Abrasive Water Jet Machining of Engineering Materials

Abrasive water jet machining (AWJM) is an advanced machining process and has a potential to cut a wide range of engineering materials. This chapter provides an understanding of AWJM process. It sheds light on working principle and mechanism of AWJM process and its process parameters, and significant benefits are discussed. This chapter also reviews some of the recent past work on cutting of various engineering materials and machining of complex shapes, typical features, and micro-parts by AWJM.

Abrasive water jet machining (AWJM) is a widely accepted sustainable machining method used to machine difficult-to-cut materials in view of both environmental and economic benefits. This chapter discusses the machining performance of sustainable/green machining method on AISI 304 grade steel material. Five process parameters, namely abrasive grain size (A), abrasive flow rate (B), nozzle speed (C), working pressure (D), and standoff distance (E), are used to know the green machining attributes like MRR, process time, surface roughness, and process energy. Experimentation is done using Taguchi (L₂₇) orthogonal array to study the influence of each process parameters on the green machining parameters. Additionally, regression analysis and ANOVA are done to show the statistical significance of the green machining process. At last, the DEAR method is used for the optimization of green machining attributes of AWJM process. The results show that AWJM process is an adequate process for machining of metallic materials and produces high-quality parts with excellent productivity and less environmental pollution. The overall optimal setting obtained is A (60 mesh, level 1), B (1.5 mm, level 1), C (150 MPa, level 1), D (225 mm/min, level 3), and E (5 g/s, level 2). The corresponding green attributes obtained are SR as 1.84 μm, MRR as 468 mm³/min, PT as 0.128 s, and PE as 769 W. Finally, confirmatory results for MRR, SR, PT, PE are found closer to the experimental results and well within the considerable ranges and satisfactory.

This chapter presents the machining performance of green abrasive water jet machining process on polymer composites. Abrasive water jet machining (AWJM), a commonly known as green machining process and wood dust filler-based reinforced polymer (WDFRP) composites or green composites, is considered in this study. An experimental investigation is carried out based on Taguchi (L₉-OA) to analyze the sensitivity of green machining attributes [such as MRR, surface roughness (SR), and machining time (MT)] to the variation in process parameters like standoff distance (SoD), working pressure (WP), nozzle speed (NS), and abrasive grain size (AGS). Additionally, regression analysis and ANOVA are done to show the statistical significance of the green machining process. At last, MOORA method is used for the optimization of AWJM process parameters. Investigation result indicates that green machining process, i.e., AWJM process is adequate in the machining of green composites and produce high-quality parts with excellent productivity and less machining time. Optimal setting obtained is SoD (2 mm, level 2), WP (125 MPa, level 1), NS (300 mm/min, level 3), and AGS (70 mesh, level 1). Parameter SoD found more significance on the AWJM response in all the cases during the machining process. Confirmatory results for MRR, SR, MT are found closer to the experimental results and well within the considerable ranges and satisfactory.

This chapter is focused on machining performance of AWJM process during the machining of zirconia (ZrO₂) ceramic composites. Experiments are conducted using the Taguchi (L₂₇) method to analyze the influence of AWJM parameters [standoff distance (A), the working pressure (B), and nozzle speed (C)] on the response parameters such as MRR and surface roughness (SR). In addition, regression and ANOVA analysis are performed to show the statistical significance of the AWJM (green machining) process. Moreover, empirical equations are derived which define the responses as a mathematical function of input variables for optimum prediction response parameters for the green machining (AWJM) process. In addition, multiple objective particle swarm optimization based on crowding distance (MOPSO-COD) method is employed to solve the optimization problem that simultaneously minimizes SR by maximizing MRR. The overall optimal setting obtained is A (1.5 mm, level 1), B (150 MPa, level 1), and C (225 mm/min, level 1). The corresponding green attributes obtained are MRR as 345.72 mm³/min and SR as 0.194 µm. Confirmatory results for MRR and SR are found closer to the experimental results and well within the considerable ranges and satisfactory.