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Research Project
INESC TEC- Institute for Systems and Computer Engineering, Technology and Science
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Publications
Developing an OPC UA Server for CNC Machines
Publication . Martins, André; Lucas, João; Costelha, Hugo; Neves, Carlos
This paper addresses the concept of Industry 4.0 from the perspective of the molds industry, a key industry in today’s industrial panorama. With its constant modernization, several technologies have been introduced, in particular regarding machining equipment. With each brand and model requiring different (proprietary) interfaces and communication protocols, this technological diversity renders the automatic interconnection with production management software extremely challenging. In this paper a methodology to build monitoring solutions for machining devices is defined, based on the main equipment and operations used by molds industry companies. For a standardized approach, OPC UA is used for high-level communication between the various systems. As a key result of this paper, and given the variety of monitoring systems and communication protocols, the developed approach combines various different machine interfaces on a single system, in order to cover a relevant subset of machining equipment currently in use by the molds industry. This kind of all-in-one approach will give production managers access to the information needed for a continuous monitoring and improvement of the entire production process.
Monocular Camera Calibration for Autonomous Driving — a comparative study
Publication . Martins, Pedro Filipe; Costelha, Hugo; Bento, Luís Conde; Neves, Carlos
Autonomous driving is currently a widely researched topic worldwide. With a large research effort being taken by industrial research units in the automotive sector, it is no longer exclusive to academic research labs. Essential to this ongoing effort towards level-5 vehicle autonomy, are the sensors used for tracking and detection, mainly lasers, radars and cameras. Most of the cameras for automotive application systems use wide-angle or fish-eye lens, which present high distortion levels. Cameras need to be calibrated for correct perception, particularly for
capturing geometry features, or for distance-based calculations. This paper describes a case-study concerning monocular camera calibration for a small scale autonomous driving vehicle vision system. It describes the fundamentals on camera calibration and implementation, with results given for different lenses and distortion models. The aim of the paper is not only to provide a detailed and comprehensive review on the application of these calibration methods, but to serve also as a reference document for other researchers and developers starting to use monocular vision in their robotic applications.
An approach to integrating manufacturing data from legacy Injection Moulding Machines using OPC UA
Publication . Martins, André; Miguel Lopes e Silva, Bruno; Costelha, Hugo; Neves, Carlos; Lyons, John; Cosgrove, John
To achieve the ambitions related with the concept of a Smart Factory, manufacturers of new industrial devices have been developing and releasing products capable of integrating themselves into fully-connected environments, with the communication capabilities and advanced specifications required. In these environments, the automatic retrieval of data across the shop floor is a must, allowing the analysis of machine performance for increased production quality and outputs. On most of the recently released industrial devices this machine data is readily available. However, the same is not true when using legacy devices. It is also well established that most SMEs are unable or do not intend to radically replace their industrial devices with this purpose only, since that would imply a high investment, and mainly because many of these legacy machines remain highly productive. That said, there is a need to develop integration methodologies for these legacy industrial devices and provide them with smart factory communication capabilities that make them suitable for the new Smart Factory environments.
In this work, an approach is proposed, using as a case study an industrial shop floor, to integrate data from a range of injection moulding machines, from different generations and different models / manufacturers. This equipment diversity renders the automatic interconnection extremely challenging, but is also representative of many existing industrial scenarios. This research will contribute to the development of integration methodologies and, consequently, improve equipment compatibility. To apply these methodologies, information about specific machines within the shop floor was gathered, as well as their communication and I/O capabilities, together with other features deemed relevant. A trend in recently released machines can be identified, revealing a special focus on the use of OPC UA standard, making use of its address space based on the structured Euromap information models. On the other hand, the legacy devices mainly allow outputting a text file to an external storage unit connected to the machine, containing machine and injection cycles related information. Regarding the communication interfaces available, the Ethernet interface reveals to be the most common among the recently acquired machines, while USB is the main interface in older equipment.
An experimental solution was developed for the presented case study, which uses the machine's USB interface to access these files at each injection cycle, mapping the acquired data to structured information model variables, according with Euromap specifications, and making it available through an OPC UA server address space. The developed server provides a standardized, interoperable, scalable, and secure approach for data exchange between the injection moulding machines and various OPC UA clients, allowing device monitoring and control during operation, as well as transmitting this data to higher-level management systems, e.g., MES and ERP systems. This solution shows that older legacy devices, available across the shop floors, can be retrofitted and integrated in Smart Factory scenarios, side-by-side with recently released equipment, giving production managers access to information needed to monitor and improve the production process, thus moving towards the Factories of the Future.
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Funding agency
Fundação para a Ciência e a Tecnologia
Funding programme
6817 - DCRRNI ID
Funding Award Number
UIDB/50014/2020