Exterior view of Okayam Field Station,1953

Inscribed verso: Standing, l to r: Dave Whentley, Ronald Anderson, Jim Kokous, Gaston Sigur, John Hall, Mr. Kayano, Jiro Taguchi. Sitting l to r: Rolf Ward, Dave Plumer (sp?), Tashio Nok, Richard Beardsly, R.B. Hall, James Plumer, Carl Remes, Hidi Shohara, Joseph Yomaguchi

Cook in kitchen at Okayama

Inscribed verso: Standing, l to r: Dave Whentley, Ronald Anderson, Jim Kokous, Gaston Sigur, John Hall, Mr. Kayano, Jiro Taguchi. Sitting l to r: Rolf Ward, Dave Plumer (sp?), Tashio Nok, Richard Beardsly, R.B. Hall, James Plumer, Carl Remes, Hidi Shohara, Joseph Yomaguchi

Three men on tennis court

Inscribed verso: Standing, l to r: Dave Whentley, Ronald Anderson, Jim Kokous, Gaston Sigur, John Hall, Mr. Kayano, Jiro Taguchi. Sitting l to r: Rolf Ward, Dave Plumer (sp?), Tashio Nok, Richard Beardsly, R.B. Hall, James Plumer, Carl Remes, Hidi Shohara, Joseph Yomaguchi

A geometrical model for surface roughness prediction when face milling Al 7075-T7351 with square insert tools

Surface quality is important in engineering and a vital aspect of it is surface roughness, since it plays an important role in wear resistance, ductility, tensile, and fatigue strength for machined parts. This paper reports on a research study on the development of a geometrical model for surface roughness prediction when face milling with square inserts. The model is based on a geometrical analysis of the recreation of the tool trail left on the machined surface. The model has been validated with experimental data obtained for high speed milling of aluminum alloy (Al 7075-T7351) when using a wide range of cutting speed, feed per tooth, axial depth of cut and different values of tool nose radius (0.8. mm and 2.5. mm), using the Taguchi method as the design of experiments. The experimental roughness was obtained by measuring the surface roughness of the milled surfaces with a non-contact profilometer. The developed model can be used for any combination of material workpiece and tool, when tool flank wear is not considered and is suitable for using any tool diameter with any number of teeth and tool nose radius. The results show that the developed model achieved an excellent performance with almost 98% accuracy in terms of predicting the surface roughness when compared to the experimental data. © 2014 The Society of Manufacturing Engineers.

Integrated optimisation of surface roughness and tool performance when face milling 416 SS

Tool life is an important factor to be considered during the optimisation of a machining process since cutting parameters can be adjusted to optimise tool changing, reducing cost and time of production. Also the performance of a tool is directly linked to the generated surface roughness and this is important in cases where there are strict surface quality requirements. The prediction of tool life and the resulting surface roughness in milling operations has attracted considerable research efforts. The research reported herein is focused on defining the influence of milling cutting parameters such as cutting speed, feed rate and axial depth of cut, on three major tool performance parameters namely, tool life, material removal and surface roughness. The research is seeking to define methods that will allow the selection of optimal parameters for best tool performance when face milling 416 stainless steel bars. For this study the Taguchi method was applied in a special design of an orthogonal array that allows studying the entire parameter space with only a number of experiments representing savings in cost and time of experiments. The findings were that the cutting speed has the most influence on tool life and surface roughness and very limited influence on material removal. By last tool life can be judged either from tool life or volume of material removal.

Artificial neural networks for surface roughness prediction when face milling Al 7075-T7351

In this work, different artificial neural networks (ANN) are developed for the prediction of surface roughness (R a) values in Al alloy 7075-T7351 after face milling machining process. The radial base (RBNN), feed forward (FFNN), and generalized regression (GRNN) networks were selected, and the data used for training these networks were derived from experiments conducted using a high-speed milling machine. The Taguchi design of experiment was applied to reduce the time and cost of the experiments. From this study, the performance of each ANN used in this research was measured with the mean square error percentage and it was observed that FFNN achieved the best results. Also the Pearson correlation coefficient was calculated to analyze the correlation between the five inputs (cutting speed, feed per tooth, axial depth of cut, chip°s width, and chip°s thickness) selected for the network with the selected output (surface roughness). Results showed a strong correlation between the chip thickness and the surface roughness followed by the cutting speed. © ASM International.

Parameter design considerations in precision engineering

Parameter design is an experimental design and analysis methodology for developing robust processes and products. Robustness implies insensitivity to noise disturbances. Subtle experimental realities, such as the joint effect of process knowledge and analysis methodology, may affect the effectiveness of parameter design in precision engineering; where the objective is to detect minute variation in product and process performance. In this thesis, approaches to statistical forced-noise design and analysis methodologies were investigated with respect to detecting performance variations. Given a low degree of process knowledge, Taguchi's methodology of signal-to-noise ratio analysis was found to be more suitable in detecting minute performance variations than the classical approach based on polynomial decomposition. Comparison of inner-array noise (IAN) and outer-array noise (OAN) structuring approaches showed that OAN is a more efficient design for precision engineering. ^

Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Análise tribo-termodinâmica da aplicação de nanopartículas de Al2O3 como aditivo lubrificante em compressor hermético de refrigeração

The thermodynamic performance of a refrigeration system can be improved by reducing the compression work by a particular technique for a specific heat removal rate. This study examines the effect of small concentrations of Al2O3 (50 nm) nanoparticles dispersion in the mineral oil based lubricant on the: viscosity, thermal conductivity, and lubrication characteristics as well as the overall performance (based on the Second Law of Thermodynamics) of the refrigerating system using R134a or R600a as refrigerants. The study looked at the influences of variables: i) refrigerant charge (100, 110, 120 and 130 g), ii) rotational speed of the condenser blower (800 and 1100 RPM) and iii) nanoparticle concentration (0.1 and 0.5 g/l) on the system performance based on the Taguchi method in a matrix of L8 trials with the criterion "small irreversibility is better”. They were carried pulldown and cycling tests according to NBR 12866 and NBR 12869, respectively, to evaluate the operational parameters: on-time ratio, cycles per hour, suction and discharge pressures, oil sump temperature, evaporation and condensation temperatures, energy consumption at the set-point, total energy consumption and compressor power. In order to evaluate the nanolubricant characteristics, accelerated tests were performed in a HFRR bench. In each 60 minutes test with nanolubricants at a certain concentration (0, 0.1 and 0.5 g/l), with three replications, the sphere (diameter 6.00 ± 0.05 mm, Ra 0.05 ± 0.005 um, AISI 52100 steel, E = 210 GPa, HRC 62 ± 4) sliding on a flat plate (cast iron FC200, Ra <0.5 ± 0.005 um) in a reciprocating motion with amplitude of 1 mm, frequency 20 Hz and a normal load of 1,96 N. The friction coefficient signals were recorded by sensors coupled to the HFRR system. There was a trend commented bit in the literature: a nanolubricant viscosity reduction at the low nanoparticles concentrations. It was found the dominant trend in the literature: increased thermal conductivity with increasing nanoparticles mass fraction in the base fluid. Another fact observed is the significant thermal conductivity growth of nanolubricant with increasing temperature. The condenser fan rotational speed is the most influential parameter (46.192%) in the refrigerator performance, followed by R600a charge (38.606%). The Al2O3 nanoparticles concentration in the lubricant plays a minor influence on system performance, with 12.44%. The results of power consumption indicates that the nanoparticles addition in the lubricant (0.1 g/L), together with R600a, the refrigerator consumption is reduced of 22% with respect to R134a and POE lubricant. Only the Al2O3 nanoparticles addition in the lubricant results in a consumption reduction of about 5%.

Empirical expression of tool wear when face milling 416 SS

During a machining process, cutting parameters must be taken into account, since depending on them the cutting edge starts to wear out to the point that tool can fail and needs to be change, which increases the cost and time of production. Since wear is a negative phenomenon on the cutting tool, due to the fact that tool life is reduced, it is important to optimize the cutting variables to be used during the machining process, in order to increase tool life. This research is focused on the influence of cutting parameters such as cutting speed, feed per tooth and axial depth of cut on tool wear during a face milling operation. The Taguchi method is applied in this study, since it uses a special design of orthogonal array to study the entire parameters space, with only few numbers of experiments. Also a relationship between tool wear and the cutting parameters is presented. For the studies, a martensitic 416 stainless steel was selected, due to the importance of this material in the machining of valve parts and pump shafts. Copyright © 2009 by ASME.

Circus Workshop in the chid Psychiatry

The following paper is about the possible psychological effects of social circus, and our experiences with teaching circus methods in children psychiatry. In the beginning the paper try to place social circus in a wider theoretical frame, and searches for the place of it among psychological methods and therapies. We look at the wider and the more specific psychological constructs, what can be effected by social circus, especially the factors which are damaged in children with psycological or psychiatrycal problems. We examine the different parts of circus, how they can help in different problems. The further aim is to research the effects of a continuous social circus group, and to find it’s own way among psychotherapies.

Otimização dos parâmetros de maquinagem no processo de fresagem

Cada vez mais, os principais objetivos na indústria é a produção a baixo custo, com a máxima qualidade e com o tempo de fabrico o mais curto possível. Para atingir esta meta, a indústria recorre, frequentemente, às máquinas de comando numérico (CNC), uma vez que com esta tecnologia torna se capaz alcançar uma elevada precisão e um tempo de processamento mais baixo. As máquinas ferramentas CNC podem ser aplicadas em diferentes processos de maquinagem, tais como: torneamento, fresagem, furação, entre outros. De todos estes processos, o mais utilizado é a fresagem devido à sua versatilidade. Utiliza-se normalmente este processo para maquinar materiais metálicos como é o caso do aço e dos ferros fundidos. Neste trabalho, são analisados os efeitos da variação de quatro parâmetros no processo de fresagem (velocidade de corte, velocidade de avanço, penetração radial e penetração axial), individualmente e a interação entre alguns deles, na variação da rugosidade num aço endurecido (aço 12738). Para essa análise são utilizados dois métodos de otimização: o método de Taguchi e o método das superfícies. O primeiro método foi utilizado para diminuir o número de combinações possíveis e, consequentemente, o número de ensaios a realizar é denominado por método de Taguchi. O método das superfícies ou método das superfícies de resposta (RSM) foi utilizado com o intuito de comparar os resultados obtidos com o método de Taguchi, de acordo com alguns trabalhos referidos na bibliografia especializada, o RSM converge mais rapidamente para um valor ótimo. O método de Taguchi é muito conhecido no setor industrial onde é utilizado para o controlo de qualidade. Apresenta conceitos interessantes, tais como robustez e perda de qualidade, sendo bastante útil para identificar variações do sistema de produção, durante o processo industrial, quantificando a variação e permitindo eliminar os fatores indesejáveis. Com este método foi vi construída uma matriz ortogonal L16 e para cada parâmetro foram definidos dois níveis diferentes e realizados dezasseis ensaios. Após cada ensaio, faz-se a medição superficial da rugosidade da peça. Com base nos resultados obtidos das medições da rugosidade é feito um tratamento estatístico dos dados através da análise de variância (Anova) a fim de determinar a influência de cada um dos parâmetros na rugosidade superficial. Verificou-se que a rugosidade mínima medida foi de 1,05m. Neste estudo foi também determinada a contribuição de cada um dos parâmetros de maquinagem e a sua interação. A análise dos valores de “F-ratio” (Anova) revela que os fatores mais importantes são a profundidade de corte radial e da interação entre profundidade de corte radial e profundidade de corte axial para minimizar a rugosidade da superfície. Estes têm contribuições de cerca de 30% e 24%, respetivamente. Numa segunda etapa este mesmo estudo foi realizado pelo método das superfícies, a fim de comparar os resultados por estes dois métodos e verificar qual o melhor método de otimização para minimizar a rugosidade. A metodologia das superfícies de resposta é baseada num conjunto de técnicas matemáticas e estatísticas úteis para modelar e analisar problemas em que a resposta de interesse é influenciada por diversas variáveis e cujo objetivo é otimizar essa resposta. Para este método apenas foram realizados cinco ensaios, ao contrário de Taguchi, uma vez que apenas em cinco ensaios consegue-se valores de rugosidade mais baixos do que a média da rugosidade no método de Taguchi. O valor mais baixo por este método foi de 1,03μm. Assim, conclui-se que RSM é um método de otimização mais adequado do que Taguchi para os ensaios realizados. Foram obtidos melhores resultados num menor número de ensaios, o que implica menos desgaste da ferramenta, menor tempo de processamento e uma redução significativa do material utilizado.