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Leveraging Automated Fiber Placement Computer Aided Process Planning Framework For Defect Validation And Dynamic Layup Strategies, Joshua Allen Halbritter
Leveraging Automated Fiber Placement Computer Aided Process Planning Framework For Defect Validation And Dynamic Layup Strategies, Joshua Allen Halbritter
Theses and Dissertations
Process planning represents an essential stage of the Automated Fiber Placement (AFP) workflow. It develops useful and efficient machine processes based upon the working material, composite design, and manufacturing resources. The current state of process planning requires a high degree of interaction from the process planner and could greatly benefit from increased automation. Therefore, a list of key steps and functions are created to identify the more difficult and time-consuming phases of process planning. Additionally, a set of metrics must exist by which to evaluate the effectiveness of the manufactured laminate from the machine code created during the Process Planning …
Comprehensive Process Planning Optimization Framework For Automated Fiber Placement, Alex Ryan Brasington
Comprehensive Process Planning Optimization Framework For Automated Fiber Placement, Alex Ryan Brasington
Theses and Dissertations
Advanced composite materials came about in 1966 and have since been widely used due to the possibility of superior structural performance while also achieving weight reductions. Such opportunities have led to composite materials being used to fabricate complex components, often in the aerospace sector. Most components, especially in aviation, are on a large scale and are outside the capabilities of traditional composite manufacturing techniques. Traditional manufacturing methods are also labor intensive, time consuming, have a high level of material scrap, and are prone to human error. This has led to the need for innovative manufacturing solutions to withstand the ever-increasing …
Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco
Hybrid Theory-Machine Learning Methods For The Prediction Of Afp Layup Quality, Christopher M. Sacco
Theses and Dissertations
The advanced manufacturing capabilities provided through the automated fiber placement (AFP) system has allowed for faster layup time and more consistent production across a number of different geometries. This contributes to the modern production of large composite structures and the widespread adaptation of composites in industry in general and aerospace in particular. However, the automation introduced in this process increases the difficulty of quality assurance efforts. Industry available tools for predicting layup quality are either limited in scope, or have extremely high computational overhead. With the advent of automated inspection systems, direct capture of semantic inspection data, and therefore complete …