In this study a tool with interchangeable inserts of sintered carbides coated with AlTiN were used to mill a duplex stainless steel with trochoidal strategies. Cutting speed range from 120 to 300 m/min were used and t he evaluation of tool deterioration and tool life was made according international standard ISO 8688-1. It was observed a progressive development of a flank wear and a cumulative cyclic process of localized adhesion of the chip to the cutting edge, followed by chipping, loss of the coating and substrate exposure. The tool life reached a maximum of 35 min. for cutting speed of 120 m/min. However, it was possible to maintain a tool life of 20-25 minutes when the cutting speed was increased up to 240 m/min.

This paper presents the development of fleet management software for mobile robots, including AGV and AMR technologies, within the scope of a case study from the GreenAuto project. The system was designed to integrate position and status data from different robots, unifying this information into a single map. To achieve this, a web-based platform was developed to allow the simultaneous, real-time visualization of all robots in operation. However, the main challenge of this research lies in the heterogeneity of the fleet, which comprises robots of different makes and models from various manufacturers, each using distinct data formats. The proposed approach addresses this by facilitating fleet monitoring and management, ensuring a greater efficiency and coordination in the robot movement. The results demonstrate that the platform improves the traceability and operational supervision, promoting the optimized management of mobile robots. It is concluded that the proposed solution contributes to industrial automation by providing an intuitive and centralized interface, enabling future expansions for new functionalities and the integration with other emerging technologies. The proposed system demonstrated efficiency in updating and supervising operations, with an average latency of 120 ms for task status updates and an interface refresh rate of less than 1 s, enabling near real-time supervision and facilitating operational decision-making.

This paper presents a method for position correction in collaborative robots, applied to a case study in an industrial environment. The case study is aligned with the GreenAuto project and aims to optimize industrial processes through the integration of various hardware elements. The case study focuses on tightening a specific number of nuts onto bolts located on a partition plate, referred to as “Cloison”, which is mounted on commercial vans produced by Stellantis, to secure the plate. The main challenge lies in deviations that may occur in the plate during its assembly process, leading to uncertainties in its fastening to the vehicles. To address this and optimize the process, a collaborative robot was integrated with a 3D vision system and a screwdriving system. By using the 3D vision system, it is possible to determine the bolts’ positions and adjust them within the robot’s frame of reference, enabling the screwdriving system to tighten the nuts accurately. Thus, the proposed method aims to integrate these different systems to tighten the nuts effectively, regardless of the deviations that may arise in the plate during assembly.

The ExoMars programme, which is carried out by European Space Agency (ESA) in cooperation with the Russian federal Space Agency (Roscosmos), foresees a two-steps mission to Mars. The first mission consists of an orbiter and an Entry Descent and Landing Demonstrator Module (EDM) to be launched in January 2016 and is scheduled to land on the planet during the statistical dust storm season; the second mission includes a descent module, a surface platform and a rover and will be launched in 2018. The DREAMS (Dust characterization, Risk assessment and Environment Analyser on the Martian Surface) experiment for ExoMars 2016 is an autonomous meteorological station designed to study the effect of dust on Martian environment which will operate for two Martian days (sols) relying on its own power supply after landing. DREAMS includes a suite of sensors able to analyse temperature, pressure, humidity, wind speed and direction and solar irradiance as well as an electric field probe which will perform the first electrical characterization of Mars surface atmosphere.