Optimization of Process Parameters of Abrasive Water Jet Machining Using Variations of Cohort Intelligence (CI)

Abrasive water jet machining is a non-conventional machining process based on sending abrasive material accelerated with high pressure water on to the planes of focused materials with the purpose to cut various engineering materials. Abrasive water jet machining process has various machining process parameters, which in turn will affect the performance parameters. The combination of all the process parameters results in desired output. Hence it is important to find the optimal combination of process parameters. Several optimization techniques have been used to optimize these parameters. Cohort intelligence (CI) is a socio-inspired algorithm based on artificial intelligence conceptions. Further researchers have developed seven variations of cohort intelligence algorithm. The present work investigates the application of four variations of cohort intelligence for the AWJM process parameter optimization. Variations of CI have been applied for the first time in manufacturing optimization. The considered problem involves optimization of commonly used responses Surface Roughness (Ra) and kerf and results are compared with Firefly Algorithm (FA). The performance of cohort intelligence algorithm is found to be much better than firefly algorithm for four variations.