This paper presents an improved mathematical model for calculation of distortion vectors of two aligned surface meshes. The model shows better accuracy when benchmarked to an existing model with exceptional mathematical conditions, such as sharp corners and small radii. The model was implemented into a developed distortion compensation digital tool and applied to an industrial component. The component was made of Inconel 718 and produced by laser powder bed fusion 3D printing technology. The digital tool was utilised to compensate the original design geometry by pre-distortion of its original geometry using the developed mathematical model. The distortion of an industrial component was reduced from approximately ±400 µm to ±100 µm for a challenging thin structure subjected to buckling during the build process. GRAPHICAL ABSTRACT

The new market trends are very different, so it is crucial to the companies improve the tools and capabilities that allow themselves readjust rapidly and effectively to the news market changes and to the new requirements. In order to facilitate this process, it is proposed in this paper an agent based implementation that can provide to the existent systems the capacity to quickly adapt and reconfigure using standard technology. The proposed framework provides an intelligent tool to autonomously help the configuration when a production operator pretends to introduce a new variant of product in runtime and consult important information provided by the system to monitor execution.

This paper presents the design of a multi-agent framework that aids engineers in the adaptation of modular production systems. The framework includes general implementations of agents and other software components for self-learning and adaptation, sensor data analysis, system modelling and simulation, as well as human-computer interaction. During an adaptation process, operators make changes to the production system, in order to increase capacity or manufacture a product variant. These changes are automatically captured and evaluated by the framework, building an experience base of adjustments that is then used to infer adaptation knowledge. The architecture of the framework consists of agents divided in two layers: the agents in the lower layer are associated with individual production modules, whereas the agents in the higher layer are associated with the entire production line. Modelling, learning, and adaptations can be performed at both levels, using a semantic model to specify the structure and capabilities of the production system. An evaluation of a prototype implementation has been conducted on an industrial assembly system. The results indicate that the use of the framework in a typical adaptation process provides a significant reduction in time and resources required.