AutomationML for Data Exchange in the Robotic Process of Metal Additive Manufacturing

Abstract

Flexibility, adaptability and standardization of multidisciplinary production processes are key issues for today's industry. The digitalization of industry partially helps to overcome these challenges, leading to the need for efficient management of data. AutomationML has been pointed as a solution to solve the problem of data exchange between heterogeneous engineering tools landscape. This paper introduces a practical approach for data exchange on a production-engineering environment linked to Metal Additive Manufacturing (MAM). The proposed approach allows the exchange of data/information between different engineering tools using AutomationML Engine. For example, the MAM paths can be edited and enriched with information along the different stages of the process (design, simulation, robotics) using a neutral format. In the sphere of Direct Energy Deposition (DED) technologies it is proposed a practical use case for data exchange and editing, from computer aided design (CAD), to path planning, to process parameters definition, to robot programming. Results demonstrated the effectiveness of the proposed AutomationML-based solution.