Joaquim Ciurana

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications.

Influence of Process Parameters and Electrode Geometry on Feature Micro-Accuracy in Electro Discharge Machining of Tool Steel

Agile manufacturing capabilities require fast responses in workshops to cope with different demands in product geometrical features and qualities in fabricating moulds. Therefore, direct machining of complex mould features using simple shape machined electrodes with the electro-discharge machining (EDM) process, empowers the flexibility and the capacity of the enterprises and dramatically reduces lead times resulting in much more efficient production processes. In the case of machining geometrical features with characteristic dimensions in the order of few millimeters, the EDM process requires further understanding. This article focuses on investigating the influence of EDM parameters and electrode geometry on feature micro-accuracy in tool steel for mould fabrication purposes. A set of designed experiments with varying EDM process parameters such as pulsed current, open voltage, pulse time, and pulse pause time is carried out in H13 steel using differently shaped copper electrodes. Microdimensional and geometrical accuracies are the measures of response. Artificial neural network and regression models have been constructed to capture the influence of the process parameters on the geometrical feature quality such as flatness, depth, slope, width, and dimension variation between the entrance and the exit (DVEE).

Design of a decision support system for machine tool selection based on machine characteristics and performance tests

Economic globalization, together with heightened market competition and increasingly short product life cycles are motivating companies to use advanced manufacturing technologies. Use of high speed machining is increasingly widespread; however, as the technology is relatively new, it lacks a deep-rooted knowledge base which would facilitate implementation. One of the most frequent problems facing companies wishing to adopt this technology is selecting the most appropriate machine tool for the product in question and own enterprise characteristics. This paper presents a decision support system for high speed milling machine tool selection based on machine characteristics and performance tests. Profile machining tests are designed and conducted in participating machining centers. The decision support system is based on product dimension accuracy, process parameters such as feed rate and interpolation scheme used by CNC and machine characteristics such as machine accuracy and cost. Experimental data for process error and cycle operation time are obtained from profile machining tests with different geometrical feature zones that are often used in manufacturing of discrete parts or die/moulds. All those input parameters have direct impact on productivity and manufacturing cost. Artificial neural network models are utilized for decision support system with reasonable prediction capability.

Modelling Power Consumption in Ball-End Milling Operations

Power consumption is a factor of increasing interest in manufacturing due to its obvious impact on production costs and the environment. The aim of this work is to analyze the influence of process parameters on power consumption in high-speed ball-end milling operations carried out on AISI H13 steel. A total of 300 experiments were carried out in a 3-axis vertical milling center, the Deckel-Maho 105 V linear. The power consumed by the spindle and by the X, Y, and Z machine tool axes was measured using four ammeters located in the respective power cables. The data collected was used to develop an artificial neural network (ANN) which was used to predict power consumption during operations. The results obtained from the ANN are very accurate. Power consumption predictions can help operators to determine the most effective cutting parameters for saving energy and money while bringing the milling process closer to the goal of environmentally sensitive manufacturing which has become a topic of general importance.

A system based on machined volumes to reduce the number of route sheets in process planning

The paper focuses on the problem of choosing the manufacturing route in metal removal processes, which is very important for the Computer Aided Process Planning (CAPP) systems.A method consisting in establishing groups of precedence between machine operations has been proposed, in order to reduce the number of possible routes. This reduction is based on the elimination of the routes which are not technologically possible, despite being mathematically computable.A wide range of parts has been evaluated, using group technology for choosing the representative cases. For the different parts, the mathematically possible routes have been generated. Graph Theory has been used to determine the precedence between operations.The application of this method permits to reduce considerably the number of possibilities that must be computed, and therefore, the route sheet is obtained more quickly and the computational resources are used more efficiently.

Pursuing successful rapid manufacturing: a users' best‐practices approach

Purpose – This paper seeks to present the results of a study carried out within rapid manufacturing (RM) service providers and engineering centres in Northern Spain. By disclosing strategies for their everyday operation, it is intended to show how the internal expertise acquired overtime copes with the lack of standards within this industry.Design/methodology/approach – The study was deployed by means of a survey including four main issues: RM concepts, process planning, materials and costs. Questions range from general RM perceptions to specific production criteria like: layer thicknesses, laser power, quality assurance methods, etc. A special emphasis is made on cost parameters, since they play a major role when selecting the final manufacturing route.Findings – The so‐called “de facto standards” were found to be widely used in order to minimize production risks for RM. The study also suggests the need for specific RM standards based on key issues like material recycling, process planning and costs assi...

Rapid tooling using 3D printing system for manufacturing of customized tracheal stent

Purpose – This work aims to present the design of a new continuous tool-path strategy for open-source low-cost fused deposition modeling (FDM) machines, such as Fab@Home or RepRap; and the development of an innovative integrated tool to design and fabricate customized tracheal stents with any FDM machine and six patient parameters. Both contributions were validated and implemented by obtaining a customized medical-grade silicone tracheal stent. Design/methodology/approach – For the design of the new deposition strategy, a Python programming language was used. The new tool-path strategy was proposed as a continuous path to avoid drops and gaps and to improve the accuracy of the final model. Meanwhile, patient parameters were obtained by medical doctors and introduced into the innovative integrated system. On the one hand, one mold generated automatically, and viewed with Matlab® software, was fabricated with a Fab@Home machine, optimized with the continuous tool-path strategy. On the other hand, the same g...

Prediction, monitoring and control of surface roughness in high-torque milling machine operations

The development and testing of an application that will predict, monitor and control surface roughness are described. It comprises three modules for off-line roughness prediction, surface roughness monitoring and surface roughness control, and is especially designed for high-torque, high-power milling operations, which are widely used nowadays in the manufacture of wind turbine components. The application is tested in a milling machine with a high working volume. Due to the highly complex phenomena that generate surface roughness and the large number of factors that interact during the cutting process, models to calculate the average surface roughness parameter (Ra) are based on artificial neural networks (ANN) as they are especially suitable for modelling complex relationships between inputs and outputs.

Tool electrode geometry and process parameters influence on different feature geometry and surface quality in electrical discharge machining of AISI H13 steel

Electro discharge machining process (EDM) is frequently used when machining of high complex and accurate features is required. Indeed, it is specially recommended for hard materials and micro-machined features. However, due to the process nature, there is still incomprehension on process parameters influence at the final quality features, ending up by lower productivity and quality ratios. On the other hand, fashioning and re-shaping of required electrodes for each feature are time consuming phases and the number of stored electrodes is very high. Therefore, in order to increase the global EDM process productivity, quality and flexibility, standardized simple electrode shapes, capable to machine different features, must be found. This study presents the influence of the main EDM process parameters and different tool geometries on basic process performance measures. A set of designed experiments with varying parameters such as pulsed current, open voltage, pulse time and pulse pause time are carried out in H13 steel using different geometries of copper electrodes. In addition, material removal rate , surface roughness and different dimensional and geometrical micro-accuracies are analyzed through statistical methods. Results help to select appropriate EDM process parameters to machine parts depending on product requirements.

Comparison of forming manufacturing processes and selective laser melting technology based on the mechanical properties of products

This study analyses the behaviour of real parts produced with Selective Laser Melting (SLM) during traction, compression and flexure tests compared to conventionally processed products. Comparisons help industrial companies to evaluate the advantages and drawbacks of SLM against forming manufacturing technologies. Three-dimensional (3D) models of four conventional final products were generated by 3D scanning. Force and elongation were measured in a testing machine and the characteristics of the final products were compared. The experiments conducted show that parts produced with SLM technology can better support forces and elongations than parts produced with forming manufacturing technologies. It was assumed that process parameters, building direction, and material all have an effect on mechanical properties. Process parameters given by machine vendors are used to manufacture the parts. The comparison of mechanical properties between forming and SLM technologies provides useful knowledge for mechanical parts development. Spare parts have a good future in SLM technology. This work quantifies the performance of the SLM technique when it comes to producing real mechanical parts. It shows that the SLM technique produces better results than the forming process.