1,721,108 research outputs found
Promoting electric vehicle demand in Europe: Design of innovative electricity consumption simulator and subsidy strategies based on well-to-wheel analysis
No full textDecarbonization in the transport sector, especially in private mobility, is one of the main objectives of the European Union (EU) for next few years. Battery electric vehicles (BEVs) represent a promising solution for reducing pollution and GHG emissions; however, their purchase price contributes to curbing their diffusion. In this scenario, the aims of this study are to develop a flexible, simulation-based analysis for EU car fleets in terms of energy consumption and GHG emissions and, based on the simulation results, to propose an innovative system of financial subsidies. This can support governments in encouraging EU customers to prefer sustainable and green options for mobility. Different car segments have been considered; the electrical energy consumptions have been obtained through the development of an ad-hoc simulation model in Simulink®-MathWorks environment, while the Well-To-Wheel analysis has been performed to estimate GHG emissions. Based on these assumptions, four different subsidy strategies have been proposed and designed for countries of the EU-27. According to different logics, economic subsidies have been linked to GHG emissions avoided thanks to the use of BEVs. The results obtained show how BEVs’ consumption of electricity is low, even for larger vehicles, and this allows BEVs to be considered less impactful than internal combustion engine vehicles (ICEV) with respect to GHG emissions. Furthermore, results are highly variable, depending on the electricity mix of each considered country, and they show how, for the countries that use the most renewable sources, the proposed subsidies even can generate gains from consumers’ perspectives
Regression models for multivariate ordered responses via the Plackett distribution
No full textAbstractWe investigate the properties of a class of discrete multivariate distributions whose univariate marginals have ordered categories, all the bivariate marginals, like in the Plackett distribution, have log-odds ratios which do not depend on cut points and all higher-order interactions are constrained to 0. We show that this class of distributions may be interpreted as a discretized version of a multivariate continuous distribution having univariate logistic marginals. Convenient features of this class relative to the class of ordered probit models (the discretized version of the multivariate normal) are highlighted. Relevant properties of this distribution like quadratic log-linear expansion, invariance to collapsing of adjacent categories, properties related to positive dependence, marginalization and conditioning are discussed briefly. When continuous explanatory variables are available, regression models may be fitted to relate the univariate logits (as in a proportional odds model) and the log-odds ratios to covariates
The role of Industry 4.0 enabling technologies for safety management: A systematic literature review
Full text linkInnovations introduced during the Industry 4.0 era consist in the integration of the so called "nine pillars of technologies" in manufacturing, transforming the conventional factory in a smart factory. The aim of this study is to investigate enabling technologies of Industry 4.0, focusing on technologies that have a greater impact on safety management. Main characteristics of such technologies will be identified and described according to their use in an industrial environment. In order to do this, we chose a systematic literature review (SLR) to answer the research question in a comprehensively way. Results show that articles can be grouped according to different criteria. Moreover, we found that Industry 4.0 can increase safety levels in warehouse and logistic, as well as several solutions are available for building sector
Testing for Asymmetric Information in Insurance Markets: A Multivariate Ordered Regression Approach
No full textThe positive correlation (PC) test is the standard procedure used in the empirical literature to detect the existence of asymmetric information in insurance markets. This article describes a new tool to implement an extension of the PC test based on a new family of regression models, the multivariate ordered logit, designed to study how the joint distribution of two or more ordered response variables depends on exogenous covariates. We present an application of our proposed extension of the PC test to the Medigap health insurance market in the United States. Results reveal that the risk–coverage association is not homogeneous across coverage and risk categories, and depends on individual socioeconomic and risk preference characteristics
AHP-TOPSIS model to evaluate maintenance strategy using RAMS and production parameters
No full textThe focus of the present research concerns a maintenance strategy selection model. An integrated approach is proposed, able to match Analytic Hierarchy Process (AHP) with Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) for the evaluation of maintenance policy, in order to improve production performance and to reduce cost organization. The proposed model has been applied in a real case study of a textile industry. Different maintenance alternatives were considered and different criteria and sub-criteria were evaluated using Reliability, Availability, Maintainability, Safety (RAMS) and production parameters. The results suggest the best maintenance solution for all machines in the analyzed textile process. The model has also been tested, by performing a sensitivity analysis, where the weight of each criterion has been varied. The proposed technique is based on general parameters and for this reason can be used in different industrial fields to select proper maintenance strategies. The results and the satisfaction of management derived by using the proposed method confirms how AHP-TOPSIS methodology represents an effective approach to arrive at best maintenance selection in order to reduce Maintenance Cost and increase System Availability
Environmental Analysis Based on Life Cycle Assessment: An Empirical Investigation on the Conventional and Hybrid Powertrain
No full textThe Life Cycle Sustainability Assessment (LCA) methodology is today considered as a crucial paradigm with multiple levels of analysis, including the economic, social and environmental aspects. In this scenario, the purpose of the present research is to carry out an accurate and extensive LCA based analysis to compare the environmental impact, between conventional gasoline and hybrid vehicle powertrains. Two different powertrain scenarios were considered maintaining the same vehicle chassis. The performed analysis concerned resources and energy consumption as well as pollutant emission of each process, evaluating the impact of powertrain production, the vehicle use phase, and powertrain end of life scenarios. A large set of indicators-including human toxicity, eutrophication, and acidification-was considered. The study indicates that the potential of electrified vehicles basically depends on efficient production and recycling of the battery. We found that the conventional powertrain determines a higher Global Warming Potential (GWP) than hybrid powertrain (by almost 30%). Conversely, the water-related impact is higher in hybrid powertrain, and this is associated to the extraction and processing of the metal and mischmetal within the battery pack. Furthermore, the incidence of transport in the use phase for the conventional powertrain has high impact related to freshwater and marine aquatic ecotoxicity
Enabling technology for maintenance in a smart factory: A literature review
Full text linkIndustry 4.0 technologies are transforming the factory in an "intelligent" or "smart" factory. In a such context, a greater efficiency and innovative relationship is basically demanded within the whole production chain, including suppliers, producers, and customers.To be more competitive, companies are becoming increasingly aware that maintenance plays a key role during the digital transformation from the perspective of both technology and management. In this work, we perform a literature review of published cases to investigate how maintenance is changing through technologies of Industry 4.0 currently used in maintenance. We found 34 papers in literature involved in analyzing relations between maintenance and Industry 4.0 technology. The analysis of such studies let us to establish the current technology state-of-art and identify the most suited technology that today is employed in maintenance tasks. In particular Industrial Internet of Things and Cloud Computing are more common in the analyzed studies, confirming how these concepts and technologies are at the basis of Industry 4.0 (C) 2021 The Authors. Published by Elsevier B.V
Marginal parameterizations of discrete models defined by a set of conditional independencies
No full textAbstractIt is well-known that a conditional independence statement for discrete variables is equivalent to constraining to zero a suitable set of log–linear interactions. In this paper we show that this is also equivalent to zero constraints on suitable sets of marginal log–linear interactions, that can be formulated within a class of smooth marginal log–linear models. This result allows much more flexibility than known until now in combining several conditional independencies into a smooth marginal model. This result is the basis for a procedure that can search for such a marginal parameterization, so that, if one exists, the model is smooth
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