scholarly journals A High-Throughput Method to Define Additive Manufacturing Process Parameters: Application to Haynes 282

2021 ◽  
Author(s):  
Zahabul Islam ◽  
Ankur Kumar Agrawal ◽  
Behzad Rankouhi ◽  
Collin Magnin ◽  
Mark H. Anderson ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
High Throughput ◽  
Process Parameters ◽  
Manufacturing Process ◽  
High Throughput Method

Learning Algorithm Based Modeling and Process Parameters Recommendation System for Binder Jetting Additive Manufacturing Process

2015 ◽  
Author(s):  
Han Chen ◽  
Yaoyao F. Zhao
Keyword(s):  
Additive Manufacturing ◽  
Product Quality ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Process Model ◽  
Recommendation System ◽  
Powder Materials ◽  
Quality Properties ◽  
Binder Jetting ◽  
Printing Time

Binder Jetting (BJ) process is an additive manufacturing process in which powder materials are selectively joined by binder materials. Products can be manufactured layer by layer directly from 3D model data. It is not always easy for manufacturing engineers to choose proper BJ process parameters to meet the end-product quality and fabrication time requirements. This is because the quality properties of the products fabricated by BJ process are significantly affected by the process parameters. And the relationships between process parameters and quality properties are very complicated. In this paper, a process model is developed by Backward Propagation (BP) Neural Network (NN) algorithm based on 16 groups of orthogonal experiment designed by Taguchi Method to express the relationships between 4 key process parameters and 2 key quality properties. Based on the modeling results, an intelligent parameters recommendation system is developed to predict end-product quality properties and printing time, and to recommend process parameters selection based on the process requirements. It can be used as a guideline for selecting the proper printing parameters in BJ to achieve the desired properties and help to reduce the printing time.

Effect of Additive Manufacturing Process Parameters on Turbine Cooling

2019 ◽  
Author(s):  
Jacob C. Snyder ◽  
Karen A. Thole
Keyword(s):  
Heat Transfer ◽  
Additive Manufacturing ◽  
Surface Morphology ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Pressure Loss ◽  
Cooling Performance ◽  
Micro Scale ◽  
Turbine Cooling ◽  
External Cooling

Abstract Turbine cooling is a prime application for additive manufacturing because it enables quick development and implementation of innovative designs optimized for efficient heat removal, especially at the micro-scale. At the micro-scale, however, the surface finish plays a significant role in the heat transfer and pressure loss of any cooling design. Previous research on additively manufactured cooling channels has shown the surface roughness increases both heat transfer and pressure loss to similar levels as highly-engineered turbine cooling schemes. What has not been shown, however, is whether opportunities exist to tailor additively manufactured surfaces through control of the process parameters to further enhance the desired heat transfer and pressure loss characteristics. The results presented in this paper uniquely show the potential of manipulating the parameters within the additive manufacturing process to control the surface morphology, directly influencing turbine cooling. To determine the effect of parameters on cooling performance, coupons were additively manufactured for common internal and external cooling methods using different laser powers, scan speeds, and scanning strategies. Internal and external cooling tests were performed at engine relevant conditions to measure appropriate metrics of performance. Results showed the process parameters have a significant impact on the surface morphology leading to differences in cooling performance. Specifically, internal and external cooling geometries react differently to changes in parameters, highlighting the opportunity to consider process parameters when implementing additive manufacturing for turbine cooling applications.

High Throughput Method to Fabricate Ordered Nano Dot Array on Various Plastic Films

2012 ◽  
Vol 523-524 ◽  
pp. 633-638 ◽  
Author(s):  
Phuc Duc Truong ◽  
Akinori Yamanaka ◽  
Masahiko Yoshino
Keyword(s):  
High Throughput ◽  
Process Parameters ◽  
Annealing Temperature ◽  
Indentation Load ◽  
Plastic Film ◽  
Pdms Film ◽  
Plastic Films ◽  
Patterned Substrate ◽  
High Throughput Method ◽  
Plastic Forming

In this paper, we propose a high throughput method to fabricate ordered metal nano dot array on a plastic film by combination of patterning by nano plastic forming, coating, annealing, and transferring to a plastic film. The effects of process parameters such as indentation load, annealing temperature on the formation of gold nano dot array and dot transfer ratio to a PDMS film are investigated. The results show that an ordered gold nano dot array is successfully formed on the pre-patterned substrate. The transfer of an ordered gold nano dot array to PDMS film is demonstrated.

Role of process parameters during additive manufacturing by direct metal deposition of Inconel 718

2017 ◽  
Vol 23 (5) ◽  
pp. 919-929 ◽  
Author(s):  
Bo Chen ◽  
Jyoti Mazumder
Keyword(s):  
Additive Manufacturing ◽  
Cooling Rate ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Inconel 718 ◽  
Processing Parameters ◽  
Forming Quality ◽  
Content Type ◽  
Forming Characteristics ◽  
The Relationship

Purpose The aim of this research is to study the influence of laser additive manufacturing process parameters on the deposit formation characteristics of Inconel 718 superalloy, the main parameters that influence the forming characteristics, the cooling rate and the microstructure were studied. Design/methodology/approach Orthogonal experiment design method was used to obtain different deposit shape and microstructure using different process parameters by multiple layers deposition. The relationship between the processing parameters and the geometry of the cladding was analyzed, and the dominant parameters that influenced the cladding width and height were identified. The cooling rates of different forming conditions were obtained by the secondary dendrite arm spacing (SDAS). Findings The microstructure showed different characteristics at different parts of the deposit. Cooling rate of different samples were obtained and compared by using the SDAS, and the influence of the process parameters to the cooling rate was analyzed. Finally, micro-hardness tests were done, and the results were found to be in accordance with the micro-structure distribution. Originality/value Relationships between processing parameters and the forming characteristics and the cooling rates were obtained. The results obtained in this paper will help to understand the relationship between the process parameters and the forming quality of the additive manufacturing process, so as to obtain the desired forming quality by appropriate parameters.

scholarly journals Performance of wearables and the effect of user behavior in additive manufacturing process

2021 ◽  
Vol 8 (1) ◽  
Author(s):  
JuYoun Kwon ◽  
Namhun Kim
Keyword(s):  
Mechanical Properties ◽  
Additive Manufacturing ◽  
Process Parameters ◽  
Manufacturing Process ◽  
High Performance ◽  
Essential Role ◽  
User Behavior ◽  
Process Parameter ◽  
Am Processes

AbstractAdditive manufacturing (AM) which can be a suitable technology to personalize wearables is ideal for adjusting the range of part performance such as mechanical properties if high performance is not required. However, the AM process parameter can impact overall durability and reliability of the part. In this instance, user behavior can play an essential role in performance of wearables through the settings of AM process parameter. This review discusses parameters of AM processes influenced by user behavior with respect to performance required to fabricate AM wearables. Many studies on AM are performed regardless of the process parameters or are limited to certain parameters. Therefore, it is necessary to examine how the main parameters considered in the AM process affect performance of wearables. The overall aims of this review are to achieve a greater understanding of each AM process parameter affecting performance of AM wearables and to provide requisites for the desired performance including the practice of sustainable user behavior in AM fabrication. It is discussed that AM wearables with various performance are fabricated when the user sets the parameters. In particular, we emphasize that it is necessary to develop a qualified procedure and to build a database of each AM machine about part performance to minimize the effect of user behavior.

scholarly journals Effect of Additive Manufacturing Process Parameters on Turbine Cooling

2020 ◽  
Vol 142 (5) ◽  
Author(s):  
Jacob C. Snyder ◽  
Karen A. Thole
Keyword(s):  
Heat Transfer ◽  
Additive Manufacturing ◽  
Surface Morphology ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Pressure Loss ◽  
Cooling Performance ◽  
Micro Scale ◽  
Turbine Cooling ◽  
External Cooling

Abstract Turbine cooling is a prime application for additive manufacturing because it enables quick development and implementation of innovative designs optimized for efficient heat removal, especially at the micro-scale. At the micro-scale, however, the surface finish plays a significant role in the heat transfer and pressure loss of any cooling design. Previous research on additively manufactured cooling channels has shown surface roughness increases both heat transfer and pressure loss to similar levels as highly engineered turbine cooling schemes. What has not been shown, however, is whether opportunities exist to tailor additively manufactured surfaces through control of the process parameters to further enhance the desired heat transfer and pressure loss characteristics. The results presented in this paper uniquely show the potential of manipulating the parameters within the additive manufacturing process to control the surface morphology, directly influencing turbine cooling. To determine the effect of parameters on cooling performance, coupons were additively manufactured for common internal and external cooling methods using different laser powers, scan speeds, and scanning strategies. Internal and external cooling tests were performed at engine relevant conditions to measure appropriate metrics of performance. Results showed the process parameters have a significant impact on the surface morphology leading to differences in cooling performance. Specifically, internal and external cooling geometries react differently to changes in parameters, highlighting the opportunity to consider process parameters when implementing additive manufacturing for turbine cooling applications.

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