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Even if the economy nowadays is still locked into a linear model of production, tighter environmental standards, resource scarcity and changing consumer expectations are forcing organizations to find alternatives to lighten their impacts. The concept of Circular Economy (CE) is to an increasing extent treated as a solution to this series of challenges. That said, the multitude of approaches and definitions around CE and Life Cycle Extension Strategies (LCES) makes it difficult to provide (Small and Medium Enterprise) SMEs with a consistent understanding of the topic. This paper aims at bridging this gap by providing a systematic literature review of the most prominent papers related to the CE and lifetime extension, with a particular focus on the equipment and machinery sector. A taxonomy was used to define and cluster a subset of selected papers to build a homogeneous approach for understanding the multiple strategies used in the industry, and the standards in maintenance and remanufacturing strategies. As a final research step, we also propose a Strategy Characterization Framework (SCF) to build the ground for the selection of the best strategy to be applied for production equipment life cycle extension on several industrial use cases.
Alessandro Fontana; Andrea Barni; Deborah Leone; Maurizio Spirito; Agata Tringale; Matteo Ferraris; Joao Reis; Gil Goncalves. Circular Economy Strategies for Equipment Lifetime Extension: A Systematic Review. Sustainability 2021, 13, 1117 .
AMA StyleAlessandro Fontana, Andrea Barni, Deborah Leone, Maurizio Spirito, Agata Tringale, Matteo Ferraris, Joao Reis, Gil Goncalves. Circular Economy Strategies for Equipment Lifetime Extension: A Systematic Review. Sustainability. 2021; 13 (3):1117.
Chicago/Turabian StyleAlessandro Fontana; Andrea Barni; Deborah Leone; Maurizio Spirito; Agata Tringale; Matteo Ferraris; Joao Reis; Gil Goncalves. 2021. "Circular Economy Strategies for Equipment Lifetime Extension: A Systematic Review." Sustainability 13, no. 3: 1117.
Purpose This paper aims to provide a service-based integrated prototype framework for the design of reusable modular assembly systems (RMAS) incorporating reusability of equipment into the process. It extends AutomationML (AML) developments for an engineering data exchange to integrate and standardize the data formats that support the design of RMAS. Design/methodology/approach The approach provides a set of systematic procedures and support tools for the design of RMAS. This includes enhanced domain knowledge models that facilitate the interpretation and integration of information across the design phases. Findings The inclusion of reusability aspects in the design phase improves the sustainability of future assembly systems, by ensuring equipment use until its end-of-life. Moreover, the integrated support tools reduce the design time, while improving the quality/performance of the system design solution, as it enables the exploration of a larger solution space. This will result in a better response to dynamic and rapidly changing system requirements. Social implications This work provides a sustainable approach for the design of modular assembly systems (MAS), which will ensure better resource utilization. Additionally, the standardization of the data and the support of low cost tools is expected to benefit industrial companies, particularly the small- and medium-sized enterprises. Originality/value This approach offers a service-based platform which uses production data to incorporate reusability aspects into the design process of modular assembly system. Moreover, it provides a framework for modular assembly system design by extending the current design processes and interactions between stakeholders. To support this, a standardized method for information representation and exchange across the several phases of the RMAS design activity is briefly illustrated with an industrial case study.
Pedro Ferreira; Paul Danny Anandan; Ivo Pereira; Vikrant Hiwarkar; Mohmed Sayed; Niels Lohse; Susana Aguiar; Gil Gonçalves; Joana Gonçalves; Fabian Bottinger. Integrated design environment for reusable modular assembly systems. Assembly Automation 2019, 39, 664 -672.
AMA StylePedro Ferreira, Paul Danny Anandan, Ivo Pereira, Vikrant Hiwarkar, Mohmed Sayed, Niels Lohse, Susana Aguiar, Gil Gonçalves, Joana Gonçalves, Fabian Bottinger. Integrated design environment for reusable modular assembly systems. Assembly Automation. 2019; 39 (4):664-672.
Chicago/Turabian StylePedro Ferreira; Paul Danny Anandan; Ivo Pereira; Vikrant Hiwarkar; Mohmed Sayed; Niels Lohse; Susana Aguiar; Gil Gonçalves; Joana Gonçalves; Fabian Bottinger. 2019. "Integrated design environment for reusable modular assembly systems." Assembly Automation 39, no. 4: 664-672.
Absolute automation in certain industries, such as the automotive industry, has proven to be disadvantageous. Robots are fairly capable when performing tasks that are repetitive and demand precision. However, a hybrid solution comprised of the adaptability and resourcefulness of humans cooperating, in the same task, with the precision and efficiency of machines is the next step for automation. Manipulators, however, lack self-adaptability and true collaborative behaviour. And so, through the integration of vision systems, manipulators can perceive their environment and also understand complex interactions. In this paper, a vision-based collaborative proof-of-concept framework is proposed using the Kinect v2, a UR5 robotic manipulator and MATLAB. This framework implements 3 behavioural modes, 1) a Self-Adaptive mode for obstacle detection and avoidance, 2) a Collaborative mode for physical human-robot interaction and 3) a standby Safe mode. These modes are activated with recourse to gestures, by virtue of the body tracking and gesture recognition algorithm of the Kinect v2. Additionally, to allow self-recognition of the robot, the Region Growing segmentation is combined with the UR5’s Forward Kinematics for precise, near real-time segmentation. Furthermore, self-adaptive reactive behaviour is implemented by using artificial repulsive action for the manipulator’s end-effector. Reaction times were tested for all three modes, being that Collaborative and Safe mode would take up to 5 seconds to accomplish the movement, while Self-Adaptive mode could take up to 10 seconds between reactions.
Roberto Nogueira; Joao Reis; Rui Pinto; Gil Gonçalves. Self-adaptive Cobots in Cyber-Physical Production Systems. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) 2019, 521 -528.
AMA StyleRoberto Nogueira, Joao Reis, Rui Pinto, Gil Gonçalves. Self-adaptive Cobots in Cyber-Physical Production Systems. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 2019; ():521-528.
Chicago/Turabian StyleRoberto Nogueira; Joao Reis; Rui Pinto; Gil Gonçalves. 2019. "Self-adaptive Cobots in Cyber-Physical Production Systems." 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) , no. : 521-528.
In today’s industry, production processes are more oriented towards customer customization, demanding manufacturing plants to be increasingly flexible, where Human-Robot Collaboration (HRC) plays an important role. To fully take advantage of this collaboration, both robot and human need to perceive each others actions and intentions, operating accordingly. Thus, the typical collaborative environment that is nowadays monitored only for safety purposes needs to evolve into a more transparent, informative and attainable concept in order to give human-like perception to the robot.This paper proposes a voxel-based space monitoring approach in collaborative robotics environments, where distinct technologies are combined to form a labeled occupancy voxel-grid (LOG), i.e, a three-dimensional grid with labels for all the critical elements of the collaborative environment. A stereo vision camera is used to capture the supervised space in a point cloud, to then create an unlabeled voxel-grid. Making use of the RGB frames, both human and robot joint positions are located (using OpenPose and robot controller), pinpointing the positions of other significant elements in collaborative tasks as well. These positions are used to label the base voxel-grid. With the composition of the collaborative space provided in the grid, not only typical obstacle avoidance can be achieved, but also more advanced topics like predictive control or task recognition. Overall, this approach provides a much higher perception of the collaborative environment, enabling a more symbiotic relation between human and robot in collaborative robotics.
Liliana Antao; Joao Reis; Gil Gonçalves. Voxel-based Space Monitoring in Human-Robot Collaboration Environments. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) 2019, 552 -559.
AMA StyleLiliana Antao, Joao Reis, Gil Gonçalves. Voxel-based Space Monitoring in Human-Robot Collaboration Environments. 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA). 2019; ():552-559.
Chicago/Turabian StyleLiliana Antao; Joao Reis; Gil Gonçalves. 2019. "Voxel-based Space Monitoring in Human-Robot Collaboration Environments." 2019 24th IEEE International Conference on Emerging Technologies and Factory Automation (ETFA) , no. : 552-559.
One of the consequences of passing from mass production to mass customization paradigm in the nowadays industrialized world is the need to increase flexibility and responsiveness of manufacturing companies. The high-mix / low-volume production forces constant accommodations of unknown product variants, which ultimately leads to high periods of machine calibration. The difficulty related with machine calibration is that experience is required together with a set of experiments to meet the final product quality. Unfortunately, all possible combinations of machine parameters is so high that is difficult to build empirical knowledge. Due to this fact, normally trial and error approaches are taken making one-of-a-kind products not viable. Therefore, a Zero-Shot Learning (ZSL) based approach called hyper-process model (HPM) to learn the relation among multiple tasks is used as a way to shorten the calibration phase. Assuming each product variant is a task to solve, first, a shape analysis on data to learn common modes of deformation between tasks is made, and secondly, a mapping between these modes and task descriptions is performed. Ultimately, the present work has two main contributions: 1) Formulation of an industrial problem into a ZSL setting where new process models can be generated for process optimization and 2) the definition of a regression problem in the domain of ZSL. For that purpose, a 2-d deep drawing simulated process was used based on data collected from the Abaqus simulator, where a significant number of process models were collected to test the effectiveness of the approach. The obtained results show that is possible to learn new tasks without any available data (both labeled and unlabeled) by leveraging information about already existing tasks, allowing to speed up the calibration phase and make a quicker integration of new products into manufacturing systems.
João Reis; Gil Gonçalves. A Zero-Shot Learning application in Deep Drawing process using Hyper-Process Model. 2019, 1 .
AMA StyleJoão Reis, Gil Gonçalves. A Zero-Shot Learning application in Deep Drawing process using Hyper-Process Model. . 2019; ():1.
Chicago/Turabian StyleJoão Reis; Gil Gonçalves. 2019. "A Zero-Shot Learning application in Deep Drawing process using Hyper-Process Model." , no. : 1.
Eliseu Pereira; Rui Pinto; João Reis; Gil Gonçalves. MQTT-RD: A MQTT based Resource Discovery for Machine to Machine Communication. Proceedings of the 4th International Conference on Internet of Things, Big Data and Security 2019, 115 -124.
AMA StyleEliseu Pereira, Rui Pinto, João Reis, Gil Gonçalves. MQTT-RD: A MQTT based Resource Discovery for Machine to Machine Communication. Proceedings of the 4th International Conference on Internet of Things, Big Data and Security. 2019; ():115-124.
Chicago/Turabian StyleEliseu Pereira; Rui Pinto; João Reis; Gil Gonçalves. 2019. "MQTT-RD: A MQTT based Resource Discovery for Machine to Machine Communication." Proceedings of the 4th International Conference on Internet of Things, Big Data and Security , no. : 115-124.
Transfer Learning aims at transferring knowledge from an already learned task to a different, but related task, in order to accelerate the learning process of the latter. This concept can be applied to manufacturing systems where process models that map process parameters into process quality are used to optimize the calibration phase of new unseen products at the shop-floor. However, these process models often require a great amount of experiments, which normally is costly and impractical for most manufacturing systems. The present work explores a Laser Seam Welding scenario with 3 different product variants where the problem is training one of the process models with a reduced amount of labeled data. Artificial Neural Networks (ANNs) were used to model these processes and Inductive Transfer Learning is then used to tackle the proposed problem. Ultimately, this approach was compared to traditional machine learning where no transfer occurs and a model is trained only using the small amount of labeled data. The results revealed that for all the Laser Seam Welding processes the trained models performed better when using Inductive Transfer.
Joao Reis; Gil Gonçalves. Laser Seam Welding optimization using Inductive Transfer Learning with Artificial Neural Networks. 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) 2018, 1, 646 -653.
AMA StyleJoao Reis, Gil Gonçalves. Laser Seam Welding optimization using Inductive Transfer Learning with Artificial Neural Networks. 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA). 2018; 1 ():646-653.
Chicago/Turabian StyleJoao Reis; Gil Gonçalves. 2018. "Laser Seam Welding optimization using Inductive Transfer Learning with Artificial Neural Networks." 2018 IEEE 23rd International Conference on Emerging Technologies and Factory Automation (ETFA) 1, no. : 646-653.
Recently, the concept of Human-centered automation is adopted in Human-Robot Collaboration (HRC) scenarios, where interactive manufacturing systems are designed to emphasize human activities, by relating them with Cyber-Physical Production Systems (CPPS). This research is focused on self-adaptation of industrial manipulators to the operator's physiological characteristics, which involve the correlation of different biometric signals. A collaborative environment was achieved by implementing a CPPS for this intent. The developed use case scenario consists in a simple manufacturing process, which involves a human operator and a mini robotic arm, in a joint manipulation of objects. The robotic arm assists the human operator regarding task execution, considering the worker's real-time monitoring, regarding stress and fatigue levels and motion tracking. The monitoring of the human operator serves as input for the self-adaptation of the robotic arm, namely task execution's speed, and correct operation. Presented results show that the implemented Fuzzy system can classify stress and fatigue with an accuracy of 87.8% and 74.4% respectively.
Liliana Antao; Rui Pinto; Joao Reis; Gil Gonçalves; Fernando Lobo Pereira. Cooperative Human-Machine Interaction in Industrial Environments. 2018 13th APCA International Conference on Control and Soft Computing (CONTROLO) 2018, 430 -435.
AMA StyleLiliana Antao, Rui Pinto, Joao Reis, Gil Gonçalves, Fernando Lobo Pereira. Cooperative Human-Machine Interaction in Industrial Environments. 2018 13th APCA International Conference on Control and Soft Computing (CONTROLO). 2018; ():430-435.
Chicago/Turabian StyleLiliana Antao; Rui Pinto; Joao Reis; Gil Gonçalves; Fernando Lobo Pereira. 2018. "Cooperative Human-Machine Interaction in Industrial Environments." 2018 13th APCA International Conference on Control and Soft Computing (CONTROLO) , no. : 430-435.
In this paper we show how Component Based Software Engineering (CBSE) concepts were applied to design the Sensor SelComp. Therefore, a component framework to address the abstraction of Component Level within the SelSus European Project ICPS. We show how the framework can be used to tackle IPCS virtualization of sensors, machines and data processing. Moreover, we show the applicability of Sensor SelComp to a real case scenario where a Bayesian Network model was applied to a SelSus demonstrator to perform runtime fault detection in a RTV dispenser machine from Ford Motor Company.
Luis Neto; Anders L. Madsen; Nicolaj Sondberg-Jeppesen; Ricardo Pinto da Silva; João Reis; Peter McIntyre; Gil Gonçalves. A component framework as an enabler for industrial cyber physical systems. 2018 IEEE Industrial Cyber-Physical Systems (ICPS) 2018, 339 -344.
AMA StyleLuis Neto, Anders L. Madsen, Nicolaj Sondberg-Jeppesen, Ricardo Pinto da Silva, João Reis, Peter McIntyre, Gil Gonçalves. A component framework as an enabler for industrial cyber physical systems. 2018 IEEE Industrial Cyber-Physical Systems (ICPS). 2018; ():339-344.
Chicago/Turabian StyleLuis Neto; Anders L. Madsen; Nicolaj Sondberg-Jeppesen; Ricardo Pinto da Silva; João Reis; Peter McIntyre; Gil Gonçalves. 2018. "A component framework as an enabler for industrial cyber physical systems." 2018 IEEE Industrial Cyber-Physical Systems (ICPS) , no. : 339-344.
The present paper details a novel methodology called Meta-Process Model that is able to generate new data-based models for manufacturing processes when no experimental data is available. For that purpose, the concept of Hyper-Models was used to create a higher level of abstraction of these manufacturing processes, along with a Statistical Shape Model (SSM) that is able to capture the modes of shape variations and build up a deformable model to generate new shapes. The main premise of the present work is to interpret a process model as a n-dimensional shape and use SSM to capture the variations among a set of different process models. This methodology is evaluated by using two already existing process models for a model generalization, from which a new process model is derived just with new, given process conditions. This new process model is then compared with a process model, which was independently estimated using real experimental data acquired under the same process conditions. The results show that a previously nonexistent process model that captures the dynamics of the real process can be generated, even when there's no experimental data and only the new process conditions are available.
João Reis; Gil Goncalves; Norbert Link. Meta-process modeling methodology for process model generation in intelligent manufacturing. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society 2017, 3396 -3402.
AMA StyleJoão Reis, Gil Goncalves, Norbert Link. Meta-process modeling methodology for process model generation in intelligent manufacturing. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 2017; ():3396-3402.
Chicago/Turabian StyleJoão Reis; Gil Goncalves; Norbert Link. 2017. "Meta-process modeling methodology for process model generation in intelligent manufacturing." IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society , no. : 3396-3402.
Cyber-Physical Production Systems (CPPS) are the key enabling for industrial businesses and economic growth. With the introduction of the Internet of Things (IoT) in the manufacturing environment, CPPS have a huge potential in terms of new business opportunities, mostly known as the 4 th Industrial Revolution. The paper presents a CPPS architecture achieved within the European R&D project SelSus, which is validated in an industrial human-machine collaborative use case scenario. This scenario is composed by a set of sequential gripping operations between a person and a robotic arm, where both sensing and actuation devices are virtualized using the SmartComponent concept. The developed prototype demonstrated that the SelSus CPPS enabled self-adaptation in industrial equipment, in order to help the human operator under high levels of stress and fatigue.
João Reis; Rui Pinto; Gil Goncalves. Human-centered application using cyber-physical production system. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society 2017, 8634 -8639.
AMA StyleJoão Reis, Rui Pinto, Gil Goncalves. Human-centered application using cyber-physical production system. IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society. 2017; ():8634-8639.
Chicago/Turabian StyleJoão Reis; Rui Pinto; Gil Goncalves. 2017. "Human-centered application using cyber-physical production system." IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society , no. : 8634-8639.
This work was developed in the context of European funded Project SelSus. Industrial clouds are heavily sensor based and Cloud Manufacturing Service frameworks are mostly grounded in the adoption of Internet of Things and Wireless Sensor Networks technologies. The SelSus framework combines both an Industrial Sensor Cloud and a Cyber Physical Production System. The Industrial Sensor Cloud supports the Cyber Physical Production System, by providing computational power, as well as internal coordination and control, and external access to realize intelligent monitoring and control. The SelSus framework combines embedded systems, networks, sensors and actuators and control algorithms in a seamless manner. Our goal is to have a Flexible Sensor Integration solution that allows rapid graphical development of interpreters of raw data packets in the Cloud and its deployment for embedded execution at the Wireless Sensor Network gateway level for automatic data acquisition. This paper describes such a technology and demonstrates its feasibility, where a match between a graphically developed interpreter and the received messages from the Wireless Sensor Network in US-ASCII is made, and the integration of such sensors is made into the system.
Ricardo Pinto da Silva; João Reis; Luis Neto; Gil Gonçalves. Universal parser for wireless sensor networks in industrial cyber physical production systems. 2017 IEEE 15th International Conference on Industrial Informatics (INDIN) 2017, 633 -638.
AMA StyleRicardo Pinto da Silva, João Reis, Luis Neto, Gil Gonçalves. Universal parser for wireless sensor networks in industrial cyber physical production systems. 2017 IEEE 15th International Conference on Industrial Informatics (INDIN). 2017; ():633-638.
Chicago/Turabian StyleRicardo Pinto da Silva; João Reis; Luis Neto; Gil Gonçalves. 2017. "Universal parser for wireless sensor networks in industrial cyber physical production systems." 2017 IEEE 15th International Conference on Industrial Informatics (INDIN) , no. : 633-638.
Industrial Internet of Thing's will pave the way for Smart Manufacturing initiatives. Intelligence will be notices even in fine grained devices, resulting in complex but at the same time highly efficient manufacturing systems. The typical field worker job will be replaced by machines and human intervention will be shifted to supervision jobs. This work presents Sensor SelComp, a Smart Component which will act in the factory shop-floor, creating the so called digital twin's of machine's by means of sensors and exposing it's functionalities as services. This component is a building block of the SelSus project vision, whose aim is to create and highly effective self-healing production environment. This component eases the process of sensor integration and data analysis by offering runtime reconfiguration and data processing capabilities. Along this document it is shown that Sensor SelComp can cope with tight industrial functional requirements and it's functionalities are described in detail.
Luis Neto; Joao Reis; Ricardo Silva; Gil Goncalves. Sensor SelComp, a smart component for the industrial sensor cloud of the future. 2017 IEEE International Conference on Industrial Technology (ICIT) 2017, 1256 -1261.
AMA StyleLuis Neto, Joao Reis, Ricardo Silva, Gil Goncalves. Sensor SelComp, a smart component for the industrial sensor cloud of the future. 2017 IEEE International Conference on Industrial Technology (ICIT). 2017; ():1256-1261.
Chicago/Turabian StyleLuis Neto; Joao Reis; Ricardo Silva; Gil Goncalves. 2017. "Sensor SelComp, a smart component for the industrial sensor cloud of the future." 2017 IEEE International Conference on Industrial Technology (ICIT) , no. : 1256-1261.
Nowadays, in order to maintain their competitiveness, manufacturing companies must adapt their production methods quickly, with minimum expenditure, to frequent variations on demand. With the shortage of the product life time, flexibility, efficiency and reusability of industrial processes are important factors, which may determine the survival of the company. The ReBORN project is working around these ideas, namely studying how can an old production equipment be reused into new contexts. The ReBORN Workbench is a simulation tool for factory layout design, which generates solutions based on the production requirements and facilities' availability, corresponding Life Cycle Assessment, and associated location cost. This paper is concerned with the ReBORN Workbench module responsible to generate solutions for equipment location, generally know as Facility Layout Problems. A Genetic Algorithm was implemented to solve these problems, which aims to minimize the total material handling costs. The effectiveness of the proposed approach is evaluated with a numerical example and compared with other similar approaches. The results show that the proposed approach is indeed effective to solve problems regarding facilities layout.
Rui Pinto; Joana Goncalves; Henrique Lopes Cardoso; Eugenio Oliveira; Gil Goncalves; Bruno Carvalho. A Facility Layout Planner tool based on Genetic Algorithms. 2016 IEEE Symposium Series on Computational Intelligence (SSCI) 2016, 1 -8.
AMA StyleRui Pinto, Joana Goncalves, Henrique Lopes Cardoso, Eugenio Oliveira, Gil Goncalves, Bruno Carvalho. A Facility Layout Planner tool based on Genetic Algorithms. 2016 IEEE Symposium Series on Computational Intelligence (SSCI). 2016; ():1-8.
Chicago/Turabian StyleRui Pinto; Joana Goncalves; Henrique Lopes Cardoso; Eugenio Oliveira; Gil Goncalves; Bruno Carvalho. 2016. "A Facility Layout Planner tool based on Genetic Algorithms." 2016 IEEE Symposium Series on Computational Intelligence (SSCI) , no. : 1-8.
In modern days people search job opportunities or candidates mainly online, where several websites for this purpose already do exist (LinkedIn, Guru and Freelancer, to name a few). This task is especially difficult because of the large number of items to look for and the need for manual compatibility by human resources. What we propose in this paper is an architecture for recruitment matchmaking that considers the user and opportunity models (content-based filtering) and social interactions (collaborative filtering) to improve the quality of its recommendations. This solution is also able to generate adequate teams for a given job opportunity, based not only on the needed competences but also on the social compatibility between their members, both using user-generated content and automatic platform data. This article is the extended version of ICE-B’s Hyred - HYbrid Job REcommenDation System, which means that it includes updated information and new advances, especially in Chap. 5.
Bruno Coelho; Fernando Costa; Gil M. Gonçalves. ARM: Architecture for Recruitment Matchmaking. Programmieren für Ingenieure und Naturwissenschaftler 2016, 81 -99.
AMA StyleBruno Coelho, Fernando Costa, Gil M. Gonçalves. ARM: Architecture for Recruitment Matchmaking. Programmieren für Ingenieure und Naturwissenschaftler. 2016; ():81-99.
Chicago/Turabian StyleBruno Coelho; Fernando Costa; Gil M. Gonçalves. 2016. "ARM: Architecture for Recruitment Matchmaking." Programmieren für Ingenieure und Naturwissenschaftler , no. : 81-99.
Sensor data is extremely important to monitor machines at the shop-floor level and its environmental surrounding conditions for condition-based monitoring, machine diagnosis and process adaptation to new requirements. Based on the described scope, self-diagnostics and self-organizing capabilities are core functionalities of any Industrial Wireless Sensor Network (IWSN). In the present work, a simulated case study was developed with the main intent of validating techniques implemented for sensor data diagnosis of error detection and equipment failure. The scenarios explored try to mimic some common situations of a manufacturing environment when dealing with WSNs, where a piece of sensor equipment suddenly stops working or an unpredictable change in the environment leads to faulty data readings. This paper introduces Castalia and describes how it was used to simulate a direct application of an Optical Metrology System on an industrial Resistance Spot Welding process, which is composed of a camera and several luminosity sensors. More specifically, a sensor data validation module was proposed, implemented and used to extend Castalia functionalities.
Rui Pinto; Rosaldo J. F. Rossetti; Gil Gonçalves. Wireless Sensor Network Simulation for Fault Detection in Industrial Processes. Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications 2016, 333 -338.
AMA StyleRui Pinto, Rosaldo J. F. Rossetti, Gil Gonçalves. Wireless Sensor Network Simulation for Fault Detection in Industrial Processes. Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications. 2016; ():333-338.
Chicago/Turabian StyleRui Pinto; Rosaldo J. F. Rossetti; Gil Gonçalves. 2016. "Wireless Sensor Network Simulation for Fault Detection in Industrial Processes." Proceedings of the 6th International Conference on Simulation and Modeling Methodologies, Technologies and Applications , no. : 333-338.
Sensor networks that consist of a variety of sensor nodes, with capability for distributed storage and analysis, interoperable and delay-tolerant communication, will pave the way for a truly scalable network of sensors which will support adaptable plug-and-produce assembly stations. The concept of Sensor Cloud has emerged as the cornerstone for enabling the integration of nearly real time data sources into Service Oriented Architectures and as one of the enablers for Reconfigurable Manufacturing Systems. Hitherto there are still some challenges that need to be tackled, namely the on-the-fly instantiation and update of services at the system level and the dynamic (re)organization of the services created. This paper presents the first steps in the development of a framework (taking advantage of several technologies like UPnP, OSGi and iPOJO) to address these challenges and make Sensor Clouds a reality in the shop floor. The results from the first implementation reveal that the performance of the system is linear in terms of scalability, and from these scalability tests, we proved the framework's robustness and consistent responsiveness.
Luis Neto; João Reis; Diana Guimaraes; Gil Goncalves. Sensor cloud: SmartComponent framework for reconfigurable diagnostics in intelligent manufacturing environments. 2015 IEEE 13th International Conference on Industrial Informatics (INDIN) 2015, 1706 -1711.
AMA StyleLuis Neto, João Reis, Diana Guimaraes, Gil Goncalves. Sensor cloud: SmartComponent framework for reconfigurable diagnostics in intelligent manufacturing environments. 2015 IEEE 13th International Conference on Industrial Informatics (INDIN). 2015; ():1706-1711.
Chicago/Turabian StyleLuis Neto; João Reis; Diana Guimaraes; Gil Goncalves. 2015. "Sensor cloud: SmartComponent framework for reconfigurable diagnostics in intelligent manufacturing environments." 2015 IEEE 13th International Conference on Industrial Informatics (INDIN) , no. : 1706-1711.
Nowadays people search job opportunities or candidates mainly online, where several websites for this end already do exist (LinkedIn, Freelancer and oDesk, amongst others). This task is especially difficult because of the large number of items to look for and the need for manual compatibility verification. What we propose in this paper is a recruitment recommendation system that considers the user model (content-based filtering) and social interactions (collaborative filtering, e.g. likes and follows) to improve the quality of its suggestions. The devised solution is also able to generate adequate teams for a given job opportunity, based not only on the needed skills but also on the social compatibility between their members.
Bruno Coelho; Fernando Costa; Gil M. Gonçalves. HYRE-ME – Hybrid Architecture for Recommendation and Matchmaking in Employment. Communications in Computer and Information Science 2015, 208 -224.
AMA StyleBruno Coelho, Fernando Costa, Gil M. Gonçalves. HYRE-ME – Hybrid Architecture for Recommendation and Matchmaking in Employment. Communications in Computer and Information Science. 2015; ():208-224.
Chicago/Turabian StyleBruno Coelho; Fernando Costa; Gil M. Gonçalves. 2015. "HYRE-ME – Hybrid Architecture for Recommendation and Matchmaking in Employment." Communications in Computer and Information Science , no. : 208-224.
Nuno Rocha; Raquel Sousa; Gil Goncalves. Continuous Monitoring and Digital Systems for Elders. Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health 2015, 81 -86.
AMA StyleNuno Rocha, Raquel Sousa, Gil Goncalves. Continuous Monitoring and Digital Systems for Elders. Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health. 2015; ():81-86.
Chicago/Turabian StyleNuno Rocha; Raquel Sousa; Gil Goncalves. 2015. "Continuous Monitoring and Digital Systems for Elders." Proceedings of the 1st International Conference on Information and Communication Technologies for Ageing Well and e-Health , no. : 81-86.
Bruno Coelho; Fernando Costa; Gil M. Gonçalves. Hyred - HYbrid Job REcommenDation System. Proceedings of the 10th International Conference on Security and Cryptography 2015, 29 -38.
AMA StyleBruno Coelho, Fernando Costa, Gil M. Gonçalves. Hyred - HYbrid Job REcommenDation System. Proceedings of the 10th International Conference on Security and Cryptography. 2015; ():29-38.
Chicago/Turabian StyleBruno Coelho; Fernando Costa; Gil M. Gonçalves. 2015. "Hyred - HYbrid Job REcommenDation System." Proceedings of the 10th International Conference on Security and Cryptography , no. : 29-38.