posted on 2020-10-28, 09:30authored byMuzaffar Rao, Liam Lynch, James Coady, Daniel ToalDaniel Toal, Thomas Newe
Industry 4.0 uses the analysis of real-time data, artificial intelligence, automation, and
the interconnection of components of the production lines to improve manufacturing efficiency and quality. Manufacturing Execution Systems (MESs) and Autonomous Intelligent Vehicles (AIVs) are key elements of Industry 4.0 implementations. An MES connects, monitors, and controls data flows on the factory floor, while automation is achieved by using AIVs. The Robot Operating System (ROS) built AIVs are targeted here. To facilitate MES and AIV interactions, there is a need to integrate the MES and the AIVs to help in building an automated and interconnected manufacturing environment. This integration needs middleware which understands both MES and AIVs. To address this issue, a LabVIEW-based scheduler is proposed here as the middleware. LabVIEW communicates with the MES through webservices and has support for ROS. The main task of the scheduler is to control the AIV based on MES requests. The scheduler developed was tested in a real factory environment using the SAP MES and a Robotnik ‘RB-10 robot. The scheduler interface provides real-time information about the current status of the MES, AIV, and the current stage of scheduler processing. The proposed scheduler provides an efficient automated product delivery system that transports
the product from process cell to process cell using the AIV, based on the production
sequences defined by the MES. In addition, using the proposed scheduler, integration of an MES is possible with any low-cost ROS-built AIV.
Funding
Development of theoretical and experimental criteria for predicting the wear resistance of austenitic steels and nanostructured coatings based on a hard alloy under conditions of erosion-corrosion wear