Session: 03-04-03: Advanced Machining and Finishing Processes

Paper Number: 115307

115307 - Waterjet Process Parameters Optimization 

The need for more optimization in advance manufacturing processes is becoming an important factor impacting the utilization of a given process. Abrasive water jet machining (AWJM) is a non-traditional cutting process that has gained prominence in advanced modern manufacturing industries for decades. Due to its advantageous machining capabilities, it is applicable in cutting all types of materials without changing the cutting tool or the geometry within a short period. The machining process's optimal result depends on the suitable configuration of the process parameters. There has been intense research on exploiting the interrelation of these process input parameters and how they can affect the desired finishing quality in terms of the material removal rate (MRR) and the surface roughness (Ra) for different materials. The change in one parameter affects the constraints of the others since these parameters are interrelated. Most research work done in the past has revealed that these input parameters, including water pressure, abrasive mass flow rate, stand-off distance, and the cutting feed, are the essential process input parameter that impacts the output results. This paper will investigate the effect of the various process parameters on selected types of materials in terms of workpiece  thickness. Establishing that parameter selection depends on the type of material and workpiece thickness to develop the optimal selection for the desired cutting to achieve the preferred response. Little research has been done on the impact of the input process parameters on the kerf width and the material removal rate based on the material thickness. The methodology for this research will be based on Design of experiment (DoE) using the Taguchi approach to study and analyze the effect of the following four factors on the output responses: 1) the pressure, 2) abrasive flow rate, 3) traverse speed, and 4) material thickness. Using three levels for each factor based on low, medium, and high categories to establish the potential range for the optimal values within the set levels.  The waterjet machine used is A-1212 WARDJet machine by Wardjet will be used for the research to perform the experiments on aluminum and steel metals. Taguchi orthogonal arrays will be generated using Minitab, where each experiment will be performed to obtain the response for the kerf width and the material removal rate. The expected result will establish that the variation in different material thicknesses affects the output response. Setting the optimal parameter combination will lead to the preferred result and reduce the cycle time for the machining process. Experiments will be run to achieve the best quality characteristics and conclude the best parameter selection approach for specific material thickness.

Key words: waterjet cutting, optimization, DoE, Taguchi method, advanced manufacturing

Presenting Author: Basel Alsayyed Western Carolina University

Presenting Author Biography: Dr. Basel Alsayyed is the Engineering Technology Program Director at the School of Engineering + Technology in Western Carolina University. Dr. Alsayyed just got the ABET program Evaluator Certificate. Before joining WCU, Dr. Alsayyed was an Industrial Professor in the department of mechanical engineering, of University of Alberta (UofA), Canada. Prior to joining UofA, Dr. Alsayyed was an Associate Professor at the Department of Mechanical Engineering in UAE University. With over 19 years of experience in academia, and over 12 years of industrial experience, primarily in the American automotive industry, Dr. Alsayyed has a passion for innovation in education, teaching, research, and training. Integration of academia and industry goals and activities are paramount to Dr. Alsayyed. Sensing the industry needs and preparing future engineers to meet those needs and challenges is an important dimension of Dr. Alsayyed’s activities.
Dr. Alsayyed has published more than forty articles in peer-reviewed journals and conference proceedings. He has seven granted patents. Dr. Alsayyed’s research interests are in the areas of advanced manufacturing, additive manufacturing, design optimization, quality & reliability, engineering education, project management, and knowledge management.
Dr. Alsayyed has a Ph.D. in Industrial engineering, three Masters: (Industrial Engineering, Manufacturing Engineering, and Project Management). Dr. Alsayyed is a Professional Engineer and a Certified Manufacturing Engineer (CMfgE) since 1997.

Authors:

Basel Alsayyed Western Carolina University
Frederick Malm Western Carolina University