Phenomenological Model of Magnetocaloric Effect in La<Subscript>0.7</Subscript>Ca<Subscript>0.2</Subscript>Ba<Subscript>0.1</Subscript>MnO<Subscript>3</Subscript> Manganite Around Room Temperature

In this work, we studied in detail the magnetic and magnetocaloric properties of the La_0.7Ca_0.2Ba_0.1MnO₃ compound according to the phenomenological model. Based on this model, the magnetocaloric parameters such as the maximum of the magnetic entropy change ΔS _M and the relative cooling power (RCP) have been determined from the magnetization data as a function of temperature at several magnetic fields. The theoretical predictions are found to closely agree with the experimental measurements, which make our sample a suitable candidate for refrigeration near room temperature. In addition, field dependences of \({{\Delta } S}_{\mathrm {M}}^{\max }\) and RCP can be expressed by the power laws \({\Delta S}_{\mathrm {M}}^{\max }\approx a\)(μ ₀ H) ⁿ and RCP ≈b(μ ₀ H) ^m , where a and b are coefficients and n and m are the field exponents, respectively. Moreover, phenomenological universal curves of entropy change confirm the second-order phase transition.     

The use of fuzzy logic and neural networks models for sensory properties prediction from process and structure parameters of knitted fabrics

In a competitive business environment, the textile industrialists intend to propose diversified products according to consumers preference. For this purpose, the integration of sensory attributes in the process parameters choice seems to be a useful alternative. This paper provides fuzzy and neural models for the prediction of sensory properties from production parameters of knitted fabrics. The prediction accuracy of these models was evaluated using both the root mean square error (RMSE) and mean relative percent error (MRPE). The results revealed the models ability to predict tactile sensory attributes based on the production parameters. The comparison of the prediction performances showed that the neural models are slightly powerful than the fuzzy models.     

ERP data sharing framework using the Generic Product Model (GPM)

Nowadays, all product life cycle processes are investigated deeply in order to get an advantage over competitors. To support these processes, several software applications are available. However, this wide range of heterogeneous applications leads to a large variety of hardware and operating systems, data management software, data models, schemas, and data semantics that hinder the information sharing process. To tackle this problem, Hitachi Company has developed a modeling language called Generic Product Model (GPM) in addition to several translators from native formats to GPM for storing, sharing and visualizing product data in a single data warehouse. In order to broaden the range of application data able to be stored and shared using the GPM data warehouse, this paper presents a methodology and a translator that allow management data to be included in a GPM data warehouse. Given the fact that most management data are stored in Enterprise Resource Planning (ERP) software, and that the latter allows extraction of database contents into Excel files, we propose a translator that handles Enterprise Resource Planning management data that are already extracted into Excel Format.The proposed framework enables data management contained in flat Excel Files to be translated into structured GPM data. Translation methodologies are given for the translation of mass production and customized product data through two case studies, one in the computer retail sector and the other in the extrusion machine industry.     

Effects of Bismuth Doping on the Physical Properties of La0.6−x Bi x Sr0.4CoO3 (0≤x≤0.15) Cobaltites

The structural and magnetic properties of cobaltites with the nominal composition La_0.6?x Bi _x Sr_0.4CoO₃ (0≤x≤0.15) have been investigated. X-ray diffraction analysis using Rietveld refinement show that all our samples crystallize in the rhombohedral structure. The zero field cooled (ZFC) and field cooled (FC) magnetization curves at 50 mT exhibits thermomagnetic irreversibility signature of short range ferromagnetic interactions in our samples. The ferromagnetic–paramagnetic transition temperature decreases with increasing Bi amount. In the paramagnetic phase, all our synthesized samples obey to the Curie–Weiss law. The Curie–Weiss analysis suggests that the spin state of Co³⁺ is IS while Co⁴⁺ ions are in IS for x=0 and LS for x≥0.05. The Bi doping also leads to a weakening in the magnetic moment. The magnetic entropy change exhibits a maximum value which decreases from 2.28 J/kg?K for x=0 to 1.24 J/kg?K for x=0.15 upon a magnetic field change of 5 T.     

Theoretical Investigation of Magnetocaloric Effect in La0.6Ca0.2Ba$_{0.15}\square _{0.05}$MnO3 Manganite

In this paper, the prediction of the magnetocaloric properties has been investigated in the La_0.6Ca_0.2Ba\(_{\mathrm {0.15}}\square _{\mathrm {0.05}}\)MnO₃ system near the ferromagnetic-paramagnetic phase transition as a function of temperature. The data indicate that the La_0.6Ca_0.2Ba\(_{\mathrm {0.15}}\square _{\mathrm {0.05}}\)MnO₃ system has potential application for magnetic refrigerants in an extended high-temperature range. In addition, the magnetic entropy change distribution is quite uniform, which is desirable for an Ericsson cycle magnetic refrigerator.     

Magnetocaloric Effect in Different Impurity Doped La0.67Ca0.33MnO3 Composite

In this paper, we investigate the effect of nonmagnetic YSZ and magnetic Fe₃O₄ addition on the magnetocaloric properties of the La_0.67Ca_0.33MnO₃ composite. The temperature dependences of the magnetization for pure LCMO and the impurity doped LCMO composite upon 0.1, 0.3, and 1 T magnetic field were simulated. By the help of the phenomenological model, magnetic entropy change and specific heat for magnetic field variation are predicted. The values of maximum magnetic entropy change, full-width at half-maximum, and relative cooling power were calculated at several magnetic fields. The ΔS _M value is 2.45, 2.39, and 5.58 J?kg^?1?K^?1 at 1 T for pristine LCMO, LCMO/YSZ, and LCMO/Fe₃O₄, respectively.     

Magnetocaloric Effect in LaFe10.7Co0.8Si1.5 Compound Near Room Temperature

Magnetocaloric properties of LaFe_10.7Co_0.8Si_1.5 with the cubic NaZn₁₃-type structure were investigated around their Curie temperature T _C . By the help of the phenomenological model, the magnetization curves for LaFe_10.7Co_0.8Si_1.5 at several magnetic fields were simulated. The magnetic entropy change and specific heat are obtained. The values of maximum magnetic entropy change, full-width at half-maximum, and relative cooling power, at several magnetic field variation, were calculated. It is shown that for LaFe_10.7Co_0.8Si_1.5 the magnetic entropy change follows an asymmetrical broadening of ΔS _M peak with increasing field. The maximum magnetic entropy change of this compound is 7.10 JK^?1?kg^?1 and relative cooling power is 201.37 J/K under a magnetic field of 2 T. The magnetocaloric effect of this material is large and tunable, suggesting a possible technical application of the material at moderate magnetic fields near room temperature.     

Multi-criteria decision making in workforce choice using AHP,WSM and WPM

This paper focuses on the implementation of Multi-Criteria Decision Making (MCDM) methods to evaluate the workforce competence in apparel industry. In this study, the Analytic Hierarchy Process (AHP), the Weighted Sum Model (WSM) and the Weighted Product Model (WPM) are suggested to solve workforce selection problem. The use of these methods is expected to help choose the best operator among several alternatives. Based on three criteria, each worker is evaluated in each executed operation. The criteria are a Quality Index ‘QI’, an Activity ‘A’ and an Attendance Rate ‘AR’. Thanks to the MCDM methods, scores allowing an objective classification of operators are obtained. Experimental results on AHP, WSM and WPM methods show the same decisions with the same workers’ classification from the best to the worst alternative. The resulting database contributes to the line balancing optimization by choosing for each operation, and as far as possible, the most competent operator.