Intelligent conceptual mould layout design system (ICMLDS) : innovation report

Family Mould Cavity Runner Layout Design (FMCRLD) is the most demanding and critical task in the early Conceptual Mould Layout Design (CMLD) phase. Traditional experience-dependent manual FCMRLD workflow results in long design lead time, non-optimum designs and costs of errors. However, no previous research, existing commercial software packages or patented technologies can support FMCRLD automation and optimisation. The nature of FMCRLD is non-repetitive and generative. The complexity of FMCRLD optimisation involves solving a complex two-level combinatorial layout design optimisation problem. This research first developed the Intelligent Conceptual Mould Layout Design System (ICMLDS) prototype based on the innovative nature-inspired evolutionary FCMRLD approach for FMCRLD automation and optimisation using Genetic Algorithm (GA) and Shape Grammar (SG). The ICMLDS prototype has been proven to be a powerful intelligent design tool as well as an interactive design-training tool that can encourage and accelerate mould designers’ design alternative exploration, exploitation and optimisation for better design in less time. This previously unavailable capability enables the supporting company not only to innovate the existing traditional mould making business but also to explore new business opportunities in the high-value low-volume market (such as telecommunication, consumer electronic and medical devices) of high precision injection moulding parts. On the other hand, the innovation of this research also provides a deeper insight into the art of evolutionary design and expands research opportunities in the evolutionary design approach into a wide variety of new application areas including hot runner layout design, ejector layout design, cooling layout design and architectural space layout design

Computer Aided Design of Side Actions for Injection Molding of Complex Parts

Often complex molded parts include undercuts, patches on the part boundaries that are not accessible along the main mold opening directions. Undercuts are molded by incorporating side actions in the molds. Side actions are mold pieces that are removed from the part using translation directions different than the main mold opening direction. However, side actions contribute to mold cost by resulting in an additional manufacturing and assembly cost as well as by increasing the molding cycle time. Therefore, generating shapes of side actions requires solving a complex geometric optimization problem. Different objective functions may be needed depending upon different molding scenarios (e.g., prototyping versus large production runs). Manually designing side actions is a challenging task and requires considerable expertise. Automated design of side actions will significantly reduce mold design lead times. This thesis describes algorithms for generating shapes of side actions to minimize a customizable molding cost function. Given a set of undercut facets on a polyhedral part and the main parting direction, the approach works in the following manner. First, candidate retraction space is computed for every undercut facet. This space represents the candidate set of translation vectors that can be used by the side action to completely disengage from the undercut facet. As the next step, a discrete set of feasible, non-dominated retractions is generated. Then the undercut facets are grouped into undercut regions by performing state space search over such retractions. This search step is performed by minimizing the customizable molding cost function. After identifying the undercut regions that can share a side action, the shapes of individual side actions are computed. The approach presented in this work leads to practically an optimal solution if every connected undercut region on the part requires three or fewer side actions. Results of computational experiments that have been conducted to assess the performance of the algorithms described in the thesis have also been presented. Computational results indicate that the algorithms have acceptable computational performance, are robust enough to handle complex part geometries, and are easy to implement. It is anticipated that the results shown here will provide the foundations for developing fully automated software for designing side actions in injection molding

Automated Parting Methodologies for Injection Moulds

Ph.DDOCTOR OF PHILOSOPH

Estudio de las variables de inyección de termoplásticos a partir de la forma de la pieza mediante herramientas CAD, CAE

En el estudio siguiente, partiendo de una familia de piezas con volumen constante trata de establecer la relación existente entre la presión de inyección, fuerza de cierre, presión de compactación, temperatura de flujo, etc, con la variación de las dimensiones de la pieza, la pieza a estudio es una pieza plana la cual se ve modificada en sus dimensiones principales, alto, ancho y alto. Los métodos empleados son el DOE y la superficie respuesta.Gámez Martínez, JL. (2011). Estudio de las variables de inyección de termoplásticos a partir de la forma de la pieza mediante herramientas CAD, CAE. Universitat Politècnica de València. http://hdl.handle.net/10251/59887Archivo delegad

Algorithms for generating multi-stage molding plans for articulated assemblies

Plastic products such as toys with articulated arms, legs, and heads are traditionally produced by first molding individual components separately, and then assembling them together. A recent alternative, referred to as in-mold assembly process, performs molding and assembly steps concurrently inside the mold itself. The most common technique of performing in-mold assembly is through multi-stage molding, in which the various components of an assembly are injected in a sequence of molding stages to produce the final assembly. Multi-stage molding produces better-quality articulated products at a lower cost. It however, gives rise to new mold design challenges that are absent from traditional molding. We need to develop a molding plan that determines the mold design parameters and sequence of molding stages. There are currently no software tools available to generate molding plans. It is difficult to perform the planning manually because it involves evaluating large number of combinations and solving complex geometric reasoning problems. This dissertation investigates the problem of generating multi-stage molding plans for articulated assemblies. The multi-stage molding process is studied and the underlying governing principles and constraints are identified. A hybrid planning framework that combines elements from generative and variant techniques is developed. A molding plan representation is developed to build a library of feasible molding plans for basic joints. These molding plans for individual joints are reused to generate plans for new assemblies. As part of this overall planning framework, we need to solve the following geometric subproblems -- finding assembly configuration that is both feasible and optimal, finding mold-piece regions, and constructing an optimal shutoff surface. Algorithms to solve these subproblems are developed and characterized. This dissertation makes the following contributions. The representation for molding plans provides a common platform for sharing feasible and efficient molding plans for joints. It investigates the multi-stage mold design problem from the planning perspective. The new hybrid planning framework and geometric reasoning algorithms will increase the level of automation and reduce chances of design mistakes. This will in turn reduce the cost and lead-time associated with the deployment of multi-stage molding process

Análisis de fabricabilidad de piezas conformadas por moldeo por inyección de polvos

Una de las primeras etapas en el Ciclo de Desarrollo Producto-Proceso es el Diseño Conceptual del producto. El Diseño Conceptual define el concepto físico del producto, estableciendo los principios para el ejercicio de su función e identificando sus geometrías características. Un diseño puede ser difícil de fabricar, originando defectos y parámetros inadecuados durante el proceso de fabricación que dan lugar a la necesidad de cambios en ingenieria que, a su vez, aumentan el tiempo de puesta en el mercado. Disponer de una herramienta de asesoramiento automático capaz de mostrar la influencia del diseño en la fabricabilidad de la pieza en un tiempo reducido resulta esencial en el Diseño Conceptual. Con una metodología de este tipo, se ofrece la posibilidad de estimar la calidad final de la pieza y su funcionalidad incluso antes de que se proceda con su fabricación. Una herramienta de asesoramiento que relaciona el diseño del producto con su fabricabilidad debe estar basada en el conocimiento de los procesos que rigen las etapas del proceso de fabricación. Relacionar la geometría del producto con su fabricabilidad utilizando dicho conocimiento permite estimar la viabilidad del producto antes de ser fabricado, mejorando el diseño del producto y evitando los costosos cambios de ingeniería que son necesarios cuando se detectan problemas en la fase de producción. En los procesos de conformado por inyección unos de los aspectos más importantes de la fabricabilidad son la posibilidad de moldeo/desmoldeo, un llenado completo y uniforme y una distribución de espesores uniforme o con cambios suaves. Todos estos aspectos están claramente relacionados con la geometría de la pieza. En esta Tesis Doctoral se detallan las bases para el desarrollo de una herramienta capaz de estimar de forma automática e integrada la fabricabilidad de una pieza conformada por el Moldeo por Inyección de Polvos (MIP). El MIP es un proceso de conformado que incluye la etapa de inyección por loPetrovic, V. (2008). Análisis de fabricabilidad de piezas conformadas por moldeo por inyección de polvos [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/2284Palanci

ANÁLISIS DE LA DEFORMACIÓN EN LA INYECCIÓN DE TERMOPLÁSTICOS BAJO VARIABLES DE FORMA DE LA PIEZA MEDIANTE RED NEURONAL Y SUPERFICIES RESPUESTA

La gran parte de productos de consumo contienen partes realizadas a través del proceso de inyección de termoplásticos, esto constata la importancia de este proceso de conformado con respecto a otros procesos de transformación de plástico. La minimización de los costes para ser más competitivos así como la eliminación o reducción de defectos en las piezas inyectadas, han sido los motivos principales para controlar el proceso a través de la optimización de las variables que entran en juego en este proceso, es por ello que se han realizado numerosos estudios referentes a obtener las relaciones existentes entre las variables del proceso y los aspectos de rentabilidad, estética y defectología de las piezas inyectadas. Modelizar dichas relaciones a través de algoritmos matemáticos con el fin de optimizar los resultados obtenidos y predecir el estado final de las piezas inyectadas han sido los objetivos de la mayoría de estudios. Uno de los efectos intrínsecos a la inyección es la deformación de la pieza, esta deformación tiene lugar debido a distintos factores que intervienen en el diseño del proceso en su conjunto, diferencias en la contracción, diferencias en la refrigeración, las esquinas de la pieza, la orientación molecular, etc son elementos condicionantes de la deformación que se han estudiado en infinidad de artículos, en esta divulgación científica se estudiará la deformación bajo aspectos dimensionales de la pieza con la finalidad de intentar descubrir y optimizar las condiciones de entrada que en este caso serían las dimensiones de la pieza a través de la observación y modelización de las variables de salida que seria la deformación. Y la pregunta que nos realizamos es ¿Cómo varían las deformaciones modificando las dimensiones de la pieza? ¿Cuáles son las dimensiones de la pieza a estudio que minimizan los efectos negativos de la deformación? ¿se puede predecir la deformación que obtendremos en una pieza solo con las dimensiones de una pieza? A todas estas preguntas intentamos dar respuesta en el estudio siguiente.Gámez Martínez, JL. (2014). ANÁLISIS DE LA DEFORMACIÓN EN LA INYECCIÓN DE TERMOPLÁSTICOS BAJO VARIABLES DE FORMA DE LA PIEZA MEDIANTE RED NEURONAL Y SUPERFICIES RESPUESTA [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/39350TESI

Friction Force Microscopy of Deep Drawing Made Surfaces

Aim of this paper is to contribute to micro-tribology understanding and friction in micro-scale interpretation in case of metal beverage production, particularly the deep drawing process of cans. In order to bridging the gap between engineering and trial-and-error principles, an experimental AFM-based micro-tribological approach is adopted. For that purpose, the can’s surfaces are imaged with atomic force microscopy (AFM) and the frictional force signal is measured with frictional force microscopy (FFM). In both techniques, the sample surface is scanned with a stylus attached to a cantilever. Vertical motion of the cantilever is recorded in AFM and horizontal motion is recorded in FFM. The presented work evaluates friction over a micro-scale on various samples gathered from cylindrical, bottom and round parts of cans, made of same the material but with different deep drawing process parameters. The main idea is to link the experimental observation with the manufacturing process. Results presented here can advance the knowledge in order to comprehend the tribological phenomena at the contact scales, too small for conventional tribology

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems

Towards a Conceptual Design of an Intelligent Material Transport Based on Machine Learning and Axiomatic Design Theory

Reliable and efficient material transport is one of the basic requirements that affect productivity in sheet metal industry. This paper presents a methodology for conceptual design of intelligent material transport using mobile robot, based on axiomatic design theory, graph theory and artificial intelligence. Developed control algorithm was implemented and tested on the mobile robot system Khepera II within the laboratory model of manufacturing environment. Matlab© software package was used for manufacturing process simulation, implementation of search algorithms and neural network training. Experimental results clearly show that intelligent mobile robot can learn and predict optimal material transport flows thanks to the use of artificial neural networks. Achieved positioning error of mobile robot indicates that conceptual design approach can be used for material transport and handling tasks in intelligent manufacturing systems