196,334 research outputs found
Binary Gaussian Process classification of quality in the production of aluminum alloys foams with regular open cells
No full textAluminum alloys foams with homogeneous and regular open cells have been frequently proposed and used as support structures for catalytic applications. In this kind of application, the quality of produced metal foam assumes primary importance. This paper presents an application of a classifier algorithm to predict quality in the manufacturing process of aluminum alloy foams with homogeneous and regular open cells. A data analysis methodology of experimental data, which is based on Binary Gaussian Process Classification, is presented. The proposed method is a Bayesian classification method, which gets away from any assumptions about the relationship between process inputs (the geometric design parameters of the regular unit cells) and process output (probability to obtain defective foam). We demonstrate that the proposed methodology can provide an effective tool to derive a model for the prediction of quality. An investment casting process, via 3D printing of wax patterns, is considered throughout the paper. Despite this specific case study, the methodology can be exploited in different processes in which the assumptions of traditional statistical approaches could not be easily verified, e.g., additive manufacturing
Logistic Regression and Response Surface Design for Statistical Modeling of Investment Casting Process in Metal Foam Production
No full textA metal foam represents a promising material since it keeps the high mechanical properties of the metal while reducing the weight up to 90%. Among several manufacturing processes, the investment casting is a foundry process flexible enough to be suitable both for stochastic and for regular foams. This paper presents an experimental determination of the manufacturing process of metal regular foams by investment casting. The goal is to derive experimentally an actual formability map. The use of logistic regression and response surface design is proposed as an effective tool for determining a statistical model of the metal foam casting process
Detecting Changes in Autoregressive Processes with a Recurrent Neural Network for Manufacturing Quality Monitoring
No full textThe traditional use of control charts assumes the independence of data. It is widely recognized that many processes are autocorrelated thus violating the main assumption of independence. As a result, there is a need for a broader approach to quality monitoring when data are time-dependent or autocorrelated. The aim of this work is to present a new procedure for manufacturing process quality control in the case of serially correlated data. In particular, a recurrent neural network is introduced for quality control problem. Performance comparisons between the neural-based algorithm and control charts are also presented in the paper in order to validate the proposed approach. The simulation results indicate that the neural-based procedure is quite effective as it achieves improved performance over control charts
Modeling the Egyptian Path to Energy Efficiency towards 2035
No full textThis paper offers a tool to evaluate the implementation of energy efficiency actions for the residential sector with a focus on Egypt which adopted a path to achieve 8.6 Mtoe energy savings through 2035. The Country has been divided in climate zones and users classified according to the kind of their typical household in the cities and in the rural areas. The National Energy Efficiency Plan (NEEP) has been taken as a reference, technologies' improvement has been evaluated in terms of savings and costs and a plan from 2017 through 2035 has been detailed by the means of an easy-to-use optimization model. The novelty lies in offering this model a tool allowing an analysis where to spot possible bottlenecks but also hidden potentials in the targeted users, among which photovoltaic for residential applications
Energy conversion systems: the case study of compressed air, an introduction to a new simulation toolbox
No full textThe paper illustrates the simulation activities going on within
the LABAC (laboratory of energy performance of compressed
air systems) at the University of Pavia. The scope is to build
up a simulator, based on a comprehensive energy model, en-
abling the end-user both to improve the system efficiency, al-
lowing modifications on the system configuration and/or the
use of alternative devices, and to properly size a pneumatic
network. The final use is both for educational and test pur-
pose. The simulator represents the laboratory plant, where the
generation unit, the receiver, the cleaning up equipment and
the distribution of compressed air are set in place. For the
modeling, the Xcos application, graphical Scilab interface,
has been used; to emphasize the potential derived by the use
of this simulator, the role of increasing storage unit/receiver
is investigated with respect to the system energy consump-
tion. Several testings have been performed. The simulation
reported in this paper has been carried out for 4000 s and two
different configurations are investigated: the living one with
0.5 m3 vs. the alternative 6.5 m3 storage tank. A detailed ap-
proach to the identification of all equipment is proposed and
energy and power considerations are reported
Fenomeni epigenetici nella regoalzione tessuto specifica e loro ruolo nella eziopatogenesi delle patologie acquisite
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