Defect Detection and Mitigation in Advanced Sheet Moulding Compounds

Lead Research Organisation: University of Nottingham
Department Name: Faculty of Engineering


Compression moulding provides a method of manufacturing composite parts faster and more cheaply than more widely-used methods, such as autoclave cure and resin transfer moulding. However, due to the random nature of the materials used in compression moulding, such as Sheet Moulding Compounds (SMCs), the resulting parts can be highly variable. Further, defects, such as surface blisters, pockmarks, internal voids, and wrinkled fibres, are frequently found in parts manufactured by compression moulding. Currently, the causes of these defects and their effects on the mechanical performance of compression moulded parts are poorly understood. This PhD project will therefore focus on studying the causes of variability and defects in SMC parts, their effects on the mechanical properties of the final part, and how they might be reduced.

The first part of this project is to study the variation in parameters such as fibre content and orientation in a commercial prepreg-based carbon SMC. Of particular interest is the effects of this variation on the mechanical performance of and defect formation in parts made from these materials and the effect of said defects on failure and mechanical properties. This part of the research will be carried out by using a method of scanning SMC samples into a CAD model to measure the thickness across the part. The mass variation will also be measured by cutting the samples into small squares and weighing them for comparison with the thickness data. Other samples will be scanned before being compression moulded. These moulded plaques will be subjected to ultrasonic C-scanning, which will determine the locations of internal defects. By comparison with the thickness scans, the relationship between thickness variation and defect formation will be studied. These plaques will then be cut into tensile test coupons, which will be tested using Digital Image Correlation (DIC) for strain measurement. This will show the effect of internal defects on local strain, failure locations, and mechanical properties.

The second part of the project is to investigate ways of reducing variation in SMCs with the goal of reducing the number and size of defects which form. This will be done by chopping regular prepreg and randomly distributing the resulting chips to produce new SMCs with varied parameters, such as the length and aspect ratio of the chips. By subjecting these new SMCs to much of the same testing as described in the previous paragraph, the effects of altering the aforementioned variables will be studied. It will also be necessary to investigate how altering the variables affects the mechanical performance of the part (for example, reducing fibre length reduces strength and stiffness but may also reduce variability and defects) and whether the result is a suitable trade-off.

The third part of the project is the development of a computational model to simulate these materials. Currently, this model places fibres onto a grid with random location and orientation. Later iterations will incorporate data from the first two studies to better represent real SMCs.


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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S515528/1 01/10/2018 30/09/2022
2117023 Studentship EP/S515528/1 01/10/2018 30/09/2022 Daniel John Wilson