Prof. Alberto Vergnano
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Academic Career Length
18Years (2009-Present)
(Calculated once Scilit publication data is synced: current year − year of first publication + 1)
Representative Publications
View All Publications1 April 2013 in Mechatronics
Journal Article
MPMarcello Pellicciari
Marcello Pellicciari
Giovanni BerselliFLF. Leali
F. LealiAlberto Vergnano27 January 2012 in IEEE Transactions on Automation Science and Engineering
Journal Article
Alberto VergnanoCTCarl Thorstensson
Carl Thorstensson
BLBengt Lennartson
Bengt Lennartson
PFPetter Falkman
Petter Falkman
MPMarcello Pellicciari
Marcello PellicciariSBStephan Biller
Stephan Biller +1
Reduction of energy consumption is important for reaching a sustainable future. This paper presents a novel method for optimizing the energy consumption of robotic manufacturing systems. The method embeds detailed evaluations of robots' energy consumptions into a scheduling model of the overall system. The energy consumption for each operation is modeled and parameterized as function of the operation execution time, and the energy-optimal schedule is derived by solving a mixed-integer nonlinear programming problem. The objective function for the optimization problem is then the total energy consumption for the overall system. A case study of a sample robotic manufacturing system and an experiment on an industrial robot are presented. They show that there exists a real possibility for a significant reduction of the energy consumption in comparison to state-of-the-art scheduling approaches.
23 May 2012 in IEEE Transactions on Automation Science and Engineering
Journal Article
OWOskar Wigstrom
Oskar Wigstrom
BLBengt Lennartson
Bengt Lennartson
Alberto VergnanoCBClaes Breitholtz
Claes Breitholtz
The reduction of energy consumption is today addressed with great effort in manufacturing industry. In this paper, we improve upon a previously presented method for robotic system scheduling. By applying dynamic programming to existing trajectories, we generate new energy optimal trajectories that follow the same path but in a different execution time frame. With this new method, it is possible to solve the optimization problem for a range of execution times for the individual operations, based on one simulation only. The minimum energy trajectories can then be used to derive a globally energy optimal schedule. A case study of a cell comprised of four six-link manipulators is presented, in which energy optimal dynamic time scaling is compared to linear time scaling. The results show that a significant decrease in energy consumption can be achieved for any given cycle time.
12 June 2014 in The International Journal of Advanced Manufacturing Technology
Journal Article
FLFrancesco Leali
Francesco LealiAlberto Vergnano
Fabio PiniMPMarcello Pellicciari
Marcello PellicciariGiovanni Berselli1 December 2011 in International Journal on Interactive Design and Manufacturing (IJIDeM)
Journal Article
AAAngelo O. Andrisano
Angelo O. AndrisanoFLFrancesco Leali
Francesco LealiMPMarcello Pellicciari
Marcello PellicciariFabio PiniAlberto Vergnano11 January 2017 in International Journal on Interactive Design and Manufacturing (IJIDeM)
Journal Article
Alberto VergnanoGiovanni BerselliMPMarcello Pellicciari
Marcello PellicciariAbout Me
Alberto Vergnano is Associate Professor in the Academic Discipline ING-IND/15 Design Methods for Industrial Engineering for the Enzo Ferrari Department of Engineering of the University of Modena and Reggio Emilia (UNIMORE). He got PhD in High Mechanics and Automotive Design and Technology in 2010 at UNIMORE defending the thesis “Integrated Design Methods for Intelligent Mechanical Systems”. He teaches courses on Industrial Technical Drawing, Fundamentals of Design and CAD, Design Methods, seminars and training on Design for Manufacturing and Assembly, Energy Saving for industrial robots, Virtual Prototyping, Design of Foundry Equipment. He is Faculty Advisor in the Unimore Learning By Doing project for the Formula Student MMR Driverless Team. His research interests in the IDEA (Integrated Design and Engineering Application) Laboratory are actuations and for autonomous driving, methods for simulation of foundry equipment, design methods based on multiphysics simulations, human intelligent system integration, Advanced Driver Assistance Systems.