**1. Introduction**

Always, time and accuracy are the most important factors for engineering appliances [1–4]. Recently, novel manufacturing methods are enabled to solve many long-term processes, such as molding and casting [5]. Additive manufacturing (AM) has been introduced for tackling this problem with many applications for creating samples with high accuracy [6]. One of the most significant approaches of AM methods is fused deposition modeling (FDM), which can create samples by 3D printing technology (Figure 1) [7]. In this technology, a layer is generated by melting the polymer with the printer head at a specific temperature [8–10]. In nature, many materials are renewable, and polylactic acid (PLA) is one of them, which is normally produced from corn starch. Also, PLA is a thermoplastic aliphatic polyester and is obtained from the sources of energy that aren't evacuated by consuming [11–13]. By combining PLA with flexible metal, such as bronze, the mechanical properties of the composite may be improved [14]. The FDM method has also been served by many researchers [15–17].

**Figure 1.** Schematic of 3D printing by the fused deposition modeling [18].

For instance, the influence of layer thickness on ABSP 400 samples was investigated by Padhi et al. [19]. Improving the quality of the parts made by two different methods was carried out by Gardan et al. [20]. The agents of the layer thickness, filling speed, extrusion speed, and line width on the built time and dimensions were investigated by Peng et al. [21]. Three responses were converted by a fuzzy inference system to a single output. The response surface methodology (RSM) was used to determine the relationship between four input parameters and comprehensive output. MATLAB software was also used to implement fitness function in the genetic algorithm. The results indicated that the proposed approach could effectively improve accuracy and efficiency in the FDM process. Sajan et al. carried out a study to improve the surface quality made with acrylonitrile butadiene styrene (ABS) filaments [22]. In this experiment, five parameters of the 3D printer were considered as input parameters, such as the printing speed, layer thickness, and infill percentage. Also, for the optimization of this experiment, they used the Taguchi method to reach the high quality of the surface. Results showed that the quality of the surface was improved in the XY and XZ planes. Gautam et al. [23] studied the compressive effect of ABS Kagome truss unit cell manufactured by the FDM. The properties of carbon-fiber-reinforced plastic (CFRP) manufactured composite parts were studied by Ning et al. [24]. They used the FDM method for fabricating CFRP composites, and the carbon fiber was added to composites filaments. In most traditional manufacturing methods, such as plastic molding [25–27], the tensile strength is acceptable due to the cohesion of materials. However, as one of the major disadvantages of additive manufacturing, they may result in weaker mechanical properties (electrical and thermal conductivity, optical transparency, and strength of printed parts). This paper attempted to improve the mechanical properties of FDM components by modifying the input parameters as well as using the design of experiment (DOE) method.

In the current research, the composite samples were produced by FDM 3D printing bronze polylactic acid (Br-PLA). Br-PLA tensile test sample was used to investigate the effects of the layer thickness, infill percentage, extruder temperature, and their interactions on mechanical properties, maximum failure load, thickness, build time of parts based on the DOE method. The main objective of this study was to fine-tune controlled variables to produce tough Br-PLA specimens, reduce part thickness, and shorten the build time of the printed parts. The build time data were recorded after printing the specimens by a digital timer. The tensile strength test determined the maximum failure load and elongation at break. Design-Expert V8 software was utilized for the statistical analysis of experimental data via the response surface method (RSM). The research objective was achieved by RSM and validated by experimental tests. Validation of the statistical model was confirmed by comparing the similar results with experimental data. Finally, the comparison of maximum failure from PLA with Br-PLA was investigated.

## **2. Experimental Design and Methodology**
