An Overview of 3-D Printing in Manufacturing, Aerospace, and Automotive Industries

Lim, Choon Wee Joel; Le, Kim Quy; Lu, Qingyang; Wong, Chee How

doi:10.1109/mpot.2016.2540098

Cited by 116 publications

(62 citation statements)

References 9 publications

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“…In particular, the fused deposition modeling (FDM) method has been popular in applications because it is inexpensive for thermoplastic materials and low maintenance [ 1 , 2 , 3 , 4 ]. Moreover, it has been used in prototypes and the production of custom parts in many industries including the medical, food, textile, automotive, aerospace, and construction industries [ 5 , 6 , 7 , 8 , 9 , 10 ]. In FDM 3D printing, melted thermoplastic is extruded in the X, Y, and Z directions, and laminated layer by layer on a platform.…”

Section: Introductionmentioning

confidence: 99%

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Prasong

Ishigami

Thumsorn³

et al. 2021

Polymers

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Poly(lactic acid) (PLA) filaments have been the most used in fused deposition modeling (FDM) 3D printing. The filaments, based on PLA, are continuing to be developed to overcome brittleness, low heat resistance, and obtain superior mechanical performance in 3D printing. From our previous study, the binary blend composites from PLA and poly(butylene adipate-co-terephthalate) (PBAT) with nano talc (PLA/PBAT/nano talc) at 70/30/10 showed an improvement in toughness and printability in FDM 3D printing. Nevertheless, interlayer adhesion, anisotropic characteristics, and heat resistance have been promoted for further application in FDM 3D printing. In this study, binary and ternary blend composites from PLA/PBAT and poly(butylene succinate) (PBS) with nano talc were prepared at a ratio of PLA 70 wt. % and blending with PBAT or PBS at 30 wt. % and nano talc at 10 wt. %. The materials were compounded via a twin-screw extruder and applied to the filament using a capillary rheometer. PLA/PBAT/PBS/nano talc blend composites were printed using FDM 3D printing. Thermal analysis, viscosity, interlayer adhesion, mechanical properties, and dimensional accuracy of binary and ternary blend composite 3D prints were investigated. The incorporation of of PBS-enhanced crystallinity of the blend composite 3D prints resulted in an improvement to mechanical properties, heat resistance, and anisotropic characteristics. Flexibility of the blend composites was obtained by presentation of PBAT. It should be noted that the core–shell morphology of the ternary blend influenced the reduction of volume shrinkage, which obtained good surface roughness and dimensional accuracy in the ternary blend composite 3D printing.

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Section: Introductionmentioning

confidence: 99%

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Prasong

Ishigami

Thumsorn³

et al. 2021

Polymers

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“…Additive manufacturing, or three-dimensional (3D) printing, is the process of depositing materials layer by layer to create solid objects from digital models [ 1 , 2 , 3 , 4 , 5 ]. Its application is gradually expanding into various sectors, including automotive, aerospace, and biomedicine [ 6 , 7 , 8 , 9 ]. This promising technology enables the production of geometrically complex parts with less time and effort compared to traditional manufacturing processes.…”

Section: Introductionmentioning

confidence: 99%

Resistance Temperature Detectors Fabricated via Dual Fused Deposition Modeling of Polylactic Acid and Polylactic Acid/Carbon Black Composites

Jeon

Hong

Park

et al. 2021

Sensors

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Planar-type resistance temperature detectors (P-RTDs) were fabricated via fused deposition modeling by dual nozzle extrusion. The temperature-sensing element of the fabricated sensor was printed with electrically conductive polylactic acid/carbon black (PLA/CB) composite, while the structural support was printed with a PLA insulator. The temperature-dependent resistivity change of PLA/CB was evaluated for different stacking sequences of PLA/CB layers printed with [0°/0°], [−45°/45°], and [0°/90°] plies. Compared to a PLA/CB filament used as 3D printing source material, the laminated structures exhibited a response over 3 times higher, showing a resistivity change from −10 to 40 Ω∙cm between −15 and 50 °C. Then, using the [0°/90°] plies stacking sequence, a P-RTD thermometer was fabricated in conjunction with a Wheatstone bridge circuit for temperature readouts. The P-RTD yielded a temperature coefficient of resistance of 6.62 %/°C with high stability over repeated cycles. Fabrication scalability was demonstrated by realizing a 3 × 3 array of P-RTDs, allowing the temperature profile detection of the surface in contact with heat sources.

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“…As a promising advanced manufacturing process, FDM can efficiently fabricate personalized products with a high degree of geometric complexity [ 11 , 12 , 13 ]. and has been employed in many significant applications [ 14 , 15 ]. However, most of these applications are not yet widely deployed in practice due to the quality variation of products, such as geometric deviations [ 16 , 17 ].…”

Section: Introductionmentioning

confidence: 99%

MOSS—Multi-Modal Best Subset Modeling in Smart Manufacturing

Wang

Jin

2021

Sensors

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Smart manufacturing, which integrates a multi-sensing system with physical manufacturing processes, has been widely adopted in the industry to support online and real-time decision making to improve manufacturing quality. A multi-sensing system for each specific manufacturing process can efficiently collect the in situ process variables from different sensor modalities to reflect the process variations in real-time. However, in practice, we usually do not have enough budget to equip too many sensors in each manufacturing process due to the cost consideration. Moreover, it is also important to better interpret the relationship between the sensing modalities and the quality variables based on the model. Therefore, it is necessary to model the quality-process relationship by selecting the most relevant sensor modalities with the specific quality measurement from the multi-modal sensing system in smart manufacturing. In this research, we adopted the concept of best subset variable selection and proposed a new model called Multi-mOdal beSt Subset modeling (MOSS). The proposed MOSS can effectively select the important sensor modalities and improve the modeling accuracy in quality-process modeling via functional norms that characterize the overall effects of individual modalities. The significance of sensor modalities can be used to determine the sensor placement strategy in smart manufacturing. Moreover, the selected modalities can better interpret the quality-process model by identifying the most correlated root cause of quality variations. The merits of the proposed model are illustrated by both simulations and a real case study in an additive manufacturing (i.e., fused deposition modeling) process.

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An Overview of 3-D Printing in Manufacturing, Aerospace, and Automotive Industries

Cited by 116 publications

References 9 publications

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Improvement of Interlayer Adhesion and Heat Resistance of Biodegradable Ternary Blend Composite 3D Printing

Resistance Temperature Detectors Fabricated via Dual Fused Deposition Modeling of Polylactic Acid and Polylactic Acid/Carbon Black Composites

MOSS—Multi-Modal Best Subset Modeling in Smart Manufacturing

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