Self-configuration of a Robotic Platform to support a self-organized Manufacturing Process
Luis A. Estrada-Jimenez, David Sanderson, Jack C. Chaplin, José Barata
Abstract
Self-configuration in manufacturing is a key trend to generate adaptable production systems. Different product requirements need different machine settings and continuous software update. Existing approaches usually assume that manufacturing resources (e.g. robotic platforms) have already a predefined set of available capabilities or that there is a centralized manager able to provide configuration updates. Centralized approaches are not always a suitable solution. Dynamic changes in production require continuous maintainability of the central server, constraining the shop-floor agility. New approaches should consider emergent self-configuration i.e. carried out at run time and decoupled from a centralized unit. In this work we present a framework for self-configuration of robotic platforms, where those are not explicitly preconfigured; instead, control parameters are transferred wirelessly from raw material to resources during production (once they arrive to the resource), following an intelligent product-driven manufacturing approach. A set of templates are proposed to generalize the sequential behaviour of manufacturing operations. Thus, manufacturing resources can read, use these parameters and store them for future operations. This framework is illustrated with an assembly operation using an educational robotic platform.