Beatriz de Agustina

Surface roughness model based on force sensors for the prediction of the tool wear.

In this study, a methodology has been developed with the objective of evaluating the surface roughness obtained during turning processes by measuring the signals detected by a force sensor under the same cutting conditions. In this way, the surface quality achieved along the process is correlated to several parameters of the cutting forces (thrust forces, feed forces and cutting forces), so the effect that the tool wear causes on the surface roughness is evaluated. In a first step, the best cutting conditions (cutting parameters and radius of tool) for a certain quality surface requirement were found for pieces of UNS A97075. Next, with this selection a model of surface roughness based on the cutting forces was developed for different states of wear that simulate the behaviour of the tool throughout its life. The validation of this model reveals that it was effective for approximately 70% of the surface roughness values obtained.

Surface Roughness Evaluation Based on Acoustic Emission Signals in Robot Assisted Polishing

The polishing process is the most common technology used in applications where a high level of surface quality is demanded. The automation of polishing processes is especially difficult due to the high level of skill and dexterity that is required. Much of this difficulty arises because of the lack of reliable data on the effect of the polishing parameters on the resulting surface roughness. An experimental study was developed to evaluate the surface roughness obtained during Robot Assisted Polishing processes by the analysis of acoustic emission signals in the frequency domain. The aim is to find out a trend of a feature or features calculated from the acoustic emission signals detected along the process. Such an evaluation was made with the objective of collecting valuable information for the establishment of the end point detection of polishing process. As a main conclusion, it can be affirmed that acoustic emission (AE) signals can be considered useful to monitor the polishing process state.

Tool selection based on surface roughness in dry facing repair operations of magnesium pieces

This paper presents an experimental study on the dry facing of pieces of UNS M11917 magnesium. The work was focused on repair operations that are typically carried out with low-performance cutting conditions. The main goal of this study was to determine the tool that best suits the requirements of surface roughness for these operations. The tools considered had the same geometry but different coatings and were selected from among the most commonly used tools for magnesium and the hybrid structures formed by magnesium and other materials. The effects of spindle speed and feed rate were also considered to determine which factors and their possible interactions are more crucial. The tests were conducted following the Taguchi orthogonal design of experiments (DOE), and the results were analysed by the analysis of variance (ANOVA) method. A model for estimating the expected surface roughness in terms of the average roughness, Ra, was also developed.

Surface Roughness Analysis of Magnesium Pieces Obtained by Intermittent Turning

This paper presents an experimental study to analyze the surface roughness reached in pieces of UNS M11917 magnesium alloy obtained by intermittent turning. A design of experiments (DOE) was established to carry out the study. Namely, factors identified as posible sources of variation of the surface roughness and their levels, written between parentheses, are the following: depth of cut (1), feed rate (2), spindle speed (2), type of tool (2), quantity of lubrication (3), type of interruption (3), measurement length (3) and measurement generatrice (3). Due to the high number of possible combinations that can be generated with the set of factors and levels identified a combined design of experiments L4x32 was performed. Data are was analyzed by means of the analysis of variance (ANOVA) method. The main results of the statistical analysis highlight the great influence of the feed rate on surface roughness among the set of factors and their interactions considered. In addition, focusing on the intermittent cutting, type of interruption and its interaction with the type of tool used are also important sources of variation, but at a lower level than feed rate.

Accuracy Analysis of Fringe Projection Systems Based on Blue Light Technology

Some manufacturers of 3D digitizing systems are developing and market more accurate, fastest and affordable systems of fringe projection based on blue light technology. The aim of the present work is the determination of the quality and accuracy of the data provided by the LED structured light scanner Comet L3D (Steinbichler). The quality and accuracy of the cloud of points produced by the scanner is determined by measuring a number of gauge blocks of different sizes. The accuracy range of the scanner has been established through multiple digitizations showing the dependence on different factors such as the characteristics of the object and scanning procedure. Although many factors influence, accuracies announced by manufacturer have been achieved under optimal conditions and it has been noted that the quality of the point clouds (density, noise, dispersion of points) provided by this system is higher than that obtained with laser technology devices.

Surface roughness predictive model of UNS A97075 aluminum pieces obtained by dry turning tests based on the cutting forces

The present work shows an experimental study for a first approach of a surface roughness predictive model of UNS A97075 aluminum pieces obtained by dry turning tests based on the cutting forces. In a first step, a design of experiments (DOE) 25 was employed to analyse the influence of the cutting parameters and type of tool on the surface roughness with the objective to find out a combination of cutting conditions that allow obtaining a range of values of surfaces roughness according to the aeronautical specifications requierements. The factors considered for this design were the feed rate, spindle speed, depth of cut, type of tool (nose radious) and machined length (zone of the workpiece where the surface roughness measurements are taken). The obtained data was analysed by means of the analysis of variance (ANOVA) method. And secondly, with the previous selected conditions selected it was developed by multiple regression a model to predict the surface roughness by measuring the cutting forces generated during the dry turning tests of aluminum alloy UNS A97075 pieces. The predictive model of surface roughness obtained includes statistical values calculated from the forces sygnal in time and frequency domains.

Analysis of Force Signals for the Estimation of Surface Roughness during Robot-Assisted Polishing

In this study feature extraction of force signals detected during robot-assisted polishing processes was carried out to estimate the surface roughness during the process. The purpose was to collect significant features from the signal that allow the determination of the end point of the polishing process based on surface roughness. For this objective, dry polishing turning tests were performed on a Robot-Assisted Polishing (RAP) machine (STRECON NanoRAP 200) during three polishing sessions, using the same polishing conditions. Along the tests, force signals were acquired and offline surface roughness measurements were taken at the end of each polishing session. As a main conclusion, it can be affirmed, regarding the force signal, that features extracted from both time and frequency domains are valuable data for the estimation of surface roughness.

Learning Activities through Academic Papers Focused on Forming Processes

This work analyses the learning tasks, related to forming processes, realized by students of a Master degree focused on Manufacturing Engineering. The forming processes include bulk deformation and sheet forming. The objective of these activities is to identify if these practices are linked to research and development or technological innovation. The students must select works from database of international scientific journals and analyze the contents. The results show that the students have identified 62 papers from 21 different journals and of authors from 17 countries; mostly traditional processes (bending, extrusion, deep-drawing, mainly) have been chosen and studied, recognizing important advances in them; moreover the learning tasks have contributed to the acquisition the basic, general and specific competences.

Manufacturing Engineering Education: Study of the Continuous Evaluation Activities on UNED

In this study, the continuous assessment activities are analyzed on the learning results. The subjects chosen belong to the field of Manufacturing Engineering. The subjects analyzed are taught in Bachelor´s Degree in College of Industrial Engineering. The continuous assessment activities were designed to propose in both obligatory and elective subjects. The number of the students in obligatory subjects is usually higher than in the other type. In this paper, the data were extracted from the last three academic courses. From the analysis of the results it can be affirmed that, in general, students who carried out assessment activities, improved their academic results.

Experimental investigation of dry turning of UNS A97050-T7 aluminium alloy bars based on surface roughness

In this research, an experimental study was carried out in order to analyse the influence of the cutting parameters (feed rate and cutting speed) and the type of tool employed (TiN coated tool and two uncoated tools) on the surface roughness obtained during dry turning tests of UNS A97050-T7 aluminium bars. These alloys are of particular interest to both the aerospace and automotive industries for the production of different elements that compose airships and aerospace vehicles due to the very good relationship between their weight and their mechanical properties. The results show that the feed rate was the more influential cutting parameter on the surface roughness and to a lesser extent the cutting speed, the type of tool and the interaction between the type of tool and the feed.