{'fraction_non_alphanumeric': 0.0199764982373678, 'fraction_numerical': 0.0, 'mean_word_length': 5.983606557377049, 'pattern_counts': {'":': 0, '<': 0, '<?xml version=': 0, '>': 0, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
Optimisation of multiple performance characteristics in abrasive jet machining using grey relational analysis

This paper discusses the application of the Taguchi method to optimise the machining parameters for machining of glass work-pieces in abrasive jet machining (AJM) for individual responses such as material removal rate and surface roughness. Moreover, a multi-response performance characteristic was used for optimisation of process parameters with application of grey relational analysis. The machining parameters are selected as pressure, nozzle-tip-distance, abrasive grain size where as the response variables selected as material removal rate (MRR) and surface roughness (Ra). The results from confirmation runs indicated that the determined optimal combination of machining parameters improved the performance of the machining process.