An integrated approach to remanufacturing: model of a remanufacturing system

Remanufacturing is the process of rebuilding used products that ensures that the quality of remanufactured products is equivalent to that of new ones. Although the theme is gaining ground, it is still little explored due to lack of knowledge, the difficulty of visualizing it systemically, and implementing it effectively. Few models treat remanufacturing as a system. Most of the studies still treated remanufacturing as an isolated process, preventing it from being seen in an integrated manner. Therefore, the aim of this work is to organize the knowledge about remanufacturing, offering a vision of remanufacturing system and contributing to an integrated view about the theme. The methodology employed was a literature review, adopting the General Theory of Systems to characterize the remanufacturing system. This work consolidates and organizes the elements of this system, enabling a better understanding of remanufacturing and assisting companies in adopting the concept.

Model-based reuse for crosscutting frameworks: assessing reuse and maintenance effort

Abstract Background Over the last years, a number of researchers have investigated how to improve the reuse of crosscutting concerns. New possibilities have emerged with the advent of aspect-oriented programming, and many frameworks were designed considering the abstractions provided by this new paradigm. We call this type of framework Crosscutting Frameworks (CF), as it usually encapsulates a generic and abstract design of one crosscutting concern. However, most of the proposed CFs employ white-box strategies in their reuse process, requiring two mainly technical skills: (i) knowing syntax details of the programming language employed to build the framework and (ii) being aware of the architectural details of the CF and its internal nomenclature. Also, another problem is that the reuse process can only be initiated as soon as the development process reaches the implementation phase, preventing it from starting earlier. Method In order to solve these problems, we present in this paper a model-based approach for reusing CFs which shields application engineers from technical details, letting him/her concentrate on what the framework really needs from the application under development. To support our approach, two models are proposed: the Reuse Requirements Model (RRM) and the Reuse Model (RM). The former must be used to describe the framework structure and the later is in charge of supporting the reuse process. As soon as the application engineer has filled in the RM, the reuse code can be automatically generated. Results We also present here the result of two comparative experiments using two versions of a Persistence CF: the original one, whose reuse process is based on writing code, and the new one, which is model-based. The first experiment evaluated the productivity during the reuse process, and the second one evaluated the effort of maintaining applications developed with both CF versions. The results show the improvement of 97% in the productivity; however little difference was perceived regarding the effort for maintaining the required application. Conclusion By using the approach herein presented, it was possible to conclude the following: (i) it is possible to automate the instantiation of CFs, and (ii) the productivity of developers are improved as long as they use a model-based instantiation approach.

A stochastic spatially structured epidemic model with diffusive processes

We developed a stochastic lattice model to describe the vector-borne disease (like yellow fever or dengue). The model is spatially structured and its dynamical rules take into account the diffusion of vectors. We consider a bipartite lattice, forming a sub-lattice of human and another occupied by mosquitoes. At each site of lattice we associate a stochastic variable that describes the occupation and the health state of a single individual (mosquito or human). The process of disease transmission in the human population follows a similar dynamic of the Susceptible-Infected-Recovered model (SIR), while the disease transmission in the mosquito population has an analogous dynamic of the Susceptible-Infected-Susceptible model (SIS) with mosquitos diffusion. The occurrence of an epidemic is directly related to the conditional probability of occurrence of infected mosquitoes (human) in the presence of susceptible human (mosquitoes) on neighborhood. The probability of diffusion of mosquitoes can facilitate the formation of pairs Susceptible-Infected enabling an increase in the size of the epidemic. Using an asynchronous dynamic update, we study the disease transmission in a population initially formed by susceptible individuals due to the introduction of a single mosquito (human) infected. We find that this model exhibits a continuous phase transition related to the existence or non-existence of an epidemic. By means of mean field approximations and Monte Carlo simulations we investigate the epidemic threshold and the phase diagram in terms of the diffusion probability and the infection probability.

Stochastic quantization of the spherical model and supersymmetry.

In this work, we reported some results about the stochastic quantization of the spherical model. We started by reviewing some basic aspects of this method with emphasis in the connection between the Langevin equation and the supersymmetric quantum mechanics, aiming at the application of the corresponding connection to the spherical model. An intuitive idea is that when applied to the spherical model this gives rise to a supersymmetric version that is identified with one studied in Phys. Rev. E 85, 061109, (2012). Before investigating in detail this aspect, we studied the stochastic quantization of the mean spherical model that is simpler to implement than the one with the strict constraint. We also highlight some points concerning more traditional methods discussed in the literature like canonical and path integral quantization. To produce a supersymmetric version, grounded in the Nicolai map, we investigated the stochastic quantization of the strict spherical model. We showed in fact that the result of this process is an off-shell supersymmetric extension of the quantum spherical model (with the precise supersymmetric constraint structure). That analysis establishes a connection between the classical model and its supersymmetric quantum counterpart. The supersymmetric version in this way constructed is a more natural one and gives further support and motivations to investigate similar connections in other models of the literature.

Experimental model identification of open-frame underwater vehicles

Most of the works published on hydrodynamic parameter identification of open-frame underwater vehicles focus their attention almost exclusively on good coherence between simulated and measured responses, giving less importance to the determination of “actual values” for hydrodynamic parameters. To gain insight into hydrodynamic parameter experimental identification of open-frame underwater vehicles, an experimental identification procedure is proposed here to determine parameters of uncoupled and coupled models. The identification procedure includes: (i) a prior estimation of actual values of the forces/torques applied to the vehicle, (ii) identification of drag parameters from constant velocity tests and (iii) identification of inertia and coupling parameters from oscillatory tests; at this stage, the estimated values of drag parameter obtained in item (ii) are used. The procedure proposed here was used to identify the hydrodynamic parameters of LAURS—an unmanned underwater vehicle developed at the University of São Paulo. The thruster–thruster and thruster–hull interactions and the advance velocity of the vehicle are shown to have a strong impact on the efficiency of thrusters appended to open-frame underwater vehicles, especially for high advance velocities. Results of tests with excitation in 1-DOF and 3-DOF are reported and discussed, showing the feasibility of the developed procedure.

Changes in renal glucose transporters in an animal model of metabolic syndrome

Considering the similarity between structural, hemodynamic, and functional changes of obesity-related renal disease and diabetic nephropathy, we hypothesized that renal glucose transporter changes occur in obesity as in diabetes. The aim of the work was to evaluate GLUT1 and GLUT2 in kidneys of an animal model of metabolic syndrome. Neonate spontaneously hypertensive rats (SHR), n=15/group, were treated with monosodium glutamate (5 mg/g) (MetS) for 9 days and compared with saline-treated Wistar-Kyoto (C) and SHR (H) rats. Lee index, systolic arterial pressure (SAP), glycemia, insulin resistance, triglycerides, and HDL cholesterol were evaluated at 3 and 6 months. Medullar GLUT1 and cortical GLUT2 were analyzed by Western blot. MetS vs. C and H rats had the highest Lee index (p<0.001) and insulin resistance (3-months C: 4.3±0.7, H: 3.9±0.9, MetS: 2.7±0.6; 6-months C: 4.2±0.6, H: 3.8±0.5, MetS: 2.4±0.6% • min−1, p<0.001), similar glycemia, and the lowest HDL-cholesterol at 6-months (p<0.001). In the MetS and H rats, SAP was higher vs. C at 3-months (p<0.001) and 6-months (C: 151±15, H: 190±11, MetS: 185±13 mm Hg, p<0.001) of age. GLUT1 was ̴ 13× lower (p<0.001) at 3-months, reestablishing its content at 6-months in MetS group, while GLUT2 was 2× higher (p<0.001) in this group at 6-months of age. Renal GLUT1 and GLUT2 are modulated in kidney of rats with metabolic syndrome, where obesity, insulin resistance and hypertension coexist, despite normoglycemia. Like in diabetes, cortical GLUT2 overexpression may contribute to the development of kidney disease

Numerical simulation of an ethanol turbulent spray flame with RANS and diffusion combustion model

A detailed numerical simulation of ethanol turbulent spray combustion on a rounded jet flame is pre- sented in this article. The focus is to propose a robust mathematical model with relatively low complexity sub- models to reproduce the main characteristics of the cou- pling between both phases, such as the turbulence modulation, turbulent droplets dissipation, and evaporative cooling effect. A RANS turbulent model is implemented. Special features of the model include an Eulerian– Lagrangian procedure under a fully two-way coupling and a modified flame sheet model with a joint mixture fraction– enthalpy b -PDF. Reasonable agreement between measured and computed mean profiles of temperature of the gas phase and droplet size distributions is achieved. Deviations found between measured and predicted mean velocity profiles are attributed to the turbulent combustion modeling adopted