Thickness control of autoclave-moulded composite laminates

IF 2.4 3区 工程技术 Q3 ENGINEERING, MANUFACTURING Journal of Manufacturing Science and Engineering-transactions of The Asme Pub Date : 2023-05-22 DOI:10.1115/1.4062581
E. Gongadze, Chris Dighton, Gregory Nash, Martin Moss, Brett Hemingway, J. Belnoue, S. Hallett
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Abstract

Composite materials and especially those made from pre-impregnated (prepreg) material are widely used in the aerospace industry. To achieve the tight assembly dimensional tolerances required, manufacturers rely on additional manufacturing steps like shimming or machining, which generate extra waste, are time-consuming and expensive. Prepreg sheets come naturally with fibre and resin volume content variability that leads manufacturers to guarantee cured ply thicknesses within a typical +/-5% margin of their nominal values. For thick laminates, this can equate to a thickness variability of as much as a few mm. To solve the issue, it is proposed to twin in-situ laser measurements of the uncured prepreg thickness with numerical simulations of the laminate autoclave consolidation and cure process and to adjust the number of additional sacrificial plies in the laminate based on the model predictions. Data for IM7/8552 and IM7/977-3 is presented to demonstrate the potential of the method to reach an almost exact target thickness for flat panels.
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热压成型复合层压板的厚度控制
复合材料,特别是由预浸渍(prepreg)材料制成的复合材料广泛应用于航空航天工业。为了实现所需的严格装配尺寸公差,制造商依赖于额外的制造步骤,如摆振或加工,这会产生额外的浪费,既耗时又昂贵。预浸板具有天然的纤维和树脂体积含量变化,这使得制造商能够保证固化厚度在其标称值的+/-5%范围内。对于厚层压板,这可能相当于厚度变化高达几毫米。为了解决这个问题,建议将未固化预浸料厚度的原位激光测量与层压板高压灭菌器固结和固化过程的数值模拟相结合,并根据模型预测调整层压板中额外牺牲层的数量。给出了IM7/8552和IM7/977-3的数据,以证明该方法在达到平板几乎精确的目标厚度方面的潜力。
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来源期刊
CiteScore
6.80
自引率
20.00%
发文量
126
审稿时长
12 months
期刊介绍: Areas of interest including, but not limited to: Additive manufacturing; Advanced materials and processing; Assembly; Biomedical manufacturing; Bulk deformation processes (e.g., extrusion, forging, wire drawing, etc.); CAD/CAM/CAE; Computer-integrated manufacturing; Control and automation; Cyber-physical systems in manufacturing; Data science-enhanced manufacturing; Design for manufacturing; Electrical and electrochemical machining; Grinding and abrasive processes; Injection molding and other polymer fabrication processes; Inspection and quality control; Laser processes; Machine tool dynamics; Machining processes; Materials handling; Metrology; Micro- and nano-machining and processing; Modeling and simulation; Nontraditional manufacturing processes; Plant engineering and maintenance; Powder processing; Precision and ultra-precision machining; Process engineering; Process planning; Production systems optimization; Rapid prototyping and solid freeform fabrication; Robotics and flexible tooling; Sensing, monitoring, and diagnostics; Sheet and tube metal forming; Sustainable manufacturing; Tribology in manufacturing; Welding and joining
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