Selvam Arivazhagan, Mayilswamy Suresh, Whenish Ruban, Naresh K, Shanmugam Vigneshwaran, Das Oisik
Department of Mechanical Engineering, KPR Institute of Engineering and Technology, Coimbatore, Tamil Nadu, India.
Department of Robotics and Automation Engineering, PSG College of Technology, Coimbatore, Tamil Nadu, India.
Sci Rep. 2022 Oct 7;12(1):16887. doi: 10.1038/s41598-022-20782-8.
In this study, fused filament fabrication (FFF) printing parameters were optimized to improve the surface quality and reduce the printing time of Acrylonitrile Butadiene Styrene (ABS) polymer using the Analysis of Variance (ANOVA), it is a statistical analysis tool. A multi-objective optimization technique was employed to predict the optimum process parameter values using particle swarm optimization (PSO) and response surface methodology (RSM) techniques. Printing time and surface roughness were analyzed as a function of layer thickness, printing speed and nozzle temperature. A central composite design was preferred by employing the RSM method, and experiments were carried out as per the design of experiments (DoE). To understand the relationship between the identified input parameters and the output responses, several mathematical models were developed. After validating the accuracy of the developed regression model, these models were then coupled with PSO and RSM to predict the optimum parameter values. Moreover, the weighted aggregated sum product assessment (WASPAS) ranking method was employed to compare the RSM and PSO to identify the best optimization technique. WASPAS ranking method shows PSO has finer optimal values [printing speed of 125.6 mm/sec, nozzle temperature of 221 °C and layer thickness of 0.29 mm] than the RSM method. The optimum values were compared with the experimental results. Predicted parameter values through the PSO method showed high surface quality for the type of the surfaces, i.e., the surface roughness value of flat upper and down surfaces is approximately 3.92 µm, and this value for the other surfaces is lower, which is approximately 1.78 µm, at a minimum printing time of 24 min.
在本研究中，采用方差分析（ANOVA，一种统计分析工具）对熔融沉积成型（FFF）打印参数进行了优化，以提高丙烯腈-丁二烯-苯乙烯（ABS）聚合物的表面质量并缩短打印时间。采用多目标优化技术，利用粒子群优化（PSO）和响应面方法（RSM）技术预测最佳工艺参数值。将打印时间和表面粗糙度作为层厚、打印速度和喷嘴温度的函数进行分析。采用RSM方法选用中心复合设计，并根据实验设计（DoE）进行实验。为了理解所确定的输入参数与输出响应之间的关系，建立了几个数学模型。在验证了所建立的回归模型的准确性之后，将这些模型与PSO和RSM相结合，以预测最佳参数值。此外，采用加权聚合和乘积评估（WASPAS）排序方法比较RSM和PSO，以确定最佳优化技术。WASPAS排序方法表明，PSO具有比RSM方法更优的最佳值[打印速度为125.6毫米/秒，喷嘴温度为221℃，层厚为0.29毫米]。将最佳值与实验结果进行了比较。通过PSO方法预测的参数值表明，对于该类型的表面具有较高的表面质量，即平坦上表面和下表面的表面粗糙度值约为3.92μm，其他表面的该值较低，约为1.78μm，最短打印时间为24分钟。
