Bio-Inspired Self-Organisation in Evolvable Production Systems

Abstract: The increasing market fluctuations and customized products demand have dramatically changed the focus of industry towards organizational sustainability and supply chain agility. Such critical changes in the strategic vision of the companies inevitably have a direct impact on the shop-floor operational requirements. In this sense, traditional shop-floor approaches are becoming increasingly inadequate leading to the adoption of more pluggable and reusable solutions.The emergence o modern manufacturing paradigms translates the effort undertaken by the academia in order to provide the required background to support the implementation of such distributed mechatronic systems. Biological systems, due to their similar distributed network-like structure, represent naturally a common analogy and source of inspiration for such distributed modular approaches. Hence, modern manufacturing paradigms usually rely on complexity science biologically inspired concepts to attain distributed control, adaptability, evolution, flexibility and robustness as core concepts. This originated the implementation of a number of different multi-agent based architectures. Nevertheless, with time the majority of the these implementation efforts left behind most of the bio-inspired concepts resulting in simple distributed approaches with considerable limitations regarding scalability, reconfigurability and distributed problem resolution. Particularly under the scope of Evolvable Production System (EPS) the implementation of self-organising mechanisms based on negotiation interaction protocols and dynamic coalition-based hierarchical complexity, have considerable hindered the system performance and limited the full exploitation of the paradigm potential.In this context, this licentiate thesis is focused on the development of a self-organising manufacturing systems that holistically mimics the main structural and regulatory principles followed by natural systems.For this purpose, the present approach was designed as opposed to the current tendency followed by modern productions approaches, in which the product holds the production knowledge and is responsible for the management of its own production. Instead, the production knowledge was reduced to the minimum and distributed over the manufacturing components. Self-organising principles heavily inspired on the regulatory mechanisms of biological systems, were then devised to regulate the critical control mechanisms of the manufacturing system. Hence, similarly to the natural world the characteristics and the system overall production emerge as consequence of the micro-dynamics of the systems. In this way, it becomes therefore possible to attain a system that is not only highly reconfigurable and scalable but also able to distributively tackle the manufacturing processes.Although the present work has been developed under the Evolvable Production System context, the introduced approach can be easily adapted to a wider range of modular networked-based systems.