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

Automation and optimisation of Family Mould Cavity and Runner Layout Design (FMCRLD) using genetic algorithms and mould layout design grammars

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 causes long design lead time, non-optimum designs and human errors. However, no previous research 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. Inspired by the theory of evolutionary design in nature “Survival of the Fittest” and the biological genotype–phenotype mapping process of the generation of form in living systems, this research first proposes an innovative evolutionary FMCRLD approach using Genetic Algorithms (GA) and Mould Layout Design Grammars (MLDG) that can automate and optimise such generative and complex FMCRLD with its explorative and generative design process embodied in a stochastic evolutionary search. Based on this approach, an Intelligent Conceptual Mould Layout Design System (ICMLDS) prototype has been developed. The ICMLDS is a powerful intelligent design system as well as an interactive design-training system that can encourage and accelerate mould designers’ design alternative exploration, exploitation and optimisation for better design in less time. This research innovates the traditional manual FMCRLD workflow to eliminate costly human errors and boost the less-experienced mould designer’s ability and productivity in performing FCMRLD during the CMLD phase

Creating DYOR: Do your own robot an educational robotic toy kit

[EN] This project presents DYOR: an educational robotic toy kit how it helps the school students to get better understanding of the aspects of engineering before they get ready to choose their career. It provides an ideal platform enabling school students understand various elements like science, manufacturing technology, mathematics, design and apply their knowledge in these areas effectively with additional inputs like programming, logical analysis to create solutions for the given task.[ES] Este proyecto presenta DYOR: un kit de juguete robótico educativa cómo ayuda a los estudiantes de la escuela para obtener una mejor comprensión de los aspectos de la ingeniería antes de que se disponen a elegir su carrera. Proporciona una plataforma ideal estudiantes de la escuela que permite comprender diversos elementos como la ciencia, la tecnología de fabricación, las matemáticas, el diseño y aplican sus conocimientos en estas áreas eficazmente con entradas adicionales como la programación, análisis lógico para crear soluciones para la tarea encomendada.Singh, H. (2016). Creating DYOR: Do your own robot an educational robotic toy kit. Universitat Politècnica de València. http://hdl.handle.net/10251/67515TFG