Experimentation investigation of abrasive water jet machining parameters using Taguchi and Evolutionary optimization techniques

- The paper demonstrates the applications of the some important optimization techniques.
- Selection of the optimal AWJM process parameters is significant.
- The experimentation is conducted on material “AA6351 Al-alloy” with abrasive water jet machining (AWJM) to get the optimum values of performance parameters “kerf top width and taper angle” for the given range of process parameters.
- Based on experimental results, the regression models for the performance parameters are developed.
- This paper compares the performance of seven optimization algorithms and confirmatory tests are conducted to validate the results.

In the last decade, numerous new materials are rapidly emerging and developed; it creates considerable interest in the researcher to search out the optimum combination of machining parameters during machining of these materials using advanced machining processes (AMP). In this work, an experimental investigation is carried out on abrasive water jet machining (AWJM) process for the machining of material AA631-T6 using the Taguchi methodology. Parameters such as transverse speed, standoff distance and mass flow rate are considered to obtain the influence of these parameters on kerf top width and taper angle. Regression models have been developed to correlate the data generated using experimental results. Seven advanced optimization techniques, i.e., particle swarm optimization, firefly algorithm, artificial bee colony, simulated annealing, black hole, biogeography based and non-dominated sorting genetic algorithm are attempted for the considered AWJM process. The effectiveness of these algorithms is compared and found that bio-geography algorithm is performing better compared to other algorithms. Furthermore, a non-dominated set of solution is obtained to have diversity in the solutions for the AWJM process. The result obtained using the Taguchi method and optimization techniques are confirmed using confirmation experiments. Confirmatory experiments show that both the optimization techniques and Taguchi method are the effective tools in optimizing the process parameters of the AWJM process.