Date of Award
Open Access Thesis
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 stage.
This work begins with a ranking process which was performed through a survey of the Advanced Composites Consortium (ACC) Collaborative Research Team (CRT). Members were interviewed who possessed practical process planning experience in the composites industry. The Process Planning survey collected general input on the overall importance and time requirements for each function and which functions would benefit most greatly from semi-automation or full automation. Layup strategies, in addition to dog ears, stagger shifts, steering constraints, and starting points, represented the group of functions labeled as process optimization and ranked the highest in terms of priority for automation. The laminates resulting from the selected parameters are evaluated through the occurrences of principal defect metrics such as fiber gaps, overlaps, angle deviation and steering violations.
This document presents an automated software solution to the layup strategy and starting point selection phase of Process Planning. A series of ply scenarios are generated with variations of these ply parameters and evaluated according to a set of metrics entered by the Process Planner. These metrics are generated through use of the Analytical Hierarchy Process (AHP), where relative importance between each of the fiber features are defined. The ply scenarios are selected which reduce the overall fiber feature scores based on the defects the Process Planner wishes to minimize.
Halbritter, J. A.(2020). Automation of Process Planning for Automated Fiber Placement. (Master's thesis). Retrieved from https://scholarcommons.sc.edu/etd/5953