Finite Element Analysis (FEA) applied to heat transfer optimization process of pultrusion die systems

The aim of this study is to optimize the heat flow through the pultrusion die assembly system on the manufacturing process of a specific glass-fiber reinforced polymer (GFRP) pultrusion profile. The control of heat flow and its distribution through whole die assembly system is of vital importance in optimizing the actual GFRP pultrusion process. Through mathematical modeling of heating-die process, by means of Finite Element Analysis (FEA) program, an optimum heater selection, die position and temperature control was achieved. The thermal environment within the die was critically modeled relative not only to the applied heat sources, but also to the conductive and convective losses, as well as the thermal contribution arising from the exothermic reaction of resin matrix as it cures or polymerizes from the liquid to solid condition. Numerical simulation was validated with basis on thermographic measurements carried out on key points along the die during pultrusion process.

Optimization process of polyester polymer mortars modified with recycled GFRP waste aggregates – application of factorial experiment design-

Glass fibre-reinforced plastics (GFRP), nowadays commonly used in the construction, transportation and automobile sectors, have been considered inherently difficult to recycle due to both: cross-linked nature of thermoset resins, which cannot be remolded, and complex composition of the composite itself, which includes glass fibres, matrix and different types of inorganic fillers. Presently, most of the GFRP waste is landfilled leading to negative environmental impacts and supplementary added costs. With an increasing awareness of environmental matters and the subsequent desire to save resources, recycling would convert an expensive waste disposal into a profitable reusable material. There are several methods to recycle GFR thermostable materials: (a) incineration, with partial energy recovery due to the heat generated during organic part combustion; (b) thermal and/or chemical recycling, such as solvolysis, pyrolisis and similar thermal decomposition processes, with glass fibre recovering; and (c) mechanical recycling or size reduction, in which the material is subjected to a milling process in order to obtain a specific grain size that makes the material suitable as reinforcement in new formulations. This last method has important advantages over the previous ones: there is no atmospheric pollution by gas emission, a much simpler equipment is required as compared with ovens necessary for thermal recycling processes, and does not require the use of chemical solvents with subsequent environmental impacts. In this study the effect of incorporation of recycled GFRP waste materials, obtained by means of milling processes, on mechanical behavior of polyester polymer mortars was assessed. For this purpose, different contents of recycled GFRP waste materials, with distinct size gradings, were incorporated into polyester polymer mortars as sand aggregates and filler replacements. The effect of GFRP waste treatment with silane coupling agent was also assessed. Design of experiments and data treatment were accomplish by means of factorial design and analysis of variance ANOVA. The use of factorial experiment design, instead of the one factor at-a-time method is efficient at allowing the evaluation of the effects and possible interactions of the different material factors involved. Experimental results were promising toward the recyclability of GFRP waste materials as polymer mortar aggregates, without significant loss of mechanical properties with regard to non-modified polymer mortars.

Optimization of the Pultrusion process

Manufacturing processes need permanently to innovate and optimize because any can be susceptible to continuous improvement. Innovation and commitment to the development of these new solutions resulting from existing expertise and the continuing need to increase productivity, flexibility and ensuring the necessary quality of the manufactured products. To increase flexibility, it is necessary to significantly reduce set-up times and lead time in order to ensure the delivery of products ever faster. This objective can be achieved through a normalization of the pultrusion line elements. Implicitly, there is an increase of productivity by this way. This work is intended to optimize the pultrusion process of structural profiles. We consider all elements of the system from the storehouse of the fibers (rack) to the pultrusion die. Particular attention was devoted to (a) the guidance system of the fibers and webs, (b) the resin container where the fibers are impregnated, (c) standard plates positioning of the fibers towards the entrance to the spinneret and also (d) reviewed the whole process of assembling and fixing the die as well as its the heating system. With the implementation of these new systems was achieved a significant saving of time set-up and were clearly reduced the unit costs of production. Quality assurance was also increased.

Millennium BCP: Optimization of the branches closure process

Nowadays, a significant number of banks in Portugal are facing a bank-branch restructuring problem, and Millennium BCP is not an exception. The closure of branches is a major component of profit maximization through the reduction in operational and personnel costs but also an opportunity to approach the idea of “baking of future” and start thinking on the benefits of the digital era. This dissertation centers on a current high-impact organizational problem addressed by the company and consists in a proposal of optimization to the model that Millennium BCP uses. Even though measures of performance are usually considered the most important elements in evaluating the viability of branches, there is evidence suggesting that other general factors can be important to assess branch potential, such as the influx on branches, business dimensions of a branch and its location, which will be addressed in this project.

Optimization of Two Stage Process for the Growth of In2S3 , CuInSe2 and CuIn (Sel-xSx)2Thin Films for Solar Cell Application

Two stage processes consisting of precursor preparation by thermal evaporation followed by chalcogenisation in the required atmosphere is found to be a feasible technique for the PV materials such as n-Beta In2S3, p-CulnSe2, p-CulnS2 and p-CuIn(Sel_xSx)2. The growth parameters such as chalcogenisation temperature and duration of chalcogenisation etc have been optimised in the present study.Single phase Beta-In2S3 thin films can be obtained by sulfurising the indium films above 300°C for 45 minutes. Low sulfurisation temperatures required prolonged annealing after the sulfurisation to obtain single phase Beta-1n2S3, which resulted in high material loss. The maximum band gap of 2.58 eV was obtained for the nearly stoichiometric Beta-In2S3 film which was sulfurised at 350°C. This wider band gap, n type Beta-In2S3 can be used as an alternative to toxic CdS as window layer in photovoltaics .The systematic study on the structural optical and electrical properties of CuInSe2 films by varying the process parameters such as the duration of selenization and the selenization temperature led to the conclusion that for the growth of single-phase CuInSe2, the optimum selenization temperature is 350°C and duration is 3 hours. The presence of some binary phases in films for shorter selenization period and lower selenization temperature may be due to the incomplete reaction and indium loss. Optical band gap energy of 1.05 eV obtained for the films under the optimum condition.In order to obtain a closer match to the solar spectrum it is desirable to increase the band gap of the CulnSe2 by a few meV . Further research works were carried out to produce graded band gap CuIn(Se,S)2 absorber films by incorporation of sulfur into CuInSe2. It was observed that when the CulnSe2 prepared by two stage process were post annealed in sulfur atmosphere, the sulfur may be occupying the interstitial positions or forming a CuInS2 phase along with CuInSe2 phase. The sulfur treatment during the selenization process OfCu11 ln9 precursors resulted in Culn (Se,S)2 thin films. A band gap of 1.38 eV was obtained for the CuIn(Se,S)2.The optimised thin films n-beta 1n2S3, p-CulnSe2 and p-Culn(Sel-xSx)2 can be used for fabrication of polycrystalline solar cells.

Optimization of Process Parameters for the Extraction of Gelatin from the Skin of Freshwater Fish and the Evaluation of Physical anal Chemical Characteristics

Faculty of Marine Sciences,Cochin University of Science and Technology

Elaboration and optimization of (Y,Er)Al(3)(BO(3))(4) glassy planar waveguides through the sol-gel process

In this work, a sol-gel route was used to prepare Y(0.9)Er(0.1)Al(3)(BO(3))(4) glassy thin films by spin-coating technique looking for the preparation and optimization of planar waveguides for integrated optics. The films were deposited on silica and silicon substrates using stable sols synthesized by the sol-gel process. Deposits with thicknesses ranging between 520 and 720 nm were prepared by a multi-layer process involving heat treatments at different temperatures from glass transition to the film crystallization and using heating rates of 2 degrees C/min. The structural characterization of the layers was performed by using grazing incidence X-ray diffraction and Raman spectroscopy as a function of the heat treatment. Microstructural evolution in terms of annealing temperatures was followed by high resolution scanning electron microscopy and atomic force microscopy. Optical transmission spectra were used to determine the refractive index and the film thicknesses through the envelope method. The optical and guiding properties of the films were studied by m-line spectroscopy. The best films were monomode with 620 nm thickness and a refractive index around 1.664 at 980 nm wavelength. They showed good waveguiding properties with high light-coupling efficiency and low propagation loss at 632.8 and 1550 nm of about 0.88 dB/cm. (C) 2009 Elsevier B.V. All rights reserved.

Simulation optimization for process scheduling through simulated annealing

This paper presents a simulation optimization of a real scheduling problem in industry, simulated annealing is introduced for this purpose.  Investigation is performed into the practicality of using simulated annealing to produce high quality schedules.  Results on the solution quality and computational effort show the inherent properties of the simulated annealing.  It is shown that when using this method, high quality schedules can be produced within reasonable time contraints.

Optimization of process parameters for the production of naringinase by Aspergillus niger MTCC 1344

Aspergillus niger MTCC 1344 was used to produce extracellular naringinase in a complex (molasses, yeast extract and salts) medium. An initial medium pH 4.5 and cultivation temperature 30 °C were optimal for enzyme production. Among various carbon and organic nitrogen sources used, molasses and peptone were the most effective for enzyme yield. The rate of enzyme production was enhanced when metal ions were added to the medium. Fermentation conditions are described which produced a higher rate of enzyme synthesis. An increase in initial sugar concentration from 6 to 10 g l⁻¹ in the fermentation medium produced decreased naringinase synthesis while cell mass growth increased with the increase of sugar concentration. At a higher sugar level (10 g l⁻¹) the production of cell mass decreased.

Optimization of medium and process parameters for the production of inulinase from a newly isolated Kluyveromyces marxianus YS-1

A newly isolated strain of Kluyveromyces marxianus YS-1 was used for the production of extra cellular inulinase in a medium containing inulin, meat extract, CaCl₂ and sodium dodecyl sulphate (SDS). Fermentation medium pH 6.5, cultivation temperature 30 °C and 5% (v/v) inoculum of 12 h-old culture were optimal for enzyme production (30.8 IU/ml) with a fermentation time of 72 h at shake flask level. Raw inulin (2%, w/v) extracted from dahlia tubers by processing at 15 kg/cm² for 10 min was optimum for bioreactor studies. Maximum enzyme production (55.4 IU/ml) was obtained at an agitation rate of 200 rpm and aeration of 0.75 vvm in a stirred tank reactor with a fermentation time of 60 h.

Stochastic optimization models for energy management in carbonization process of carbon fiber production

Industrial producers face the task of optimizing production process in an attempt to achieve the desired quality such as mechanical properties with the lowest energy consumption. In industrial carbon fiber production, the fibers are processed in bundles containing (batches) several thousand filaments and consequently the energy optimization will be a stochastic process as it involves uncertainty, imprecision or randomness. This paper presents a stochastic optimization model to reduce energy consumption a given range of desired mechanical properties. Several processing condition sets are developed and for each set of conditions, 50 samples of fiber are analyzed for their tensile strength and modulus. The energy consumption during production of the samples is carefully monitored on the processing equipment. Then, five standard distribution functions are examined to determine those which can best describe the distribution of mechanical properties of filaments. To verify the distribution goodness of fit and correlation statistics, the Kolmogorov-Smirnov test is used. In order to estimate the selected distribution (Weibull) parameters, the maximum likelihood, least square and genetic algorithm methods are compared. An array of factors including the sample size, the confidence level, and relative error of estimated parameters are used for evaluating the tensile strength and modulus properties. The energy consumption and N2 gas cost are modeled by Convex Hull method. Finally, in order to optimize the carbon fiber production quality and its energy consumption and total cost, mixed integer linear programming is utilized. The results show that using the stochastic optimization models, we are able to predict the production quality in a given range and minimize the energy consumption of its industrial process.