EFFECT OF PROCESSING PARAMETERS ON THE WIDTHS AND THICKNESSES OF THERMOPLASTIC COMPOSITES MADE BY AUTOMATED FIBER PLACEMENT

The advent of Automated Fiber Placement (AFP) machine has expanded the capacities to manufacture engineering structures using thermoplastic composites. Structures of cylindrical shapes, flat and curved panels can be easily made using this technique. As more applications and more studies have been made on this technique for thermoplastic composites, many issues have come up. One issue of importance is the variation of the width and thickness of the tow as it is deposited. As the melted thermoplastic composite tow is being pressed under the compression force of the roller, the material flows. This changes the width and the thickness of the tow. The values of the width and thickness depend on many parameters such as the properties of the substrate, the temperature of the material, and the applied pressure. This variation in width and thickness of the individual tow being deposited has an influence on the development of laps and gaps between the deposited tows. This paper presents some of the results on an investigation on the above topic. Widths and thicknesses of carbon/PEEK tows processed using an Automated Fiber Placement machine with a hot gas torch were examined. Preliminary results show that there is significant variation in the width and thickness of the tows upon deposition.

Using an Improved Differential Evolution for Scheduling Optimization of Dual-Gantry Multi-Head Surface-Mount Placement Machine

The difference between dual-gantry and single-gantry surface-mount placement (SMP) machines is that dual-gantry machines exhibit higher complexity and more problems due to their additional gantry robot, such as component allocation and collision. This paper presents algorithms to prescribe the assembly operations of a dual-gantry multi-head surface-mount placement machine. It considers five inter-related problems: (i) component allocation; (ii) automatic nozzle changer assignment; (iii) feeder arrangement; and (iv) pick-and-place sequence; it incorporates a practical restriction related to (v) component height. The paper proposes a solution to each problem: (i) equalizing “workloads” assigned to the gantries, (ii) using quantity ratio method, (iii) using two similarity measurement mechanisms in a modified differential evolution algorithm with a random-key encoding mapping method that addresses component height restriction, (iv) and a combination of nearest-neighbor search and 2-opt method to plan each placing operation. This study reports an experiment that involved the processing of 10 printed circuit boards and compared the performance of a modified differential evolution algorithm with well-known algorithms including differential evolution, particle swarm optimization, and genetic algorithm. The results reveal that the number of picks, moving distance of picking components, and total assembly time with the modified differential evolution algorithm are less than other algorithms.

Kinematic modeling and parameter identification for a heavy gantry-type automated fiber placement machine considering gravity deformation

Automated fiber placement machine is the key equipment for low-cost and automated manufacturing of high-performance carbon composite materials. In order to meet the required position accuracy of fiber placement, this paper focuses on the kinematic modeling and parameter identification of the automated fiber placement machine. A kinematic model taking account of geometric deviations is established firstly. Since joint interfaces are the main origin of gravity deformation in a machine tool, an elastic beam deformation model is introduced to represent the joint interface, and then the former kinematic model is modified by analytical expressions of the gravity deformation for each joint interface. Based on the measurement data and the Levenberg-Marquardt optimization method, the parameter identification of the kinematic model is realized, and main issues such as measurement data selection, objective function definition are discussed. Finally, a kinematic calibration experiment is performed, and the experimental results verify the feasibility and validity of the modeling method. The position errors in Z direction of the automated fiber placement machine are effectively reduced by over 80%, which suggests that the proposed method reduces the effect of the gravity deformation and improves the accuracy of the automated fiber placement machine.