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Article
Publication date: 9 August 2024

Muhammad Arif Mahmood, Marwan Khraisheh, Andrei C. Popescu and Frank Liou

This study aims to develop a holistic method that integrates finite element modeling, machine learning, and experimental validation to propose processing windows for optimizing…

82

Abstract

Purpose

This study aims to develop a holistic method that integrates finite element modeling, machine learning, and experimental validation to propose processing windows for optimizing the laser powder bed fusion (LPBF) process specific to the Al-357 alloy.

Design/methodology/approach

Validation of a 3D heat transfer simulation model was conducted to forecast melt pool dimensions, involving variations in laser power, laser scanning speed, powder bed thickness (PBT) and powder bed pre-heating (PHB). Using the validated model, a data set was compiled to establish a back-propagation-based machine learning capable of predicting melt pool dimensional ratios indicative of printing defects.

Findings

The study revealed that, apart from process parameters, PBT and PHB significantly influenced defect formation. Elevated PHBs were identified as contributors to increased lack of fusion and keyhole defects. Optimal combinations were pinpointed, such as 30.0 µm PBT with 90.0 and 120.0 °C PHBs and 50.0 µm PBT with 120.0 °C PHB.

Originality/value

The integrated process mapping approach showcased the potential to expedite the qualification of LPBF parameters for Al-357 alloy by minimizing the need for iterative physical testing.

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Article
Publication date: 9 June 2023

Asif Ur Rehman, Burak Karakas, Muhammad Arif Mahmood, Berkan Başaran, Rashid Ur Rehman, Mertcan Kirac, Marwan Khraisheh, Metin Uymaz Salamci and Rahmi Ünal

For metal additive manufacturing, metallic powders are usually produced by vacuum induction gas atomization (VIGA) through the breakup of liquid metal into tiny droplets by gas…

228

Abstract

Purpose

For metal additive manufacturing, metallic powders are usually produced by vacuum induction gas atomization (VIGA) through the breakup of liquid metal into tiny droplets by gas jets. VIGA is considered a cost-effective technique to prepare feedstock. In VIGA, the quality and the morphology of the produced particles are mainly controlled by the gas pressure used during powder production, keeping the setup configuration constant.

Design/methodology/approach

In VIGA process for metallic additive manufacturing feedstock preparation, the quality and morphology of the powder particles are mainly controlled by the gas pressure used during powder production.

Findings

In this study, Inconel-625 feedstock was produced using a supersonic nozzle in a close-coupled gas atomization apparatus. Powder size distribution (PSD) was studied by varying the gas pressure.

Originality/value

The nonmonotonic but deterministic relationships were observed between gas pressure and PSD. It was found that the maximum 15–45 µm percentage PSD, equivalent to 84%, was achieved at 29 bar Argon gas pressure, which is suitable for the LPBF process. Following on, the produced powder particles were used to print tensile test specimens via LPBF along XY- and ZX-orientations by using laser power = 475 W, laser scanning speed = 800 mm/s, powder layer thickness = 50 µm and hatch distance = 100 µm. The yield and tensile strengths were 9.45% and 13% higher than the ZX direction, while the samples printed in ZX direction resulted in 26.79% more elongation compared to XY-orientation.

Details

Rapid Prototyping Journal, vol. 29 no. 9
Type: Research Article
ISSN: 1355-2546

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Article
Publication date: 5 May 2023

Senlin Zhao and Rongrong Mao

Asymmetric cost information exists between a supplier and a manufacturer regarding the manufacturer's process innovation for remanufacturing (PIR), which may hurt the supplier's…

202

Abstract

Purpose

Asymmetric cost information exists between a supplier and a manufacturer regarding the manufacturer's process innovation for remanufacturing (PIR), which may hurt the supplier's profit. The authors therefore seek to develop a menu of nonlinear pricing contracts for channel information sharing.

Design/methodology/approach

Based on principal–agent theory, the supplier, acting as a Stackelberg leader, designs a menu of nonlinear pricing contracts to impel the manufacturer to disclose its private cost information on PIR (i.e. PIR efficiency). In addition, the authors compare the equilibrium outcomes under asymmetric and symmetric information to examine the effects of asymmetric PIR information on the production policies and profits of the supplier and the manufacturer.

Findings

The proposed contract menu encourages th4e manufacturer to spontaneously share PIR efficiency information with the supplier. Asymmetric PIR information may distort the output of new products upward or downward, but the output of remanufactured products may only be distorted downward. In addition, the manufacturer with high PIR efficiency gains information rent, and interestingly, the increase in the probability of low PIR efficiency amplifies its information rent. Finally, an asymmetric information environment may increase the threshold for the manufacturer to enter remanufacturing.

Originality/value

The authors probe the issue of the supplier's contract design by jointly considering remanufacturing, process innovation and information asymmetry. The paper expands the influencing mechanism of process innovation information in the remanufacturing field. The authors also observe new results that may offer guidance to decision makers.

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