Optimization of Abrasive Flow Nano-Finishing Processes by Adopting Artificial Viral Intelligence

Abstract

This work deals with the optimization of crucial process parameters related to the abrasive flow machining applications at micro/nano-levels. The optimal combination of abrasive flow machining parameters for nano-finishing has been determined by applying a modified virus-evolutionary genetic algorithm. This algorithm implements two populations: One comprising the hosts and one comprising the viruses. Viruses act as information carriers and thus they contribute to the algorithm by boosting efficient schemata in binary coding to facilitate both the arrival at global optimal solutions and rapid convergence speed. Three cases related to abrasive flow machining have been selected from the literature to implement the algorithm, and the results corresponding to them have been compared to those available by the selected contributions. It has been verified that the results obtained by the virus-evolutionary genetic algorithm are not only practically viable, but far more promising compared to others as well. The three cases selected are the traditional “abrasive flow finishing,” the “rotating workpiece” abrasive flow finishing, and the “rotational-magnetorheological” abrasive flow finishing.

Sustainable Manufacturing Technologies: A Systematic Review of Latest Trends and Themes

“…cloud manufacturing [169,170], intelligent manufacturing systems and metaheuristics [171,172], and Maintenance 4.0 [173] will not only catalyse implementation and dissemination of SM process technologies but also provide meaningful contributions to various SM aspects, including facilitation of remanufacturing [174], optimisation of manufacturing process parameters for sustainability improvements [172], and robotic automation [175]. Ultimately, sustainability assessment is another key pillar of SM [124], which will provide the means for sustainability impact monitoring, decision-making, and continuous improvement through life-cycle assessment (LCA) [136]; multicriteria process parameter analysis and decision-making (MCDM) techniques [176]; and various algorithm-based optimisation approaches [177].…”

“…Ultimately, sustainability assessment is another key pillar of SM [124], which will provide the means for sustainability impact monitoring, decision-making, and continuous improvement through life-cycle assessment (LCA) [136]; multicriteria process parameter analysis and decision-making (MCDM) techniques [176]; and various algorithm-based optimisation approaches [177]. The digital manufacturing technologies, such as data analytics architectures [168], cloud manufacturing [169,170], intelligent manufacturing systems and metaheuristics [171,172], and Maintenance 4.0 [173] will not only catalyse implementation and dissemination of SM process technologies but also provide meaningful contributions to various SM aspects, including facilitation of remanufacturing [174], optimisation of manufacturing process parameters for sustainability improvements [172], and robotic automation [175].…”

“…Expansion of scope: Although the scope of SM technology research was established as significant, limited research was noted on key technologies, such as cloud manufacturing and data analytics; manufacturing system and process design for sustainability; intelligent manufacturing systems; and some fundamental processes, such as grinding and drilling. In particular, state-of-the-art contributions, such as Fountas and Vaxevanidis (2021) highlight the high potential and key role of metaheuristics in driving sustainable development of the manufacturing processes, including the machining processes, facilitating optimisation of process parameters [171,172]. Future SM technology research is particularly encouraged in these fundamental manufacturing areas, which will pave the way for sustainable manufacturing.…”

Surface Characteristics Measurement Using Computer Vision: A Review

“…Al-Kindi et al [241] provided an approach focused on perception to the measurement of surface roughness in micro and nano areas [241,268,269]. The suggested solution offered effective outcomes.…”

Application of Evolutionary Artificial Intelligence. An Exploratory Literature Review

“…Microbiology and medical knowledge have also inspired scientists to create algorithms that simulate the behaviour of viruses [73] and the processes of changes in immunity [74].…”