Abstract: This study shows a methodology for characterizing high speed machining centres, in
terms of their capabilities, to reach programmed feed rates while the machining of complex
sculptured surfaces. The impact on the cycle time of the whole operation has been evaluated making
a parametric variation of the geometries to be machined. Therefore, for a distributed and
simultaneous characterization of machining centres located in different places, tools for
Collaborative Engineering have been used (PLM and CAD/CAM/CAE).
Abstract: To allow for enhanced quality while reducing machining time, machines have become
increasingly complex, thus leading to an increase in purchase, running and operator training costs.
In what follows in the present paper, we shall firstly show how a virtual machine tool can be
developed. Secondly, we shall study the influence this tool can have on teaching methods..
Abstract: During turning operations, the workpiece clamping system and the selection of the
cutting conditions are of prime importance. They both have a significant influence on workpiece
roundness error ER, due to the dynamic behaviour of the chuck-axis-workpiece system. This
dynamic behaviour is conditioned by selected machining parameters (cutting speed v, depth-of-cut
d, feed rate f) and the design of the workpiece (length L and diameter φ). The main aim of the work
was to evaluate the influence of the aforementioned parameters (v, d, f, L/φ) on workpiece
roundness error ER during turning AISI-1045 steel material, for a range of machining conditions
(v=150, 200, 250 m/min, f=0.15, 0.20, 0.25 mm/rev, d=1, 2, 3 mm). Furthermore, the cutting force
signals were monitored throughout the tests in order to control the process and the correlation of the
three force components (depth Fd, tangential Ft, feed Ff) with workpiece roundness error ER was
analysed. Of all the various operating process parameters that were evaluated, the machined
workpiece length L and the depth-of-cut d were shown to have the most significant influence on ER
variation. The highest ER values were obtained when the highest depth-of-cut d, feed rate f, cutting
speed v and length L values were employed and combined. Little effect on the output measure ER
was observed when cutting speed v and feed rate f parameters were individually increased.
Moreover, an increase in the cutting force (Fd, Ft y Ff) values showed to produce a significant
increase in workpiece roundness error ER.
Abstract: The purpose of this study is to develop two predictive models for burr height in cutting
titanium alloy plates by using Nd:YAG laser. Firstly, Taguchi method has been used to arrange the
experimental scheme and analyze the results via analysis of mean . The important laser cutting
parameters affecting burr height can be found. It shows that the pressure of assistant gas, the
focusing position and the pulsed frequency are the most important cutting parameters in order. Then
they have been chosen as the input variables for response surface methodology and used to
construct a mathematical equation for predicting burr height. Secondly, the laser cutting parameters
and experimental results obtained from conducting the schematic arrangement using Taguchi
method and response surface methodology have been treated as training patterns and recalling
patterns for the back-propagation neural network. As a result, a predictive model for burr height
prediction in laser cutting titanium alloy has been established. To verify the accuracy of above two
prediction models, there are 9 sets of experiment have been performed. It shows that the average
error for predicting burr height by the mathematical equation derived from response surface
methodology is 5.52% and by the predictive model established by back-propagation neural network
is 4.51%, respectively. Obviously, both predictive models are good enough for the relational
research and practical applications. It can be concluded that the procedure used in this research and
the obtaining predictive models can be used practically in correlate industry.
Abstract: Present work shows many of Virtual Reality (RV) developments carried out in
manufacturing processes field by the collaboration between Aerospace Materials and Production
Department at the UPM University and Manufacturing and Construction Engineering at the UNED
university. Most of them have been directed towards Numerical Control Machine Tools field and
towards equipment that configure automated manufacturing systems like Flexible Manufacturing
Abstract: In the present consumer, the personalization and originality of the made polymeric
products it is one of the area in which dwells efforts of investigation take it pleases. Many
companies uses plastic recipients that dog be painted or wrapped with to plastic but to however, the
development of artistic relief plows not developed. The biggest problem was obtaining an artistic
process out. In manual a way, it is very complicated, and there was not specific software to develop
this kind of work because they were designed to carry out tech-line pieces. The aim of this work is
to develop to method to produces to 3-D relief, an artistic appears and some letters, in a mould.
Abstract: In this work, a surface roughness study on the die-sinking electrical discharge machining
(EDM) of siliconised silicon carbide (SiSiC) has been carried out. The selection of the abovementioned
conductive ceramic was made taking into account its wide range of applications in the
industrial field: high temperature gas turbines, bearings, seals and lining of industrial furnaces. This
study was made only for the finish stages, due to the enormous importance that a good surface
quality has over such important properties as, in the case of ceramic materials: corrosion, fatigue
and wear resistance. The present study has been carried out on the influence of five design factors:
intensity supplied by the generator of the EDM machine (I), pulse time (ti), duty cycle (η), opencircuit
voltage (U) and dielectric flushing pressure (P), which are the most relevant parameters to be
controlled by the EDM process machinists, over two roughness parameters such as Ra and Rq. The
study of the behaviour of the two previously mentioned parameters has been done by means of the
technique of design of experiments (DOE), which allows us to carry out the previous analysis
performing a relatively small number of experiments. In this case, a 25-1 fractional factorial design,
whose resolution is V, has been selected due to the number of factors considered in the study.
Abstract: This study concerns the formulation of a multi-parameter surface texture model in
EDMachining of AISI D2 tool steel. The model is developed in terms of pulse current and pulse-on
time which are the dominant machining conditions, via factorial design of experiments. By applying
analysis of variance and statistical multi-regression analysis to the experimental data close
correlation is proved between certain surface finish parameters and the machining conditions, with
pulse current exerting the strongest influence. By applying this model the appropriate conditions for
successful finish can be selected, as well as functional surface characteristics can be quantified.
Abstract: A new type of ceramic abrasive tools prepared of aluminium oxide (alumina), designed
to realise the one-pass process of inside diameter grinding.
Distinctive feature of these tools is the gradient distribution of the abrasive grain zones with
different sizes and structure which enables to carry out the rough (efficient) and finishing grinding
in one pass.
An influence of the grinding speed vS and the quantities of the working engagement ae on the worksurface
roughness and the grinding power were determined.
Abstract: This paper shows a solution to the problem of finding an optimum sheet metal bending
sequence using Genetic Algorithms (GA). First it shall be explained how the problem can be
modelled, previous to its solution by GA. Secondly the method for optimization, under different
criteria, is described. Finally the results obtained and the advantages of using the GA are shown.