Transfer of technical know-how in the machine-tool industry in Brazil, part II: the example of Brazil

Includes bibliography

Efeito do fresamento com alta velocidade de corte na integridade superficial de aços ferríticos com grãos ultrafinos

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Chemical composition and metabolizable energy values of corn germ meal obtained by wet milling for layers

An experiment was carried out to determine the chemical composition, metabolizable energy values, and coefficients of nutrient digestibility of corn germ meal for layers. The chemical composition of corn germ meal was determined, and then a metabolism assay was performed to determine its apparent metabolizable energy (AME) and apparent metabolizable energy corrected for nitrogen (AMEn) values and its dry matter and gross energy apparent metabolizability coefficients (CAMDM and CAMGE, respectively). In the 8-day assay (four days of adaptation and four days of total excreta collection), 60 29-week-old white Lohman LSL layers were used. A completely randomized experimental design, with three treatments with five replicates of four birds each, was applied. Treatments consisted of a reference diet and two test diets, containing 20 or 30% corn germ meal. Results were submitted to analysis of variance and means were compared by the Tukey tests at 5% probability level. The chemical composition of corn germ meal was: 96.39% dry matter, 49.48% ether extract, 1.87% ashes, 7243 kcal gross energy/kg, 11.48% protein, 0.19% methionine, 0.21% cystine, 0.48% lysine, 0.40% threonine, 0.72% arginine, 0.35% isoleucine, 0.83% leucine, 0.57% valine, and 0.37% histidine, on as-fed basis. There were no statistical differences in AME, AMEn, CAMDM, and CAMGE values with the inclusion of 20 and 30% corn germ meal in the diets. On dry matter basis, AME, AMEn, CAMDM, and CAMGE values of corn germ meal were: 4,578 and 4,548 kcal/kg, 4,723 and 4,372 kcal/kg, 64.95 and 61.86%, respectively.

Modeling heat transfer in die milling

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Machine vision to identify broiler breeder behavior

Animal behavioral parameters can be used to assess welfare status in commercial broiler breeders. Behavioral parameters can be monitored with a variety of sensing devices, for instance, the use of video cameras allows comprehensive assessment of animal behavioral expressions. Nevertheless, the development of efficient methods and algorithms to continuously identify and differentiate animal behavior patterns is needed. The objective this study was to provide a methodology to identify hen white broiler breeder behavior using combined techniques of image processing and computer vision. These techniques were applied to differentiate body shapes from a sequence of frames as the birds expressed their behaviors. The method was comprised of four stages: (1) identification of body positions and their relationship with typical behaviors. For this stage, the number of frames required to identify each behavior was determined; (2) collection of image samples, with the isolation of the birds that expressed a behavior of interest; (3) image processing and analysis using a filter developed to separate white birds from the dark background; and finally (4) construction and validation of a behavioral classification tree, using the software tool Weka (model 148). The constructed tree was structured in 8 levels and 27 leaves, and it was validated using two modes: the set training mode with an overall rate of success of 96.7%, and the cross validation mode with an overall rate of success of 70.3%. The results presented here confirmed the feasibility of the method developed to identify white broiler breeder behavior for a particular group of study. Nevertheless, more improvements in the method can be made in order to increase the validation overall rate of success. (C) 2013 Elsevier B.V. All rights reserved.

Application of acoustoelasticity to measure the stress generated by milling in ASTM A36 steel plates

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Hot turning of a difficult-to-machine steel (sae xev-f) aided by infrared radiation

A possible way for increasing the cutting tool life can be achieved by heating the workpiece in order to diminish the shear stress of material and thus decrease the machining forces. In this study, quartz electrical resistances were set around the workpiece for heating it during the turning. In the tests, heat-resistant austenitic alloy steel was used, hardenable by precipitation, mainly used in combustion engine exhaustion valves, among other special applications for industry. The results showed that in the hot machining the cutting tool life can be increased by 340% for the highest cutting speed tested and had a reduction of 205% on workpiece surface roughness, accompanied by a force decrease in relation to conventional turning. In addition, the chips formed in hot turning exhibited a stronger tendency to continuous chip formation indicating less energy spent in material removal process. Microhardness tests performed in the workpieces subsurface layers at 5 m depth revealed slightly higher values in the hot machining than in conventional, showing a tendency toward the formation of compressive residual stress into plastically deformed layer. The hot turning also showed better performance than machining using cutting fluid. Since it is possible to avoid the use of cutting fluid, this machining method can be considered better for the environment and for the human health.

STOCHASTIC ADDING MACHINE AND 2-DIMENSIONAL JULIA SETS

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Physical-chemical characterization and wet milling yield of four maize hybrids

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Integrated cutting machine programming and lot sizing in furniture industry

In this paper a mathematical model that combines lot-sizing and cutting-stock problems applied to the furniture industry is presented. The model considers the usual decisions of the lot sizing problems, as well as operational decisions related to the cutting machine programming. Two sets of a priori generated cutting patterns are used, industry cutting patterns and a class of n-group cutting patterns. A strategy to improve the utilization of the cutting machine is also tested. An optimization package was used to solve the model and the computational results, using real data from a furniture factory, show that a small subset of n-group cutting patterns provides good results and that the cutting machine utilization can be improved by the proposed strategy.

Introducing the Discriminative Paraconsistent Machine (DPM)

This paper introduces a new tool for pattern recognition. Called the Discriminative Paraconsistent Machine (DPM), it is based on a supervised discriminative model training that incorporates paraconsistency criteria and allows an intelligent treatment of contradictions and uncertainties. DPMs can be applied to solve problems in many fields of science, using the tests and discussions presented here, which demonstrate their efficacy and usefulness. Major difficulties and challenges that were overcome consisted basically in establishing the proper model with which to represent the concept of paraconsistency.

Effect of ball milling on the physicochemical characteristics of Peruvian carrot and cassava starches

Peruvian carrot and cassava starches were ground in a ball mill for 4, 8, 16, and 32 h and their structural and physicochemical characteristics were determined. Results obtained from HPAEC-PAD, GPC, and amylose content indicated a breaking of hydrogen bounds and α-(1 [RIGHTWARDS ARROW] 6) linkages of the starch molecules after treatment. X-ray diffractograms showed that the milling provided a reduction in the crystalline area of the starch granules. Most of the starch granules displayed agglomeration after 4 h of milling, when observed under a scanning electron microscope, and after 16 h a shapeless mass was observed for Peruvian carrot starch. Solubility and water absorption capacity of the starches increased with an increase in the milling time, while RVA profiles showed a progressive reduction of peak, breakdown, and final viscosities, as well as the development of initial viscosity. Gelatinization temperatures and enthalpies were reduced. Prolonged ball milling accelerated the enthalpy relaxation in both starches. These results confirmed a partial gelatinization of the starches, which was 82.6% for Peruvian carrot and 65.4% for cassava starches after 32 h of milling. The Peruvian carrot starch was more affected by the ball milling because of both its lower amylose content and the defects in its crystalline structure

Cardiopulmonary bypass: development of John Gibbon's heart-lung machine

To provide a brief review of the development of cardiopulmonary bypass. A review of the literature on the development of extracorporeal circulation techniques, their essential role in cardiovascular surgery, and the complications associated with their use, including hemolysis and inflammation. The advancement of extracorporeal circulation techniques has played an essential role in minimizing the complications of cardiopulmonary bypass, which can range from various degrees of tissue injury to multiple organ dysfunction syndrome. Investigators have long researched the ways in which cardiopulmonary bypass may insult the human body. Potential solutions arose and laid the groundwork for development of safer postoperative care strategies. Steady progress has been made in cardiopulmonary bypass in the decades since it was first conceived of by Gibbon. Despite the constant evolution of cardiopulmonary bypass techniques and attempts to minimize their complications, it is still essential that clinicians respect the particularities of each patient's physiological function.