The performance characterization of the manufacturing processes for additive manufacturing (AM) systems is a significant task for their standardization and implementation in the industry. Also, there is a large diversity of materials used in different AM processes. In the present paper, a methodology is proposed to evaluate, in different directions, the performance of an AM process and material characterization in terms of surface quality. This methodology consists of eight steps, based on a new surface inspection artifact and basic artifact orientations. The proposed artifact with several design configurations fits different AM systems sizes and meets the needs of customers. The effects of main factors on the surface roughness of up-facing platens of the artifacts are investigated using the statistical design of experiments. The proposed methodology is validated by a case study focused on PolyJet material jetting technology. Samples are manufactured of photopolymer resins and post-processed. Three factors (i.e., artifact orientation, platen orientation, and finish type) are considered for the investigation. The case study results show that the platen orientation, finish type, and their interaction have a significant influence on the surface roughness (Ra). The best Ra roughness results were obtained for the glossy finish type in the range of 0.5–4 μm.

MATEC Web of Conferences, open access proceedings in Materials science, Engineering and Chemistry

Polymer-based additive manufacturing (AM) gathers a great deal of interest with regard to standardization and implementation in mass production. A new methodology for the system and process capabilities analysis in additive manufacturing, using statistical quality tools for production management, is proposed. A large sample of small specimens of circular shape was manufactured of photopolymer resins using polymer jetting (PolyJet) technology. Two critical geometrical features of the specimen were investigated. The variability of the measurement system was determined by Gage repeatability and reproducibility (Gage R&R) methodology. Machine and process capabilities were performed in relation to the defined tolerance limits and the results were analyzed based on the requirements from the statistical process control. The results showed that the EDEN 350 system capability and PolyJet process capability enables obtaining capability indices over 1.67 within the capable tolerance interval of 0.22 mm. Furthermore, PolyJet technology depositing thin layers of resins droplets of 0.016 mm allows for manufacturing in a short time of a high volume of parts for mass production with a tolerance matching the ISO 286 IT9 grade for radial dimension and IT10 grade for linear dimensions on the Z-axis, respectively. Using microscopy analysis some results were explained and validated from the capability study.

Fibre-reinforced polymers (FRP) have attracted much interest within many industrial fields where the use of 3D printed molds can provide significant cost and time savings in the production of composite tooling. Within this paper, a novel method for the manufacture of complex-shaped FRP parts has been proposed. This paper features a new design of bike saddle, which was manufactured through the use of molds created by fused deposition modeling (FDM), of which two 3D printable materials were selected, polylactic acid (PLA) and acrylonitrile butadiene styrene (ABS), and these molds were then chemically and thermally treated. The novel bike saddles were fabricated using carbon fiber-reinforced polymer (CFRP), by vacuum bag technology and oven curing, utilizing additive manufactured (AM) molds. Following manufacture the molded parts were subjected to a quality inspection, using non-contact three-dimensional (3D) scanning techniques, where the results were then statistically analyzed. The statistically analyzed results state that the main deviations between the CAD model and the manufactured CFRP parts were within the range of ±1 mm. Additionally, the weight of the upper part of the saddles was found to be 42 grams. The novel method is primarily intended to be used for customized products using CFRPs.

The tribological performance of Glass Fiber Reinforced Polymer (GFRP) composites is essential for applications in automotive, aerospace, and industrial sectors. This study investigates the effect of fiber weight fraction ratio (wf.) (50%, 65%, and 70%), applied load, and sliding speed on the tribological behavior of twill-woven GFRP using a pin-on-disc tribometer. Experimental trials were carried out to assess the impact of control factors on the coefficient of friction, specific wear rate, and contact temperature. Statistical analyses based on generalized linear models (GLM) method or multi-factor ANOVA, identified the most significant factors and their contributions. Results indicate that sliding speed contributes the highest to COF (46.51%), while fiber wf. primarily influences wear rate (34.15%). The applied load was found to have the strongest impact on contact temperature (39.08%). Furthermore, SEM and EDS analyses reveal dominant wear mechanisms, including abrasive wear and transfer layer formation. This study introduces the novelty of using statistical modeling to optimize GFRP for high-performance tribological applications, providing a more precise and efficient approach to enhancing their properties.

The communication in quarantined areas, e.g., due to the new COVID-19 pandemic, between isolated areas and in areas with technical damage has resulted in a great deal of interest concerning the safety of the population. A new method for ensuring communication between different areas, using unmanned aerial vehicle (UAV) networks with a well-established mobility schedule is proposed. UAVs fly based on a mission plan using regular polygons covering an area from a map. The area is considered to be equidistantly covered with points, grouped in triangles which are further grouped into hexagons. In this paper, UAVs, including battery charging or battery swapping stations and light weight Wi-Fi boards, are used for the data transfer among drones and stations using delivery protocols. UAV network analysis and evaluation (lengths of the arcs in seconds) based on experimental preliminary flight tests are proposed. Multiple simulations are performed based on six DTN algorithms, single-copy, and multiple-copies algorithms, and the efficiency of data transmission (delivery rate and latency) is analyzed. A very good delivery rate of 0.973 is obtained using the newly introduced TD-UAV Dijkstra algorithm.