and technological interpretation of results enables identifying three typical technological scenarios that affect multistage machining process. The knowledge of the variance transmission modalities related to each scenario is a winning factor in achieving quality improvement and cost reduction. It has a direct influence on the effectiveness of variation reduction efforts and may provide useful information to define manufacturing cycles or to select machining tolerances. The application proposed has been developed in the AVIO industry, an international aerospace company at the leading edge of propulsion technology. Copyright

Technological Process Innovation via Engineering and Statistical Knowledge Integration

This chapter shows the strategic role that a systematic approach to planning for a designed industrial experiment plays in technological process innovation. Guidelines already proposed in the literature emphasizing the pre-experimental planning phase are customized and applied in a case study concerning the laser drilling process of a combustion chamber in aerospace industry. The team approach is the real driving force for pre-experimental activities; it enables the integration of engineering and statistical knowledge, catalyzes process innovation and, moreover, it allows a virtuous cycle of sequential learning to be put into action. The innovative technological results obtained in the first screening experimental phase are presented. Since these results arise from a sound systematic approach, they enable a future experimental phase on optimization and robustness to be planned. The case study of a laser drilling process provides a best-practice guide to synergic collaboration and partnership between academic statisticians and industrial practitioners; it was developed by AVIO, an aerospace company at the leading edge of propulsion technology.

New Insights into the Decisional Use of Process Capability Indices via Hypothesis Testing

Process capability indices Cp, Cpk, and Cpm are still nowadays widely used in industry—thanks to their easy formulation and implementation. This paper aims to give new mathematical insights in order to support their use in decision-making via hypothesis testing. The minimum sample size usually needed in the applications to achieve fixed significance level and power is reported in light of the new mathematical aspects for Cpk and Cpm, which avoid misleading conclusions and the use of extensive numerical experiments. In addition, power curves for Cpk and Cpm, which have not previously appeared in the literature before, are also presented. Lastly, easy-to-follow diagrams for hypothesis testing with Cpk and Cpm and two critical scenarios for Cpm are included in the paper to facilitate the applicative use and the comprehension of the novel inferential aspects. Copyright

A Procedure for Predicting and Controlling the Ship Fuel Consumption: Its Implementation and Test

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

The performance of semi-empirical Bayesian control charts for monitoring Weibull data

Abstract In this paper we investigate the performance of semi-empirical Bayesian control charts to monitor the percentiles and the shape parameter of a Weibull distribution. These charts have been recently introduced in literature, where it is shown how Weibull-distributed data need specifically designed control schemes and how a Bayesian approach can help in such cases. The main focus of this paper, instead, is a simulation study of the charts’ performance. To this aim, a large Monte Carlo analysis is presented, highlighting the main effects on the chart performance of single/combined changes in the Weibull parameters. Some Weibull contour plots are presented to visualize the investigated technological scenarios. An illustrative example using a reference data-set is included too.

Tensile Properties Characterization of AlSi10Mg Parts Produced by Direct Metal Laser Sintering via Nested Effects Modeling

A statistical approach for the characterization of Additive Manufacturing (AM) processes is presented in this paper. Design of Experiments (DOE) and ANalysis of VAriance (ANOVA), both based on Nested Effects Modeling (NEM) technique, are adopted to assess the effect of different laser exposure strategies on physical and mechanical properties of AlSi10Mg parts produced by Direct Metal Laser Sintering (DMLS). Due to the wide industrial interest in AM technologies in many different fields, it is extremely important to ensure high parts performances and productivity. For this aim, the present paper focuses on the evaluation of tensile properties of specimens built with different laser exposure strategies. Two optimal laser parameters settings, in terms of both process quality (part performances) and productivity (part build rate), are identified.

Experimental investigation on CFRP milling by low power Q-switched Yb:YAG laser source

In the present study, laser milling of CFRP plate by means of a 30W Q-Switched Yb:YAG fiber laser is investigated through statistical analysis. Milling tests were performed at the nominal power changing the pulse power; the scanning speed, the hatch distance and the released energy. Design of Experiments (DoE) and ANalysis Of VAriance (ANOVA) were applied with the aim to improve the process performances in term of material removal rate and heat affected zone extension. The results show that, the adopted laser is an effective solution for the CFRP milling. Moreover, adopting an accurate approach to the problem, process variability and material damages can be easily reduced.

A robust calibration methodology for an on-board diagnostic car system:

New car models are now by law equipped with on-board diagnostic (OBD) systems aimed at monitoring the state of health of strategic components that ensure low levels of polluting exhaust emissions. During development phases, for each new car model, the OBD system must be finely calibrated. This article presents a robust calibration methodology taking into account sources of variability mainly due to production process, operating, and environmental conditions. The methodology enables us to evaluate the false alarm and failure to detect risks intrinsically related to the adopted calibration. An application concerning an upstream oxygen sensor monitored by the OBD is presented.

A note on decision making method for product acceptance based on process capability indices Cpk and Cpmk

Abstract In this short note, we prove that the derivation of the required sample size and critical acceptance value under the normality assumption of the quality characteristic proposed by Wu, C. W., Aslam, M., & Jun, C. H. (2012). Variables sampling inspection scheme for resubmitted lots based on the process capability index C pk . European Journal of Operational Research, 217(3), 560–566, is inappropriate. In fact, it leads to a lower probability of acceptance than the one desired by the producer. The same issue also occurs in the case of a variables single sampling plan described in a previous paper by Pearn, W. L., & Wu, C. W. (2007). An effective decision making method for product acceptance. Omega, 35(1), 12–21. Nevertheless, a similar yet less severe inaccuracy is also noticed in Wu, C. W., & Pearn, W. L. (2008). A variables sampling plan based on C pmk for product acceptance determination. European Journal of Operational Research, 184(2), 549–560.