1,546 research outputs found

    A comparison of processing techniques for producing prototype injection moulding inserts.

    Get PDF
    This project involves the investigation of processing techniques for producing low-cost moulding inserts used in the particulate injection moulding (PIM) process. Prototype moulds were made from both additive and subtractive processes as well as a combination of the two. The general motivation for this was to reduce the entry cost of users when considering PIM. PIM cavity inserts were first made by conventional machining from a polymer block using the pocket NC desktop mill. PIM cavity inserts were also made by fused filament deposition modelling using the Tiertime UP plus 3D printer. The injection moulding trials manifested in surface finish and part removal defects. The feedstock was a titanium metal blend which is brittle in comparison to commodity polymers. That in combination with the mesoscale features, small cross-sections and complex geometries were considered the main problems. For both processing methods, fixes were identified and made to test the theory. These consisted of a blended approach that saw a combination of both the additive and subtractive processes being used. The parts produced from the three processing methods are investigated and their respective merits and issues are discussed

    Selected Papers from IEEE ICASI 2019

    Get PDF
    The 5th IEEE International Conference on Applied System Innovation 2019 (IEEE ICASI 2019, https://2019.icasi-conf.net/), which was held in Fukuoka, Japan, on 11–15 April, 2019, provided a unified communication platform for a wide range of topics. This Special Issue entitled “Selected Papers from IEEE ICASI 2019” collected nine excellent papers presented on the applied sciences topic during the conference. Mechanical engineering and design innovations are academic and practical engineering fields that involve systematic technological materialization through scientific principles and engineering designs. Technological innovation by mechanical engineering includes information technology (IT)-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology. These new technologies that implant intelligence in machine systems represent an interdisciplinary area that combines conventional mechanical technology and new IT. The main goal of this Special Issue is to provide new scientific knowledge relevant to IT-based intelligent mechanical systems, mechanics and design innovations, and applied materials in nanoscience and nanotechnology

    Robotic Training for the Integration of Material Performances in Timber Manufacturing

    Get PDF
    The research focuses on testing a series of material-sensitive robotic training methods that flexibly extend the range of subtractive manufacturing processes available to designers based on the integration of manufacturing knowledge at an early design stage. In current design practices, the lack of feedback information between the different steps of linear design workflows forces designers to engage with only a limited range of standard materials and manufacturing techniques, leading to wasteful and inefficient solutions. With a specific focus on timber subtractive manufacturing, the work presented in this thesis addresses the main issue hindering the utilisation of non-standard tools and heterogeneous materials in design processes which is the significant deviation between what is prescribed in the digital design environment and the respective fabrication outcome. To begin, it has been demonstrated the extent to which the heterogeneous properties of timber affect the outcome of the robotic carving process beyond the acceptable tolerance thresholds for design purposes. Resting on this premise, the devised strategy to address such a material variance involved capturing, transferring, augmenting and integrating manufacturing knowledge through the collection of real- world fabrication data, both by human experts and robotic sessions, and training of machine learning models (i.e. Artificial Neural Networks) to achieve an accurate simulation of the robotic manufacturing task informed by specific sets of tools affordances and material behaviours. The results of the training process have demonstrated that it is possible to accurately simulate the carving process to a degree sufficient for design applications, anticipating the influence of material and tool properties on the carved geometry. The collaborations with the industry partners of the project, ROK Architects (ZĂĽrich) and BIG (Copenhagen), provided the opportunity to assess the different practical uses and related implications of the tools in a real-world scenario following an open-ended and explorative approach based on several iterations of the full design-to-production cycle. The findings have shown that the devised strategy supports decision-making procedures at an early stage of the design process and enables the exploration of novel, previously unavailable, solutions informed by material and tool affordances
    • …
    corecore