Fused Deposition Modeling (FDM), the preferred additive manufacturing technology used for creating plastic-based parts, due to its affordability and simplicity of use. A well-known material used in FDM is Polylactic acid (PLA); however, its mechanical properties limit its use as a functional part for many applications. This research investigates the effect Copper-reinforcement has on PLA material's ultimate tensile strength (UTS) during production with a FDM process. The max tensile strength measured during this study was produced using a combination of low layer thickness (0.14 mm), high infill (90%), and high printing speed (100 mm/s). The wall thickness had a point of maximum tensile strength which was found at approximately 1.2 mm before strength began to decrease. Surface finish results were achieved with a combination of 0.14 mm layer thickness, 95 mm/s printing speed, 85% infill, and 1.0 mm wall thickness, and deviations from these settings led to increased roughness due to thermal and structural factors. Multi-objective evolutionary algorithm-based optimization MOEA/D method produced a combined "knee" point for tensile strength that was greater than all the highest experimental tensile strength measures while maintaining surface roughness identical to established through experimental means, demonstrating the effectiveness of multi-objective FDM parameter optimization utilizing it.

3D printers and robots (3DPR) are new technologies that may disrupt traditional supply chains.The location of the manufacturing place can be moved toward more customer side in the supply chain, which brings both agility and the ability of customization.The impact is yet to be examined quantitatively. In this paper we study the location of 3DPR in the supply chain. We present and compare three models of supply chains: Traditional supply chain; 3DPR at warehouse; 3DPR at shop. The semodels are compared by the equipment installation cost, the production cost,and inventory cost for safety-stock. The study presents a practical case study motivated from a real-world apparel company, discusses the three models under various parameter settings, comparing the obtained total cost and discovers the advantages and disadvantages.

A multitude of techniques fall under the domain of Multi- Criteria Decision Making (MCDM) which is used to select the best alternative among the available ones. The objective of this paper is to compare some of these techniques with respect to the problem of selection of 3D printers, which is associated with multiple attributes. The weights of the criteria were determined using analytical network process (ANP). Next, the alternatives were ranked using three different MCDM techniques- 1.TOPSIS which ranks alternatives having the shortest distance to the ideal solution as well as the greatest distance from the negative-ideal solution 2. Deng’s Similarity based Approach where the most preferred alternative should have the highest degree of similarity to the positive ideal solution and the lowest degree of similarity to the negative-ideal solution and 3.PROMETHEE and GAIA. The solutions for each of these three cases were analyzed thoroughly, and reasons for any deviations were discussed.