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366 results on '"Faccio, Maurizio"'

8. Dynamic Task Allocation for Collaborative Robot Systems

Author

Granata, Irene, Faccio, Maurizio, Maretto, Leonardo, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Galizia, Francesco Gabriele, editor, and Bortolini, Marco, editor

Published
2023
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9. Models for the Cost-Benefit Analysis of Digitalization and Industry 4.0: A Systematic Literature Review

Author

Maretto, Leonardo, Faccio, Maurizio, Battini, Daria, Granata, Irene, Chaari, Fakher, Series Editor, Gherardini, Francesco, Series Editor, Ivanov, Vitalii, Series Editor, Haddar, Mohamed, Series Editor, Cavas-Martínez, Francisco, Editorial Board Member, di Mare, Francesca, Editorial Board Member, Kwon, Young W., Editorial Board Member, Trojanowska, Justyna, Editorial Board Member, Xu, Jinyang, Editorial Board Member, Galizia, Francesco Gabriele, editor, and Bortolini, Marco, editor

Published
2023
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20. Novel design, implementation, and performance optimization of inverters by considering the effect of modulation.

Author

Nedaei, Mojtaba, Faccio, Maurizio, Walsh, Philip R, Rasul, Mohammad G, and Alain Bordas, Stéphane Pierre

Subjects
ELECTRIC metal-cutting, SUSTAINABILITY, PAYBACK periods, INDUSTRIAL efficiency, DISTRIBUTION (Probability theory)
Abstract

This research seeks to combine a comprehensive analysis of the literature regarding energy efficiency and inverters with an analysis of a configuration of a hybrid energy system including a generator, an inverter and a battery. The inverter's power output is analyzed under the influence of different distribution functions during a robust modulation procedure for achieving optimum energy saving. The modulation is tested on two processing machines independently: (a) an electric discharge machine, and (b) an injection molding machine. Based on the research methodology, problem formulations and the conducted analysis, a novel research software called "Inverter Pro V1" was programmed to analyze the estimations and performance of inverters in an energy system. An optimal levelized cost of electricity was determined given certain systems design and operating hours, and a sensitivity analysis was undertaken that identified a range of energy savings. In the sensitivity and optimization analysis, interactions among the primary decision parameters including the system's capacity, operating time, energy saving, cost of energy and payback period are investigated. It is also found that for each system, the inverter modulation categories with the optimum payback period belong to a modulation of inverter designed according to the Sawtooth function with a 45% duty cycle and switching intervals of 0.35 s. By considering the operating hours of 12.5 h per day, and the calculated system's investment cost of €31,782.158, the optimum payback period is estimated to be 1.7729 year. The study results are to inform policy with regard to assisting sustainable electricity production. [ABSTRACT FROM AUTHOR]

Published
2024
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21. Control Model for Collaborative Manufacturing: An Integrated Opened Framework for Human-Robot Collaboration

Author

Boschetti, Giovanni, Faccio, Maurizio, Minto, Riccardo, Ceccarelli, Marco, Series Editor, Hernandez, Alfonso, Editorial Board Member, Huang, Tian, Editorial Board Member, Takeda, Yukio, Editorial Board Member, Corves, Burkhard, Editorial Board Member, Agrawal, Sunil, Editorial Board Member, Niola, Vincenzo, editor, and Gasparetto, Alessandro, editor

Published
2021
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50. Deploying cobots in collaborative systems: major considerations and productivity analysis.

Author

Cohen, Yuval, Shoval, Shraga, Faccio, Maurizio, and Minto, Riccardo

Subjects
SHARED workspaces, INDUSTRY 4.0, HUMAN-robot interaction, ASSEMBLY line methods, ROBOTS, ASSEMBLY line balancing
Abstract

Collaborative robots (cobots) are important components of the Industry 4.0 paradigm and smart manufacturing. Cobots are known for their ability to interact with the operators in a shared workspace. Due to their spread in the last decade, cobot research proliferated. However, most individual studies focused on specific aspects of cobot deployment, and only scant attention was given to their evaluation (mostly not based on productivity criteria). Thus, better support is needed for cobot acquisition and deployment decisions. This paper answers this need by presenting a summary of the major considerations related to cobots acquisition and deployment, and providing a productivity analysis procedure that supports cobot acquisition and deployment decisions. Defining the cobots' required characteristics and capabilities, effectively narrows the possible selection of cobots. However, it does not give information as to the economic value of acquiring and deploying a specific cobot. So, in addition to cobots' characteristics and capabilities, this paper presents computational techniques to analyse and support this decision for a single workstation per se, and for a station in an assembly line. The difference between these two cases is discussed and analysed, and corresponding models are presented with computational examples. [ABSTRACT FROM AUTHOR]

Published
2022
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