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Mr. Duarte Alemão
UNINOVA

Basic Info


Research Keywords & Expertise

0 Distributed Systems
0 Smart Manufacturing
0 production scheduling
0 Industrial AI
0 Cyber-Physical Production Systems

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Short Biography

Duarte Alemão is currently a PhD student at the Nova University of Lisbon focusing on production scheduling optimization and is a researcher at the UNINOVA institute. He received his MSc (2017) in Electrical and Computer Engineering from the Nova University of Lisbon in Genetic Algorithms applied to task allocation. As a researcher, he is interested in topics such as robotics and integrated manufacturing, smart manufacturing and cyber-physical production systems, and has been involved in national and international projects such as H2020 PERFoRM, H2020 GO0DMAN, H2020 AVANGARD, and CESME.

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Project

Project Goal: The AVANGARD project addresses the integration of three novel processing units into an existing Microfactory test bed conceived to produce urban electric vehicles, namely robotized integration of laser cutting-shaping-welding for 3D components, Supersonic deposition of metallic powders for high speed 3D printing, and Large volume and high-speed 3D polymeric printing. The operation of the AVANGARD pilot will be demonstrated manufacturing I-Bikes, I-CARS and innovative battery packs.

Starting Date:15 October 2019

Current Stage: On going

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Project

Project Goal: The main overall objective of the CESME project is to design and develop an ecosystem capable to deal with Systems of Cyber-Physical Systems (CPS) for manufacturing.

Starting Date:01 September 2018

Current Stage: On going

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Project

Project Goal: The project aims the development of Zero-Defect Manufacturing (ZDM) strategies in multi-stage production systems, through the integration of quality control and process control using cyber-physical systems, intelligent inspection systems and advanced data analysis tools.

Starting Date:01 October 2016

Current Stage: Concluded

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Project

Project Goal: The project targeted the need for increasing flexibility and reconfigurability in the manufacturing domain, by developing new modular and distributed automation solutions.

Starting Date:01 October 2015

Current Stage: Concluded

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Journal article
Published: 17 June 2021 in Energies
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Industrial environments are heterogeneous systems that create challenges of interoperability limiting the development of systems capable of working collaboratively from the point of view of machines and software. Additionally, environmental issues related to manufacturing systems have emerged during the last decades, related to sustainability problems faced in the world. Thus, the proposed work aims to present an interoperable solution based on events to reduce the complexity of integration, while creating energetic profiles for the machines to allow the optimization of their energy consumption. A publish/subscribe-based architecture is proposed, where the instantiation is based on Apache Kafka. The proposed solution was implemented in two robotic cells in the automotive industry, constituted by different hardware, which allowed testing the integration of different components. The energy consumption data was then sent to a Postgres database where a graphical interface allowed the operator to monitor the performance of each cell regarding energy consumption. The results are promising due to the system’s ability to integrate tools from different vendors and different technologies. Furthermore, it allows the possibility to use these developments to deliver more sustainable systems using more advanced solutions, such as production scheduling, to reduce energy consumption.

ACS Style

Andre Rocha; Nelson Freitas; Duarte Alemão; Magno Guedes; Renato Martins; José Barata. Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring. Energies 2021, 14, 3620 .

AMA Style

Andre Rocha, Nelson Freitas, Duarte Alemão, Magno Guedes, Renato Martins, José Barata. Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring. Energies. 2021; 14 (12):3620.

Chicago/Turabian Style

Andre Rocha; Nelson Freitas; Duarte Alemão; Magno Guedes; Renato Martins; José Barata. 2021. "Event-Driven Interoperable Manufacturing Ecosystem for Energy Consumption Monitoring." Energies 14, no. 12: 3620.

Review
Published: 02 March 2021 in Applied Sciences
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The recent advances in technology and the demand for highly customized products have been forcing manufacturing companies to adapt and develop new solutions in order to become more dynamic and flexible to face the changing markets. Manufacturing scheduling plays a core role in this adaptation since it is crucial to ensure that all operations and processes are running on time in the factory. However, to develop robust scheduling solutions it is necessary to consider different requirements from the shopfloor, but it is not clear which constraints should be analyzed and most research studies end up considering very few of them. In this review article, several papers published in recent years were analyzed to understand how many and which requirements they consider when developing scheduling solutions for manufacturing systems. It is possible to understand that the majority of them are not able to be adapted to real systems since some core constraints are not even considered. Consequently, it is important to consider how manufacturing scheduling solutions can be structured to be adapted effortlessly for different manufacturing scenarios.

ACS Style

Duarte Alemão; André Rocha; José Barata. Smart Manufacturing Scheduling Approaches—Systematic Review and Future Directions. Applied Sciences 2021, 11, 2186 .

AMA Style

Duarte Alemão, André Rocha, José Barata. Smart Manufacturing Scheduling Approaches—Systematic Review and Future Directions. Applied Sciences. 2021; 11 (5):2186.

Chicago/Turabian Style

Duarte Alemão; André Rocha; José Barata. 2021. "Smart Manufacturing Scheduling Approaches—Systematic Review and Future Directions." Applied Sciences 11, no. 5: 2186.

Conference paper
Published: 01 July 2019 in 2019 IEEE 17th International Conference on Industrial Informatics (INDIN)
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In the last years the utilization of Multiagent Systems to implement distributed control systems in industrial environments was presented as suitable and as a cost-effective solution to deal with the new requirements regarding flexibility and dynamism on the shop-floor. However, the proposed implementation of these distributed Cyber-Physical Production Systems faced some challenges regarding hardware and network requirements. Hence, the proposed work presents one utilization of a Multiagent-based distributed control system running on the fog level and running upon the edge level. This research presents a test and assessment of running intelligent agents outside the edge level but at the same time avoid the deployment of the industrial agents on the cloud level due to time and performance constraints. The proposed test presents a Multiagent architecture responsible for controlling the shop-floor, but the overall architecture was designed to accommodate the agents on the fog level, running upon the edge level composed by industrial controllers running Device Profile Web Services.

ACS Style

Andre Dionisio Rocha; Joao Tripa; Duarte Alemao; Ricardo Peres; Jose Barata. Agent-based Plug and Produce Cyber-Physical Production System – Test Case. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 2019, 1, 1545 -1551.

AMA Style

Andre Dionisio Rocha, Joao Tripa, Duarte Alemao, Ricardo Peres, Jose Barata. Agent-based Plug and Produce Cyber-Physical Production System – Test Case. 2019 IEEE 17th International Conference on Industrial Informatics (INDIN). 2019; 1 ():1545-1551.

Chicago/Turabian Style

Andre Dionisio Rocha; Joao Tripa; Duarte Alemao; Ricardo Peres; Jose Barata. 2019. "Agent-based Plug and Produce Cyber-Physical Production System – Test Case." 2019 IEEE 17th International Conference on Industrial Informatics (INDIN) 1, no. : 1545-1551.

Conference paper
Published: 16 April 2019 in Lecture Notes in Control and Information Sciences
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The production scheduling has attracted a lot of researchers for many years, however most of the approaches are not targeted to deal with real manufacturing environments, and those that are, are very particular for the case study. It is crucial to consider important features related with the factories, such as products and machines characteristics and unexpected disturbances, but also information such as when the parts arrive to the factory and when should be delivered. So, the purpose of this paper is to identify some important characteristics that have been considered independently in a lot of studies and that should be considered together to develop a generic scheduling framework to be used in a real manufacturing environment.

ACS Style

Duarte Alemão; André Dionísio Rocha; Jose Barata. Production Scheduling Requirements to Smart Manufacturing. Lecture Notes in Control and Information Sciences 2019, 227 -237.

AMA Style

Duarte Alemão, André Dionísio Rocha, Jose Barata. Production Scheduling Requirements to Smart Manufacturing. Lecture Notes in Control and Information Sciences. 2019; ():227-237.

Chicago/Turabian Style

Duarte Alemão; André Dionísio Rocha; Jose Barata. 2019. "Production Scheduling Requirements to Smart Manufacturing." Lecture Notes in Control and Information Sciences , no. : 227-237.

Conference paper
Published: 31 December 2018 in Security Education and Critical Infrastructures
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The market demand has changed in recent years due to increased interest in more customized and diversified products by the consumers, leading to a change in production lines, which are becoming more flexible and dynamic. At the same time, the amount of data available in the factories is growing more and more, thereby the number of errors in the production schedule may occur often. Several approaches have been used over time to plan and schedule the shop-floor production. However, some only consider static environments, where the tasks are allocated to the machines, not considering that machines may not be available and sometimes maintenance interventions are needed. The introduction of maintenance increases the scheduling complexity and makes it harder to allocate the tasks efficiently. So, new solutions have been proposed, giving manufacturing systems the ability to quickly adapt to some disturbances that may occur. Thus, Artificial Intelligence approaches have been adopted to do the task allocation for the shop-floor. Those approaches can find suitable solutions faster than traditional approaches. This article proposes an architecture, based on Genetic Algorithm, capable of generating schedules including both production and maintenance tasks.

ACS Style

Duarte Alemão; Mafalda Parreira-Rocha; José Barata. Production and Maintenance Scheduling Supported by Genetic Algorithms. Security Education and Critical Infrastructures 2018, 49 -59.

AMA Style

Duarte Alemão, Mafalda Parreira-Rocha, José Barata. Production and Maintenance Scheduling Supported by Genetic Algorithms. Security Education and Critical Infrastructures. 2018; ():49-59.

Chicago/Turabian Style

Duarte Alemão; Mafalda Parreira-Rocha; José Barata. 2018. "Production and Maintenance Scheduling Supported by Genetic Algorithms." Security Education and Critical Infrastructures , no. : 49-59.