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Background: Molten pool temperature in Laser Additive Manufacturing (LAM) will affect powder efficiency, structural compositions of reactants and products in the molten pool, thus determining the microstructure evolutions and mechanical properties of the final part. An interest in molten pool temperature measurement has been around for a long time since the appearance of LAM. However, a comprehensive summary of the existing methods and their applications does not exist in the literature. Objective: The state-of-the-art of the existed devices and methods for molten pool temperature measurement in various of LAM processes is reviewed in this paper. Methods: The existing temperature measurement methods for molten pool monitoring in LAM processes are discussed. For each method, the existed patents, detailed procedures, advantages and disadvantages, specific applications are specified. In the end, comparisons among the current temperature measurement techniques are made according to data accuracy, operation complexity and cost of implementation. Results: Four methods are currently being used for the molten pool temperature measurement in LAM processes, including (i) Thermocouples, (ii) Infrared pyrometers, (iii) Infrared cameras, and (iv) Charge-coupled-device cameras. Conclusion: Different measurement methods represent different characteristics of the signal, and each has merits and defects. Selecting suitable measurement method according to different process characteristics will be helpful to achieve a preferable and more convincing results.

In the present study, the influence of laser energy density (LED) on geometrical characteristics, mechanical properties and microstructure of Inconel 718 parts fabricated by laser engineered net shaping (LENS) were investigated. Thin walls and block specimens were designed and fabricated under a total of 25 different energy density combinations. The material properties, including part dimensional shrinkage, surface roughness, surface hardness, and microstructures, including, porosity, geometrical dilution, average grain size and dendrite arm spacing (DAS), were evaluated. The results of this investigations indicate that with the increase of LED, the part shrinkage and surface roughness present a down and up trend, whereas the porosity, geometrical dilution, grain size and DAS increase with increasing of LED and there is no statistically significant effect of LED on the surface micro hardness. Taking account of the material characterization results, the energy density window for LENS process of Inconel 718 is suggested between 98.21 J/mm2 to 107.14 J/mm2. The outputs of this study could provide an insightful view of the effects of energy input on mechanical and microstructural properties of as-deposited Inconel 718 alloy by LENS process.

The molten pool temperature during laser engineered net shaping (LENS) could directly affect the microstructure and phase compositions of materials in the molten pool, thereby affecting the mechanical properties of the fabricated parts. To achieve a well-built solid structure, the research on fundamentals and methods of molten pool thermal behavior monitoring is of great significance. Using a high-resolution infrared camera, this paper realized real-time temperature tracking of Inconel 718 deposition in the LENS process. The effects of deposition variables, such as laser power and scanning speed, on the molten pool temperature and cooling rate have been investigated. In addition, the effects of the molten pool temperature on the molten pool depth and dendrite arm spacing (DAS) have been analyzed. The results suggest that the molten pool temperature increases with increasing of the laser power while it drops first and then rises with increasing of the scanning speed. The molten pool temperature increases nonlinearly with increasing of the number of layers during the material deposition process.

Cystic fibrosis (CF) is an autosomal recessive disease caused by mutations in the cystic fibrosis transmembrane regulator (CFTR) gene: the gene product responsible for transporting chloride and bicarbonate ions through the apical membrane of most epithelial cells. Major clinical features of CF include respiratory failure, pancreatic exocrine insufficiency, and intestinal disease. Many CF animal models have been generated, but some models fail to fully capture the phenotypic manifestations of human CF disease. Other models that better capture the key characteristics of the human CF phenotype are cost prohibitive or require special care to maintain. Important differences have been reported between the pathophysiology seen in human CF patients and in animal models. These limitations present significant limitations to translational research. This review outlines the study of CF using patient-derived organs-on-a-chip to overcome some of these limitations. Recently developed microfluidic-based organs-on-a-chip provide a human experimental model that allows researchers to manipulate environmental factors and mimic in vivo conditions. These chips may be scaled to support pharmaceutical studies and may also be used to study organ systems and human disease. The use of these chips in CF discovery science enables researchers to avoid the barriers inherent in animal models and promote the advancement of personalized medicine.

Improving the accuracy of material feeding for printed circuit board (PCB) template orders can reduce the overall cost for factories. In this paper, a data mining approach based on multivariate boxplot, multiple structural change model (MSCM), neighborhood component feature selection (NCFS), and artificial neural networks (ANN) was developed for the prediction of scrap rate and material feeding optimization. Scrap rate related variables were specified and 30,117 samples of the orders were exported from a PCB template production company. Multivariate boxplot was developed for outlier detection. MSCM was employed to explore the structural change of the samples that were finally partitioned into six groups. NCFS and ANN were utilized to select scrap rate related features and construct prediction models for each group of the samples, respectively. Performances of the proposed model were compared to manual feeding, ANN, and the results indicate that the approach exhibits obvious superiority to the other two methods by reducing surplus rate and supplemental feeding rate simultaneously and thereby reduces the comprehensive cost of raw material, production, logistics, inventory, disposal, and delivery tardiness compensation.

The amount of heat input, expressed as energy density, is one of the key parameters for laser additive manufacturing process. It will affect the melt pool dynamics, such as melt pool/powder interaction and temperature distribution, during the material solidification process, thus exerting an important influence on the forming accuracy and properties of the fabricated part. This paper investigates the effect of energy density on the forming accuracy and physical/mechanical properties of Inconel 718 part fabricated by LENS technique. Specifically, geometrical accuracy and relative density are measured with thin wall specimens. Surface roughness test is performed with block specimens. Based on the experimental results of the forming accuracy, relative density, and surface roughness, the suggested energy density ranges from 83.33 J/mm2 to 137.5 J/mm2.

In order to improve the accuracy and efficiency of damage assessment, a novel method to evaluate the damage state for remanufacturing blanks based on the magnetic and surface texture feature fusion was developed. Through modeling of the magnetic and surface texture features, sample entropy parameters from the magnetic intensity and its gradients were extracted, and energy, entropy, contrast, and correlation parameters from surface texture were obtained. The two-layered feature fusion model comprised of the data layer and the index layer was established. In the data layer, parameters of the magnetic and surface texture features and their nonlinear mapping relationships with damage were obtained. In the index layer, the information fusion between the magnetic and surface texture features was carried out by Dempster-Shafer (D-S) evidence theory. Finally, fatigue test samples were selected to verify the feasibility of the proposed method. Results show that the method can be used to determine the damage states of the remanufacturing blanks, which provides theoretical and technical decision support for remanufacturability of the components.

Due to high strength and ductility, AISI 4141 alloy steel is widely used in many industrial applications, such as gears and blades. When it is composed to harsh working environment, severe mechanical failures may happen. In order to save the high added value of the components, necessary repairing techniques are required to recover their functionality. Laser Engineered Net Shaping (LENS) is an innovative technology for metal parts repairing and rebuilding due to its metallurgical bonding and exhibit heat affected zone (HAZ). Compared to other repairing processes, LENS cannot only reduce the manufacturing time and cost, increase material utilization, but also provide an outstanding as-fabricated mechanical properties. Considering the compatibility and availability of powder materials, the selection of to-be-fabricated materials are important and decisive to the mechanical properties and the quality of the deposits. In this investigation, nickel-based and cobalt based superalloys are deposited onto AISI 4140 steel substrate using laser engineered net shaping (LENS) process to verify the feasibility of these superalloys for repairing of AISI 4140 workpieces. The micro-hardness, tensile strength, fracture and wear resistance are analyzed to testify the resistance of deformation, tension and anti-friction performance of deposited materials.

This paper explores the specific energy consumption (SEC) and environmental impacts for typical additive manufacturing processes. Also, the paper examines the possibility that ensure the product quality while reducing energy consumption with experimental analysis. The results show that (1) the SEC of additive manufacturing processes is related not only to material characteristics but also to the process input parameters, (2) it is possible to increase the energy efficiency without reducing product quality by adjusting the process rate or selecting different materials, and (3) the global warming potential (GWP) result of AM processes indicates that the GWP is brought about principally by the energy production process. The information provided by this project can also be of benefit to life cycle assessment and other environmental impact assessment related to AM processes.

Data mining (DM) with Big Data has been widely used in the lifecycle of electronic products that range from the design and production stages to the service stage. A comprehensive analysis of DM with Big Data and a review of its application in the stages of its lifecycle will not only benefit researchers to develop strong research themes and identify gaps in the field but also help practitioners for DM application system development. In this paper, a brief clarification of DM-related topics is presented first. A flowchart of DM and the main content of the flowchart steps are given in which commonly used data preparation and preprocessing approaches, DM functions and techniques, and performances indicators are summarized. Then, a comprehensive review covering 105 articles from 2007 to 2017 on DM or Big Data applications in the electronics industry is provided according to the flowchart from various points of view such as data handling, applications of DM, or Big Data at different lifecycle stages, and the software used in the applications. On this basis, a diagram of data content for different knowledge areas and a framework for DM and Big Data applications in the electronics industry are established. Finally, conclusions and future research directions are given.

As an important factor during direct energy deposition (DED) additive manufacturing process, powder stream distribution will not only affect the deposition rate, but also the powder-gas and power-powder interactions, and thus the consequent quality and property of the fabricated part. This paper created an analytical model to illustrate the powder stream distribution under the four-jet nozzles in the DED. To validate the proposed model, weight measurement method was used to track the powder stream distributions at different positions under the nozzle. Additionally, the effects of the input variables, including powder flow rate, gas flow rate and particle size, on the powder stream distribution were also analyzed. The results suggest a relatively good agreement between the modelling and experimental measurements. At the end, the powder deposition efficiency (PDE) was estimated based on the simulation results.

AISI 4140 powder was directly deposited on AISI 4140 wrought substrate using laser engineered net shaping (LENS) to investigate the compatibility of a LENS-deposited part with the substrate. Tensile testing at room temperature was performed to evaluate the interface bond performance and fracture behavior of the test specimens. All the samples failed within the as-deposited zone, indicating that the interfacial bond is stronger than the interlayer bond inside the deposit. The fracture surfaces were analyzed using scanning electron microscopy (SEM) and energy disperse X-ray spectrometry (EDS). Results show that the tensile fracture failure of the as-deposited part is primarily affected by lack-of-fusion defects, carbide precipitation, and oxide particles inclusions, which causes premature failure of the deposit by deteriorating the mechanical properties and structural integrity.

As a prospective candidate material for surface coating and repair applications, nickel-based superalloy Inconel 718 (IN718) was deposited on American Iron and Steel Institute (AISI) 4140 alloy steel substrate by laser engineered net shaping (LENS) to investigate the compatibility between two dissimilar materials with a focus on interface bonding and fracture behavior of the hybrid specimens. The results show that the interface between the two dissimilar materials exhibits good metallurgical bonding. Through the tensile test, all the fractures occurred in the as-deposited IN718 section rather than the interface or the substrate, implying that the as-deposited interlayer bond strength is weaker than the interfacial bond strength. From the fractography using scanning electron microscopy (SEM) and energy disperse X-ray spectrometry (EDS), three major factors affecting the tensile fracture failure of the as-deposited part are (i) metallurgical defects such as incompletely melted powder particles, lack-of-fusion porosity, and micropores; (ii) elemental segregation and Laves phase, and (iii) oxide formation. The fracture failure mechanism is a combination of all these factors which are detrimental to the mechanical properties and structural integrity by causing premature fracture failure of the as-deposited IN718.