Abstract

Industry 4.0’s vision incorporates decentralised production planning and control to cater for the complex and unpredictable future production environment, resulting from market fluctuation, and changes in customers demands and behaviour. One of the primary goals of decentralised planning and control in industry 4.0 is to realise a fully autonomous production system, where manufacturing resources, material handling systems, and products can execute production tasks without human involvement. Decentralised control, and by extension, self-organisation and emergence properties, achieved through meta-heuristics techniques have been proposed to achieve autonomous production. But these approaches have not been adequately explored in actual production systems, due to their unpredictability, uncontrollability and slow convergence. To address these challenges, we propose an Enhanced Meta-heuristic Approach (EMA), where an iterative optimisation algorithm guides the meta-heuristics optimisation process to ensure good solutions are achievable in a shorter time.

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