Quantifying a Fused Deposition Modeling System’s Dimensional Performance Through Its Addressability

As additive manufacturing becomes widely adopted for prototyping and part manufacturing, the need for controlling quality becomes crucial for this technology to continue its development in the manufacturing industry. Many studies over the last decade have been conducted to find suitable means to gauge and improve accuracy and performance for additive manufacturing systems. Prior research has experimented with benchmark tests, printer calibration, standardized test targets, and performance optimization based on critical printer parameters to find solutions to this problem. The goal of this study was to investigate the effect of printer parameters on dimensional accuracy through the most fundamental element of the printer, its addressability. The experiment utilized a simple test target comprised of raised lines that was the smallest line addressable for this analysis. Defined by the design of experiment, the factors investigated were: cooling fan speed (1500 RPM and 5100 RPM levels, nozzle temperature (175º C and 200º C levels), and platen temperature (45º C and 70º C levels). Test targets comprising of eight combinations of these factors and levels were printed and replicated. The sixteen test targets were three-dimensional imaged with an optical microscope for data collection. Five cross-sectional profiles were sampled from each test target in order to record line heights and widths of the printed parts for analysis. After careful data extraction and coding, 720 meaningful data points were used within an Analysis of Variance test for the response variables. The results showed platen temperature and cooling fan speed had an influence on the ΔH response variable. Both factors had low p-values of 0.010 and 0.058 respectively which means the null hypothesis can be rejected. As for the response variable ΔWa, the nozzle temperature, and cooling fan speed had an influence. Both factors had low p-values of 0.000 and 0.023 respectively which means the null hypothesis can be rejected. This research found these parameters to be significant when operating a fused deposition modeling system and will impact the part being produced. Therefore, this work expands upon previous parametric studies and demonstrates to the additive manufacturing industry the importance of characterizing the operating temperatures and cooling fan speeds of their systems. This study shows certain fan speeds and temperatures affect dimensional accuracy and certain values will produce fewer deviations in the part’s dimensions. The researcher believes this work will help others in the additive manufacturing industry optimize their fused deposition systems and future research can be conducted to further expand this line of experimentation

Geometric Element Test Targets for Visual Inference of a Printer\u27s Dimension Limitations

As technologies advance in the field of additive manufacturing (AM), it increases the demand in using test targets to quantitatively appraise the performance of AM processes and parts. This study presents a unique concept to address the dimensional and geometric viability of three-dimensional (3D) printers with test targets that are unique and complementary to those currently available. We have named these distinct designed artifacts as Geometric Element Test Targets (GETTs(TM)). The concept for the targets is to rely on positioning and spatial frequency of geometric shapes to induce failures that are indicative of the system’s dimensional limitations. A distinguishing characteristic is that the dimensional failures can be inspected visually. Systematic evaluations of the limitations can be further conducted through contact or non-contact measurements. The initial GETTs(TM) include three suites of test targets: line, angular and circular suites. We will illustrate this concept with samples produced with fused deposition modeling printers. The potential applications of GETTs(TM) include standardization, reference targets, in-line system control, and more