为新产品开发改善3D打印原型的感觉:通过优化填充结构和材料模拟质量特性的可行性研究

IF 1.8 Q3 ENGINEERING, MANUFACTURING Design Science Pub Date : 2023-07-24 DOI:10.1017/dsj.2023.18
H. Felton, J. Yon, B. Hicks
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引用次数: 0

摘要

产品原型,特别是那些3D打印的产品,其质量特性与它们所代表的产品有很大的不同。这既影响功能性能,也影响涉众对原型的看法。在这项工作中,考虑了原始物体(立方体)的质量特性的计算仿真,开发了一种基线数值方法和参数集,目的是展示改善3D打印原型感觉的方法。然后将该方法应用于三个案例研究产品-游戏控制器,手钻和激光笔-证明产品质量特性可以在数值模拟中达到目标值的1%以内。这是使用典型的材料挤压技术实现的,没有物理或工艺修改。仿真结果表明,仿真精度取决于质量中心与几何中心的相对偏移量。进一步进行敏感性分析,以证明产品特定参数可能是有益的。通过对这些值进行调优,并忽略一些实际限制,可以实现高达~99.8%的仿真精度。与传统制造相比,这一方法的误差降低了99.6%。
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Improving the feel of 3D printed prototypes for new product development: A feasibility study of emulating mass properties by optimising infill structures and materials
Abstract Product prototypes and particularly those that are 3D printed will have mass properties that are significantly different from the product they represent. This affects both functional performance and stakeholder perception of the prototype. Within this work, computational emulation of mass properties for a primitive object (a cube) is considered, developing a baseline numerical method and parameter set with the aim of demonstrating the means of improving feel in 3D printed prototypes. The method is then applied and tuned for three case study products – a games controller, a hand drill and a laser pointer – demonstrating that product mass properties could be numerically emulated to within ~1% of the target values. This was achieved using typical material extrusion technology with no physical or process modification. It was observed that emulation accuracy is dependent on the relative offset of the centre of mass from the geometric centre. A sensitivity analysis is further undertaken to demonstrate that product-specific parameters can be beneficial. With tuning of these values, and with some neglect of practical limitations, emulation accuracy as high as ~99.8% can be achieved. This was shown to be a reduction in error of up to 99.6% relative to a conventional fabrication.
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来源期刊
Design Science
Design Science ENGINEERING, MANUFACTURING-
CiteScore
4.80
自引率
12.50%
发文量
19
审稿时长
22 weeks
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