Abrasive waterjet process parameters optimization
- WCU Author/Contributor (non-WCU co-authors, if there are any, appear on document)
- Frederick Malm (Creator)
- Institution
- Western Carolina University (WCU )
- Web Site: http://library.wcu.edu/
- Advisor
- Basel Alsayyed
Abstract: Abrasive waterjet machining has gained significant importance in the manufacturing sector for its efficiency and versatility in cutting various materials without generating heat, making it suitable for temperature-sensitive materials. It presents a significant challenge in achieving high-quality surface finishes, especially with varying metal thicknesses. The study aimed to use the Taguchi Design of Experiment (DOE) coupled with Grey Relational Analysis (GRA) to optimize the single and multi-responses for Aluminum 6061-T6 and 1020 carbon steel. The experiments were conducted using the A-0612 WARD Jet machine, and data analysis was performed using Minitab and Microsoft Excel. The Taguchi orthogonal array was used to design the experimental runs(L27). This experimental research explored the effects of influential input factors such as water pressure, abrasive mass flow rate, traverse speed, standoff distance, and material thickness, where each input factor was tested at three levels. The GRA methodology was used to optimize the output responses, such as surface roughness (Ra), Kerf angle, and material removal rate (MRR), simultaneously to achieve high surface quality, and the results were compared to those of the single response optimization. The study highlights the significant impact of material thickness on the variation in machined metal surface quality. The main effect plots and analysis of variance (ANOVA) reveal that aluminum thicknesses of 1.016 and 4.825mm and carbon steel thicknesses of 6.35 and 9.525 mm consistently result in the desirable output response. These high-quality results were achieved using optimal settings derived from the findings of the optimization model.
Abrasive waterjet process parameters optimization
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Created on 5/1/2024
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Additional Information
- Publication
- Thesis
- Language: English
- Date: 2024
- Keywords
- Analysis of Variance (ANOVA), Grey Relational Analysis (GRA), Non traditional machining, Optimization, Taguchi DOE, Waterjet
- Subjects
- Abrasives
- Water jet cutting
- Taguchi methods (Quality control)
- Mathematical optimization
- Analysis of variance