Abstract

Fused filament fabrication (FFF) has been proven to be an effective additive manufacturing technique for carbon fiber reinforced polyether–ether–ketone (CFR-PEEK) due to its practicality in use. However, the relationships between the process parameters and their trade-offs in manufacturing performance have not been extensively studied for CFR-PEEK although they are essential to identify the optimal parameter settings. This study therefore investigates the impact of critical FFF parameters (i.e., layer thickness, build orientation, and printing speed) on the manufacturing performance (i.e., printing time, dimensional accuracy, and material cost) of CFR-PEEK outputs. A full factorial design of the experiments is performed for each of the three sample designs to identify the optimal parameter combinations for each performance measure. In addition, multiple response optimization was used to derive optimal parameter settings for the overall performance. The results show that the optimal parameter settings depend on the performance measures regardless of the designs, and that the layer thickness plays a critical role in the performance trade-offs. In addition, lower layer thickness, horizontal orientation, and higher speed form the optimal settings to maximize the overall performance. The findings from this study indicate that FFF parameter settings for CFR-PEEK should be identified through multi-objective decision making that involves conflicts between the operational objectives for the parameter settings.

Highlights

  • Additive manufacturing has received increasing attention as industries have pursued new profit paths through the small volume production of more innovative, customized, and sustainable products with high competitiveness [1]

  • Motivated by the above issues, this study aims to identify the dynamics of key Fused filament fabrication (FFF) process parameters for CFR-PEEK on manufacturing performance measures that are closely related to manufacturing time, quality, and cost

  • The following sub-sections show statistical results to identify the impact of the FFF process parameter combinations for the CFR-PEEK on the manufacturing performance measures, and the individual and overall optimal parameter settings for each design type are analyzed to derive their manufacturing implications

Read more

Summary

Introduction

Additive manufacturing has received increasing attention as industries have pursued new profit paths through the small volume production of more innovative, customized, and sustainable products with high competitiveness [1]. Additive manufacturing, defined as the process of building up materials layer by layer to make objects from 3D model data [2], initially emerged for rapid prototyping to create prototypes in a short time [3]. Additive manufacturing as a means of rapid prototyping has been extended to rapid manufacturing to take advantage of various materials and the design freedom provided by additive manufacturing [1,4,5]. Additive manufacturing is employed for various application areas including patient-specific medical implants [6], lightweight parts in high-end engineering [7], artistic devices [8,9], and so on.

Objectives
Methods
Results
Conclusion
Full Text
Published version (Free)

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call