The Experts below are selected from a list of 6444 Experts worldwide ranked by ideXlab platform
Petko Vladev Petkov - One of the best experts on this subject based on the ideXlab platform.
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Laser Milling: Tool making capabilities
International Congress on Applications of Lasers & Electro-Optics, 2011Co-Authors: Stefan Simeonov Dimov, Petko Vladev Petkov, Franck Lacan, Steffen ScholzAbstract:Laser Milling is a relatively new manufacturing process that has attracted much attention from engineers and researchers for the last decade. The process allows complex parts and tooling inserts to be fabricated directly from 3D CAD data in a wide range of advanced engineering materials such as ceramics, hardened steel, bulk metallic glasses, titanium and nickel alloys. The paper discusses the process design and implementations issues in applying the Laser Milling technology for tool making. Especially, the focus is on design and implementation of appropriate material removal strategies and the necessary optimisation of processing parameters to produce replication tools with required surface integrity and resolution. Two application case studies are used to demonstrate the capabilities of the Laser Milling process, in particular for the fabrication of replication tools for serial manufacture of micro needles arrays for drug delivery and bio inspired surface structures for drag reduction. The paper concludes with a discussion of tool making capabilities and limitations of Laser Milling technology.Laser Milling is a relatively new manufacturing process that has attracted much attention from engineers and researchers for the last decade. The process allows complex parts and tooling inserts to be fabricated directly from 3D CAD data in a wide range of advanced engineering materials such as ceramics, hardened steel, bulk metallic glasses, titanium and nickel alloys. The paper discusses the process design and implementations issues in applying the Laser Milling technology for tool making. Especially, the focus is on design and implementation of appropriate material removal strategies and the necessary optimisation of processing parameters to produce replication tools with required surface integrity and resolution. Two application case studies are used to demonstrate the capabilities of the Laser Milling process, in particular for the fabrication of replication tools for serial manufacture of micro needles arrays for drug delivery and bio inspired surface structures for drag reduction. The paper conclud...
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Manufacturing of an array of microneedles in a steel insert for micro-injection moulding using Laser Milling
Proceedings of the 8th International Conference on Multi-Material Micro Manufacture, 2011Co-Authors: Franck Lacan, Petko Vladev Petkov, Steffen Scholz, Stefan Simeonov DimovAbstract:The use of arrays of hollow micro needles offers the potential of pain free drug delivery through the skin. However, their batch manufacture represents a real challenge. Especially, it is difficult to design and implement reliable and cost effective manufacturing solutions suitable for scale up production of such new drug delivery devices. In this paper the authors report an investigation of possible manufacturing process chains for producing steel mould inserts for serial replication of microneedles’ patches employing injection moulding. The focus is on manufacturing solutions that utilise nano-second and pico-second Laser Milling for machining the necessary replication inserts. The process optimisation issues associated with their manufacture are discussed, and the processing windows that were determined are described. To validate the proposed tool-making process chains some moulding inserts were successfully machined using both Laser Milling technologies. Finally the limitations and uncertainties of these tool making process chains are discussed.
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Laser Milling pulse duration effects on surface integrity
Proceedings of the Institution of Mechanical Engineers Part B: Journal of Engineering Manufacture, 2008Co-Authors: Petko Vladev Petkov, Stefan Simeonov Dimov, Roussi Minev, D T PhamAbstract:Laser Milling of engineering materials is a viable alternative to conventional methods for machining complex microcomponents. The Laser source employed to perform such microstructuring has a direct impact on achievable surface integrity. At the same time, the trade-offs between high removal rates and the resulting surface integrity should be taken into account when selecting the most appropriate ablation regime for performing Laser Milling. In this paper the effects of pulse duration on surface quality and material microstructure are investigated when ablating a material commonly used for manufacturing microtooling inserts. For both micro- and nanosecond Laser regimes, it was estimated that the heat-affected zone on the processed surface is within 50 μm. When performing ultra-short pulsed Laser ablation, the effects of heat transfer are not as evident as they are after processing with longer Laser pulse durations. Although some heat is dissipated into the bulk when working in pico- and femtosecond regimes it is not sufficient to trigger significant structural changes.
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Strategies for material removal in Laser Milling
2008Co-Authors: Petko Vladev Petkov, Steffen Scholz, Stefan Simeonov DimovAbstract:Laser Milling with microsecond pulses is a thermal material removal process usually associated with detrimental effects such as heat affected zones (HAZ), a recast layer and debris. Process optimisation can lead to considerable reduction of the above mentioned negative effects. In this context, the research investigates the effects of tool path optimisation and material removal strategies on the resultant surface quality and edge definition. The conducted experimental study shows clearly that the applied Milling strategies have a significant effect on the resulting surface topography and the edge definition. Also, the research demonstrates that by optimising the Laser path and material removal strategies it is possible to reduce significantly the thermal load when Milling micro features, and thus to minimise HAZ and other secondary effects.
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Laser Milling of ceramic components
International Journal of Machine Tools & Manufacture, 2006Co-Authors: Duc Truong Pham, Stefan Simeonov Dimov, Petko Vladev PetkovAbstract:Abstract Conventional methods of producing ceramic components are based on sintering technology which requires expensive tooling making it uneconomic for small batch fabrication. Laser Milling provides a new method of producing parts in a wide range of materials, including ceramics, directly from CAD data. This paper considers the technical capabilities of Laser Milling when applied to the machining of microcomponents from alumina and silicon nitride ceramics. The main parameters affecting the material removal characteristics of Laser Milling are reviewed. A new technique for machining alumina components is proposed emphasising the importance of correct set-up design in achieving a high level of accuracy. Process parameters influencing part quality are analysed and guidelines for machine set-ups are formulated. The paper concludes with an assessment of the accuracy of the Laser Milling process.
Silvio Genna - One of the best experts on this subject based on the ideXlab platform.
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Multiobjective optimisation of nanosecond fiber Laser Milling of 2024 T3 aluminium alloy
Journal of Manufacturing Processes, 2020Co-Authors: Claudio Leone, Silvio Genna, Flaviana TagliaferriAbstract:Abstract In the present study, a 30 W Q-switched fiber Laser was adopted for Milling 2024 aluminium alloy sheet 2 mm in thickness. Square pockets, 10 × 10 mm2 in plane dimension, were machined at the maximum nominal average power (30 W), under different Laser processing parameters: scan speed, hatching distance, pulse energy and repetitions. After machining, the achieved depth (Depth) and roughness (Ra) were measured by way of a 3D surface profiling system. In addition, the material removal rate (MRR) was calculated as the ratio between the removed volume/process time. Analysis of Variance was adopted to assess the effect of the process parameters on the Depth, Ra and MRR. Response Surface Methodology (RSM) was adopted to model the process behaviours; the roughness and MRR were found to be strictly related to the machined depth. In the end, Multi-Response Optimisation (MRO) methodology was adopted to individuate the optimal process conditions allowing the process conditions able to produce the desired depths with the minimum roughness at the maximum MRR.
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Laser Milling of yttria-stabilized zirconia by using a Q-switched Yb:YAG fiber Laser: experimental analysis
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Stefano Guarino, Silvio Genna, Gennaro Salvatore Ponticelli, Oliviero Giannini, Federica TrovalusciAbstract:The present investigation deals with Laser Milling process of yttria-stabilized zirconia (YSZ), by using a Q-switched 30 W Yb:YAG fiber Laser. First, the influence of Laser operational parameters, Laser beam scan speed, the number of time, and the sample surface is worked (number of repetition) and the scanning strategy was investigated. This first step allowed to identify the most suitable processing window in terms of surface quality and machined depth. Then, a systematic approach based on full factorial design of experiment was developed and successfully adopted to identify and explain the effect of each operational parameter on Laser–material interaction and on the process outputs: roughness, machined depth, and material removal rate. The experimental results demonstrate that the Laser treatment is suitable for YZS highlighting high repeatability, process accuracy, short machining time, and the possibility to easily control the process outputs
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Multi‐response optimization of CFRP Laser Milling process based on response surface methodology
Polymer Engineering & Science, 2017Co-Authors: Silvio Genna, Claudio Leone, Flaviana Tagliaferri, Ilaria Papa, Biagio PalumboAbstract:In this study, ANalysis Of VAriance (ANOVA) and Response Surface Methodology were applied to characterize and optimize Laser Milling of Carbon Fiber Reinforced Polymer (CFRP) plates. The process was performed by means of a 30W Q-switched Yb:YAG fiber Laser, working at the fundamental wavelength of 1064 nm. The machined material was a CFRP plate, 4 mm in thickness, obtained by autoclave cure. According to Design of Experiments (DoE) methodology and previous experiences, a Central Composite Design (CCD) was developed and applied. The investigated parameters were the scan speed, the pulse frequency, the number of repetitions of the geometric pattern and the hatch distance. The suitable Milling conditions were obtained from the response surface model. The model allows to set the process parameters to obtain the desired depth with an error
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Prediction of Poly-methyl-methacrylate Laser Milling Process Characteristics Based on Neural Networks and Fuzzy Data☆
Procedia CIRP, 2016Co-Authors: Doriana M. D’addona, Silvio Genna, Claudio Leone, D. MatarazzoAbstract:Abstract Laser Milling is a recent technology adopted in rapid prototyping to produce tool, mould and polymer-based microfluidic devices. In this process, a Laser beam is used to machine a solid bulk, filling the area to be machined with a number of closely spaced parallel lines. Compared to traditional machining, this method has some advantages, such as: greater flexibility of use, no mechanical contact with the surface, a reduction in industrial effluents, a fine accuracy of machining, even with complex forms, and the possibility to work different kind of materials. While it is relatively easy to predict the depth of the area worked, the surface roughness is more difficult to predict due to the materials behaviors at microscopic level. This is truer when polymer processing is considered due to the local thermal effects. The paper addresses the application of an artificial neural network computing technique to predict the depth and the surface roughness in Laser Milling tests of poly-methyl-methacrylate. The tests were carried out adopting a CO 2 Laser working in continuous and pulsed wave mode. The obtained results showed a good agreement between the model and the experimental data. As a matter of fact, despite the thermal degradation that occurs on the PMMA surface, neural network processing offers an effective method for the prevision of roughness parameters as a function of the adopted process parameters.
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Experimental investigation on Laser Milling of aluminium oxide using a 30 W Q-switched Yb:YAG fiber Laser
Optics & Laser Technology, 2016Co-Authors: Claudio Leone, Silvio Genna, Flaviana Tagliaferri, Biagio Palumbo, Martin DixAbstract:Abstract In the present study, Laser Milling tests were carried out on aluminium oxide (Al2O3) plate, 3 mm in thickness, using a Q-Switched 30 W Yb:YAG fiber Laser. A systematic approach based on Design of Experiment (DoE) has been successfully adopted with the aim to detect which and how the process parameters affect the Laser beam–material interaction, and to explain the effect of the process parameters on the material removal rate and surface quality. The examined process parameters were the Laser beam scan speed, the pulse frequency, the total energy released for surface unit, the distance between two consecutive scan lines and the scanning strategy. A full factorial design and ANalysis Of VAriance (ANOVA) were applied for the results analysis. Finally, the various effects of the process parameters on the material removal rate and surface roughness have been analysed and discussed.
Viboon Tangwarodomnukun - One of the best experts on this subject based on the ideXlab platform.
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Experiment and analytical model of Laser Milling process in soluble oil
The International Journal of Advanced Manufacturing Technology, 2018Co-Authors: Viboon Tangwarodomnukun, Chaiya DumkumAbstract:The liquid-assisted Laser machining process is a promising method to cut materials with minimum thermal damage caused by Laser, and water is typically used in the process due to its high thermal conductivity, nontoxicity, and relatively low price. However, water can intrinsically oxidize ferrous metals and in turn deteriorate the workpiece through corrosion during Laser ablation in water. This study has for the first time proposed Laser ablation in soluble oil to effectively cut the ferrous metals by using Laser in a high cooling rate and low potentiality of corrosion to the metals. A nanosecond pulse Laser was used to scan over the AISI H13 steel sheet to create a square cavity, while the workpiece surface was covered by a thin and flowing soluble oil film throughout the Laser Milling process. The effects of Laser scan overlap, traverse speed, and liquid flow rate on cavity dimensions and milled surface morphology were experimentally examined. The results revealed that a clean and uniform cavity with a smooth machined surface can be attained by using 70% scan overlap, 6 mm/s traverse speed, and 3.9 cm^3/s soluble oil flow rate. Furthermore, analytical models based on heat transfer equations were formulated to predict the cavity profile and cooling of molten droplets in flowing liquid. The predicted profile was found to correspond well to the experiment, and the calculated temperature of cut particles can endorse the experimental findings on debris deposition and recast formation. The implications of this study could bring a new technological approach for damage-free fabrication and fine-scale manufacturing.
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Underwater Laser MicroMilling of Commercially-Pure Titanium Using Different Scan Overlaps
IOP Conference Series: Materials Science and Engineering, 2018Co-Authors: Wisan Charee, Viboon TangwarodomnukunAbstract:Underwater Laser Milling process is a technique for minimizing the thermal damage and gaining a higher material removal rate than processing in air. This paper presents the effect of Laser scan overlap on cavity width, depth and surface roughness in the Laser Milling of commercially-pure titanium in water. The effects of Laser pulse energy and pulse repetition rate were also examined, in which a nanosecond pulse Laser emitting a 1064-nm wavelength was used in this study. The experimental results indicated that a wide and deep cavity was achievable under high Laser energy and large scan overlap. According to the surface roughness, the use of high pulse repetition rate together with low Laser energy can promote a smooth Laser-milled surface particularly at 50% scan overlap. These findings can further suggest a suitable Laser microMilling condition for titanium in roughing and finishing operations.
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Evolution of milled cavity in the multiple Laser scans of titanium alloy under a flowing water layer
The International Journal of Advanced Manufacturing Technology, 2017Co-Authors: Viboon Tangwarodomnukun, Taweeporn WuttisarnAbstract:The needs for damage-free and fine-scale features with good surface finish have been challenging today’s manufacturing technologies. Laser machining process performed under a flowing water layer is a capable technique to satisfy these requirements with high processing rate and clean cut surface. However, the capability and performance of this process for Milling applications have not clearly been understood yet. Therefore, this study aims at enabling an insight into the Laser Milling process under a flowing water layer. Titanium alloy (Ti-6Al-4V) was employed as a work sample in this study, and a nanosecond pulse Laser was used to ablate the material in water. The effects of Laser traverse speed and number of scans on geometrical dimensions, surface and subsurface characteristics were experimentally investigated. The results revealed that a deeper milled cavity with a smaller taper angle was achievable by using a slower traverse speed and more number of Laser scans. A trade-off between the uniformity and roughness of milled surface was also evidenced under the different Laser traverse speeds examined in this study. By comparing to the Laser Milling of titanium alloy in ambient air, there was no metallurgical change remarkably found in the Laser-milled area when the process was carried out in water. In addition, specific energy required to fabricate a Laser-milled cavity was about 18 kWs/mm^3 for a single scan technique and linearly increased with the number of scans. The findings of this study will advance the understanding of Laser ablation in flowing water as well as other liquid-assisted Laser machining techniques. The implication of this study will further open wider applications of liquid-assisted Laser ablation for a more intricate micro-fabrication with high resolution, high processing rate, and less thermal damage.
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Effect of Water Flow Direction on Cut Features in the Laser Milling of Titanium Alloy under a Water Layer
Materials Science Forum, 2016Co-Authors: Ornicha Tevinpibanphan, Viboon Tangwarodomnukun, Chaiya DumkumAbstract:Laser ablation under a flowing water layer can reduce thermal damage in work material and also provide a better machining performance than processing in ambient air. However, there is still a lack of insight into a more complicated process like Laser Milling operation in water. Besides the Laser parameters, the roles of water flow direction on the cut geometries need to be elucidated to realize the viability and reliability of the Laser Milling process in water. This study is for the first time to reveal the effects of water flow direction on the cavity dimensions and cut surface roughness in the Laser Milling process performed under a flowing water layer. Titanium alloy was used as a work sample in this study. The experimental results indicated that the Laser beam should travel in the same direction of water flow to provide a uniform cavity depth and smooth milled surface.
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Cavity formation and surface modeling of Laser Milling process under a thin-flowing water layer
Applied Surface Science, 2016Co-Authors: Viboon TangwarodomnukunAbstract:Abstract Laser Milling process normally involves a number of Laser scans over a workpiece to selectively remove the material and then to form cavities with shape and dimensions required. However, this process adversely causes a heat accumulation in work material, which can in turn damage the Laser-milled area and vicinity in terms of recast deposition and change of material properties. Laser Milling process performing in a thin-flowing water layer is a promising method that can overcome such damage. With the use of this technique, water can flush away the cut debris and at the same time cool the workpiece during the ablation. To understand the potential of this technique for Milling application, the effects of process parameters on cavity dimensions and surface roughness were experimentally examined in this study. Titanium sheet was used as a workpiece to be milled by a nanosecond pulse Laser under different water flow velocities. A smooth and uniform cut feature can be obtained when the metal was ablated under the high Laser pulse frequency and high water flow velocity. Furthermore, a surface model based on the energy balance was developed in this study to predict the cavity profile and surface roughness. By comparing to the experiments, the predicted profiles had a good agreement with the measured ones.
Stefan Simeonov Dimov - One of the best experts on this subject based on the ideXlab platform.
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Manufacturing of an array of microneedles in a steel insert for micro-injection moulding using Laser Milling
Proceedings of the 8th International Conference on Multi-Material Micro Manufacture, 2011Co-Authors: Franck Lacan, Petko Vladev Petkov, Steffen Scholz, Stefan Simeonov DimovAbstract:The use of arrays of hollow micro needles offers the potential of pain free drug delivery through the skin. However, their batch manufacture represents a real challenge. Especially, it is difficult to design and implement reliable and cost effective manufacturing solutions suitable for scale up production of such new drug delivery devices. In this paper the authors report an investigation of possible manufacturing process chains for producing steel mould inserts for serial replication of microneedles’ patches employing injection moulding. The focus is on manufacturing solutions that utilise nano-second and pico-second Laser Milling for machining the necessary replication inserts. The process optimisation issues associated with their manufacture are discussed, and the processing windows that were determined are described. To validate the proposed tool-making process chains some moulding inserts were successfully machined using both Laser Milling technologies. Finally the limitations and uncertainties of these tool making process chains are discussed.
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Laser Milling: Tool making capabilities
International Congress on Applications of Lasers & Electro-Optics, 2011Co-Authors: Stefan Simeonov Dimov, Petko Vladev Petkov, Franck Lacan, Steffen ScholzAbstract:Laser Milling is a relatively new manufacturing process that has attracted much attention from engineers and researchers for the last decade. The process allows complex parts and tooling inserts to be fabricated directly from 3D CAD data in a wide range of advanced engineering materials such as ceramics, hardened steel, bulk metallic glasses, titanium and nickel alloys. The paper discusses the process design and implementations issues in applying the Laser Milling technology for tool making. Especially, the focus is on design and implementation of appropriate material removal strategies and the necessary optimisation of processing parameters to produce replication tools with required surface integrity and resolution. Two application case studies are used to demonstrate the capabilities of the Laser Milling process, in particular for the fabrication of replication tools for serial manufacture of micro needles arrays for drug delivery and bio inspired surface structures for drag reduction. The paper concludes with a discussion of tool making capabilities and limitations of Laser Milling technology.Laser Milling is a relatively new manufacturing process that has attracted much attention from engineers and researchers for the last decade. The process allows complex parts and tooling inserts to be fabricated directly from 3D CAD data in a wide range of advanced engineering materials such as ceramics, hardened steel, bulk metallic glasses, titanium and nickel alloys. The paper discusses the process design and implementations issues in applying the Laser Milling technology for tool making. Especially, the focus is on design and implementation of appropriate material removal strategies and the necessary optimisation of processing parameters to produce replication tools with required surface integrity and resolution. Two application case studies are used to demonstrate the capabilities of the Laser Milling process, in particular for the fabrication of replication tools for serial manufacture of micro needles arrays for drug delivery and bio inspired surface structures for drag reduction. The paper conclud...
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Techniques for improving surface quality after Laser Milling
Proceedings of the Institution of Mechanical Engineers Part B: Journal of Engineering Manufacture, 2008Co-Authors: Todor Dobrev, Duc Truong Pham, Stefan Simeonov DimovAbstract:The major drawbacks of long-pulse Laser Milling are the deposition of debris on the target surface and the formation of recast layers. The removal of debris becomes very important when Laser Milling is employed as a technology for microstructuring and especially for machining micro-cavities for a number of replication technologies. For such applications, the surface quality of the manufactured geometry becomes even more important due to the micro sizes of the machined features. A recast layer is also formed on the Laser-milled surfaces. It generally consists of metal oxides and has different material properties from those of the bulk of the material. This paper discusses cleaning techniques for removing the debris, contaminations, and recast layers from micro-structures, and thus improving the surface quality of finished products. In particular, four techniques are investigated in this research: Laser cleaning, ultrasonic cleaning, deoxidization (or pickling), and electrochemical polishing.
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Laser Milling pulse duration effects on surface integrity
Proceedings of the Institution of Mechanical Engineers Part B: Journal of Engineering Manufacture, 2008Co-Authors: Petko Vladev Petkov, Stefan Simeonov Dimov, Roussi Minev, D T PhamAbstract:Laser Milling of engineering materials is a viable alternative to conventional methods for machining complex microcomponents. The Laser source employed to perform such microstructuring has a direct impact on achievable surface integrity. At the same time, the trade-offs between high removal rates and the resulting surface integrity should be taken into account when selecting the most appropriate ablation regime for performing Laser Milling. In this paper the effects of pulse duration on surface quality and material microstructure are investigated when ablating a material commonly used for manufacturing microtooling inserts. For both micro- and nanosecond Laser regimes, it was estimated that the heat-affected zone on the processed surface is within 50 μm. When performing ultra-short pulsed Laser ablation, the effects of heat transfer are not as evident as they are after processing with longer Laser pulse durations. Although some heat is dissipated into the bulk when working in pico- and femtosecond regimes it is not sufficient to trigger significant structural changes.
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Strategies for material removal in Laser Milling
2008Co-Authors: Petko Vladev Petkov, Steffen Scholz, Stefan Simeonov DimovAbstract:Laser Milling with microsecond pulses is a thermal material removal process usually associated with detrimental effects such as heat affected zones (HAZ), a recast layer and debris. Process optimisation can lead to considerable reduction of the above mentioned negative effects. In this context, the research investigates the effects of tool path optimisation and material removal strategies on the resultant surface quality and edge definition. The conducted experimental study shows clearly that the applied Milling strategies have a significant effect on the resulting surface topography and the edge definition. Also, the research demonstrates that by optimising the Laser path and material removal strategies it is possible to reduce significantly the thermal load when Milling micro features, and thus to minimise HAZ and other secondary effects.
Emilio Corchado - One of the best experts on this subject based on the ideXlab platform.
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Optimizing the operating conditions in a high precision industrial process using soft computing techniques
Expert Systems, 2011Co-Authors: Emilio Corchado, Javier Sedano, Leticia Curiel, José R. VillarAbstract:This interdisciplinary research is based on the application of unsupervized connectionist architectures in conjunction with modelling systems and on the determining of the optimal operating conditions of a new high precision industrial process known as Laser Milling. Laser Milling is a relatively new micro-manufacturing technique in the production of high-value industrial components. The industrial problem is defined by a data set relayed through standard sensors situated on a Laser-Milling centre, which is a machine tool for manufacturing high-value micro-moulds, micro-dies and micro-tools. The new three-phase industrial system presented in this study is capable of identifying a model for the Laser-Milling process based on low-order models. The first two steps are based on the use of unsupervized connectionist models. The first step involves the analysis of the data sets that define each case study to identify if they are informative enough or if the experiments have to be performed again. In the second step, a feature selection phase is performed to determine the main variables to be processed in the third step. In this last step, the results of the study provide a model for a Laser-Milling procedure based on low-order models, such as black-box, in order to approximate the optimal form of the Laser-Milling process. The three-step model has been tested with real data obtained for three different materials: aluminium, cooper and hardened steel. These three materials are used in the manufacture of micro-moulds, micro-coolers and micro-dies, high-value tools for the medical and automotive industries among others. As the model inputs are standard data provided by the Laser-Milling centre, the industrial implementation of the model is immediate. Thus, this study demonstrates how a high precision industrial process can be improved using a combination of artificial intelligence and identification techniques. © 2012 Wiley Periodicals, Inc.
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A Soft Computing System for Modelling the Manufacture of Steel Components
Soft Computing Methods for Practical Environment Solutions, 2010Co-Authors: Javier Sedano, José R. Villar, Leticia Curiel, Emilio Corchado, Andres BustilloAbstract:This chapter presents a soft computing system developed to optimize the Laser Milling manufacture of high value steel components, a relatively new and interesting industrial technique. This applied research presents a multidisciplinary study based on the application of unsupervised neural projection models in conjunction with identification systems, in order to find the optimal operating conditions in this industrial issue. Sensors on a Laser Milling centre capture the data used in this industrial case of study defined under the frame of a machine-tool that manufactures steel components for high value molds and dies. Then a detailed study of the Laser Milling manufacture of high value steel components is presented based mainly on the analysis of four features: angle error, depth error, surface roughness and material removal rate. The presented model is based on a two-phases application. The first phase uses an unsupervised neural projection model capable of determine if the data collected is informative enough. The second phase is focus on identifying a model for the Laser-Milling process based on low-order models such as Black Box ones. The whole system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins and Output Error algorithms, which calculate the function of a linear system based on its input and output variables, are the most appropriate models to control such industrial task for the case of the analysed steel tools. The model can be applied to Laser Milling optimization of other materials of industrial interest and also to other industrial multivariable processes like High Speed Milling or Laser Cladding.
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Computer Recognition Systems 3 - A Soft Computing System for Modelling the Manufacture of Steel Components
Advances in Intelligent and Soft Computing, 2009Co-Authors: Andres Bustillo, Javier Sedano, José R. Villar, Leticia Curiel, Emilio CorchadoAbstract:In this paper we present a soft computing system developed to optimize the Laser Milling manufacture of high value steel components, a relatively new and interesting industrial technique. This multidisciplinary study is based on the application of neural projection models in conjunction with identification systems, in order to find the optimal operating conditions in this industrial issue. Sensors on a Laser Milling centre capture the data used in this industrial case study defined under the frame of a machine-tool that manufactures steel components like high value molds and dies. The presented model is based on a two-phase application. The first phase uses a neural projection model capable of determine if the data collected is informative enough based on the existence of internal patterns. The second phase is focus on identifying a model for the Laser-Milling process based on low-order models such as Black Box ones. The whole system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples, is the most appropriate model to control such industrial task for the case of steel components.
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IDEAL - AI for Modelling the Laser Milling of Copper Components
Lecture Notes in Computer Science, 2008Co-Authors: Andres Bustillo, Javier Sedano, José R. Villar, Leticia Curiel, Emilio CorchadoAbstract:Laser Milling is a relatively new micromanufacturing technique in the production of copper and other metallic components. This study presents multidisciplinary research, which is based on unsupervised connectionist architectures in conjunction with modelling systems, on the determination of the optimal operating conditions in this industrial process. Sensors on a Laser Milling centre relay the data used in this industrial case study of a machine-tool that manufactures copper components for high value micro-coolers. The two-phase application of the connectionist architectures is capable of identifying a model for the Laser-Milling process based on low-order models such as Black Box. The final system is capable of approximating the optimal form of the model. Finally, it is shown that the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples, is the most appropriate model to control these industrial tasks.
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EMS - Conventional Methods and AI models for Solving an Industrial an Industrial Problem
2008 Second UKSIM European Symposium on Computer Modeling and Simulation, 2008Co-Authors: Andres Bustillo, Javier Sedano, José R. Villar, Leticia Curiel, Emilio CorchadoAbstract:This study presents a research that identifies and applies unsupervised connectionist models in conjunction with modelling systems, in order todetermine optimal conditions to perform Laser Milling of metallic components. This industrial problem is defined by a data set relayed through sensors situated on a Laser Milling centre that is a machine-tool used to manufacture high value micro-molds and micro-dies. The results of the study and the application of the connectionist architectures allow the identification, in a second phase, of a model for the Milling machine process based on low-order models such as Black Box, which are capable of approximating the optimal form of the model. Finally, it is shown that the most appropriate model to control these industrial tasks is the Box-Jenkins algorithm, which calculates the function of a linear system from its input and output samples.
