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MICHELE GADALETA

TITOLARE DI BORSA DI STUDIO
Dipartimento di Ingegneria "Enzo Ferrari"


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Pubblicazioni

2020 - Extensive experimental investigation for the optimization of the energy consumption of a high payload industrial robot with open research dataset [Articolo su rivista]
Gadaleta, M.; Berselli, G.; Pellicciari, M.; Grassia, F.
abstract

The optimization of the energy consumption of Industrial Robots (IRs) has been widely investigated. Unfortunately, on the field, the prediction and optimization strategies of IRs energy consumption still lack robustness and accuracy, due to the elevated number of parameters involved and their sensitivity to environmental working conditions. The purpose of this paper is to present, and share with the research community, an extensive experimental campaign that can be useful to validate virtual prototypes computing the energy consumption of robotic cells. The test cell, comprising a high payload IR equipped with multiple sensors and different payloads, is firstly described. The testing procedures are then presented. Experimental results are analyzed providing novel qualitative and quantitative evaluations on the contribution and relevance of different power losses and system operating conditions, clearly depicting the nonlinear relation between the energy consumption and various freely programmable parameters, thus paving the way to optimization strategies. Finally, all the experimental tests data are provided in the form of an open research dataset, along with custom Matlab scripts for plotting graphs and maps presented in this paper. These tests, which are verifiable via the shared dataset, consider the overall measured IR energy consumption (as drawn from the electric network) and highlight that, in some industrially interesting case scenarios, optimization potentials for energy savings of more than 50% are possible.


2019 - A comparative study on computer-integrated set-ups to design human-centred manufacturing systems [Articolo su rivista]
Peruzzini, Margherita; Pellicciari, Marcello; Gadaleta, Michele
abstract

Manufacturing ergonomics refers to the application of ergonomic principles and human factors analysis to the design of manufacturing tasks with the final aim to optimize the workers’ wellbeing and guarantee the expected process performance. Traditional design approaches are based on the observation of individual workers performing their jobs, the detection of unnatural postures (e.g., bending, twisting, overextending, rotating), and the definition of late corrective actions according to ergonomic guidelines. Recently, computer-integrated simulations based on virtual prototypes and digital human models (DHMs) can be used to assess manufacturing ergonomics on virtual manikins operating in digital workplaces. Such simulations allow validating different design alternatives and optimizing the workstation design before the creation, and pave the way to a new approach to manufacturing system design. The present paper aims at comparing different computer-integrated set-ups to support the design of human-centred manufacturing workstations. It defines a protocol analysis to support workstation design by analysing both physical and cognitive aspects, and applies the protocol within different digital set-ups. In particular, the study investigates a 2D desktop set-up using standardized DHMs and a 3D immersive mixed reality set-up based on motion capture of real workers’ acting into a mixed environment, comparing them with the traditional approach. An industrial case study focusing on design optimization of a manufacturing workstation in the energy industry is used to test the effectiveness of the two digital set-ups for the definition of re-design actions.


2019 - Optimization of the energy consumption of industrial robots for automatic code generation [Articolo su rivista]
Gadaleta, M.; Pellicciari, M.; Berselli, G.
abstract

At present, energy consumption strongly affects the financial payback period of industrial robots, as well as the related manufacturing process sustainability. Henceforth, during both design and manufacturing management stages, it becomes crucial to assess and optimize the overall energy efficiency of a robotic cell by means of digital manufacturing tools. In practice, robotic plant designers and managers should be able to provide accurate decisions also aimed at the energy optimization of the robotic processes. The strong scientific and industrial relevance of the topic has led to the development of many solutions but, unfortunately, state of the art industrial manipulators are equipped with closed controllers, which heavily limit the feasibility and performance of most of the proposed approaches. In light of the aforementioned considerations, the present paper presents a novel simulation tool, seamlessly interfaced with current robot offline programming tools used in industrial practices, which allows to automatically compute energy-optimal motion parameters, thus reducing the robot energy consumption, while also keeping the same productivity and manufacturing quality. The main advantage of this method, as compared to other optimization routines that are not conceived for direct integration with commercial industrial manipulators, is that the computed parameters are the same ones settable in the robot control codes, so that the results can automatically generate ready-to-use energy-optimal robot code. Experimental tests, performed on a KUKA Quantec KR210 R2700 prime industrial robot, have confirmed the effectiveness of the method and engineering tool.


2017 - A Simulation Tool for Computing Energy Optimal Motion Parameters of Industrial Robots [Articolo su rivista]
Gadaleta, Michele; Berselli, Giovanni; Pellicciari, Marcello; Sposato, Mario
abstract

This paper presents a novel robot simulation tool, fully interfaced with a common Robot Offline Programming software (i.e. Delmia Robotics), which allows to automatically compute energy-optimal motion parameters, for a given end-effector path, by tuning the joint speed/acceleration during point-to-point motions whenever allowed by the manufacturing constraints. The main advantage of this method, as compared to other optimization routines that are not conceived for a seamless integration with commercial industrial manipulators, is that the computed parameters are the same required by the robot controls, so that the results can generate ready-to-use energy-optimal robot code.


2017 - Analysis of the Energy Consumption of a Novel DC Power Supplied Industrial Robot [Articolo su rivista]
Grebers, R.; Gadaleta, M.; Paugurs, A.; Senfelds, A.; Avotins, A.; Pellicciari, M.
abstract

The energy consumption and electrical characteristics of a novel direct current (DC) power supplied industrial robot prototype are compared and analyzed with a state of the art alternating current (AC) supplied industrial robot. An extensive set of experiments shows an important reduction of the total energy consumption for different electrical power profiles measured in various robot trajectories with specific working temperatures. The recuperated energy is also analyzed in the different scenarios. Experimental results show that a DC type robot can be up to 12.5% more energy-efficient than an equivalent AC type robot.


2017 - Energy-optimal layout design of robotic work cells: Potential assessment on an industrial case study [Articolo su rivista]
Gadaleta, Michele; Berselli, Giovanni; Pellicciari, Marcello
abstract

This paper presents a new method for optimizing the layout position of several Industrial Robots (IRs) placed within manufacturing work-cells, in order to execute a set of specified tasks with the minimum energy consumption. At first, a mechatronic model of an anthropomorphous IR is developed, by leveraging on the Modelica/Dymola built-in capabilities. The IR sub-system components (namely mechanical structure, actuators, power electronic and control logics) are modeled with the level of detail strictly necessary for an accurate prediction of the system power consumption, while assuring efficient computational efforts. Secondly, once each IR task is assigned, the optimal work-cell layout is computed by using proper optimization techniques, which numerically retrieve the IR base position corresponding to the minimum energy consumption. As an output to this second development stage, a set of color/contour maps is provided, that depicts both energy demand and time required for the task completion as function of the robot position in the cell to support the designer in the development of an energy-efficient layout. At last, two robotic manufacturing work-cells are set-up within the Delmia Robotics environment, in order to provide a benchmark case study for the evaluation of any energy saving potential. Numerical results confirm possible savings up to 20% with respect to state-of-the-art work-cell design practice.


2017 - Engineering methods and tools enabling reconfigurable and adaptive robotic deburring [Capitolo/Saggio]
Berselli, Giovanni; Gadaleta, Michele; Genovesi, Andrea; Pellicciari, Marcello; Peruzzini, Margherita; Razzoli, Roberto
abstract

According to recent researches, it is desirable to extend Industrial Robots (IR) applicability to strategic fields such as heavy and/or fine deburring of customized parts with complex geometry. In fact, from a conceptual point of view, anthropomorphic manipulators could effectively provide an excellent alternative to dedicated machine tools (lathes, milling machines, etc.), by being both flexible (due to their lay-out) and cost efficient (20-50% cost reduction as compared to traditional CNC machining). Nonetheless, in order to successfully enable highquality Robotic Deburring (RD), it is necessary to overcome the intrinsic robot limitations (e.g. reduced structural stiffness, backlash, time-consuming process planning/optimization) by means of suitable design strategies and additional engineering tools. Within this context, the purpose of this paper is to present recent advances in design methods and software platforms for RD effective exploitation. Focusing on offline methods for robot programming, two novel approaches are described. On one hand, practical design guidelines (devised via a DOE method) for optimal IR positioning within the robotic workcell are presented. Secondly, a virtual prototyping technique for simulating a class of passively compliant spindles is introduced, which allows for the offline tuning of the RD process parameters (e.g. feed rate and tool compliance). Both approaches are applied in the design of a robotic workcell for high-accuracy deburring of aerospace turbine blades.


2017 - Virtual Prototyping of a Flexure-based RCC Device for Automated Assembly [Articolo su rivista]
Vaschieri, V.; Gadaleta, M.; Bilancia, P.; Berselli, G.; Razzoli, R.
abstract

The actual use of Industrial Robots (IR) for assembly systems requires the exertion of suitable strategies allowing to overcome shortcomings about IR poor precision and repeatability. In this paper, the practical issues that emerge during common “peg-in-hole” assembly procedures are discussed. In particular, the use of passive Remote Center of Compliance (RCC) devices, capable of compensating the IR non-optimal performance in terms of repeatability, is investigated. The focus of the paper is the design and simulation of a flexure-based RCC that allows the prevention of jamming, due to possible positioning inaccuracies during peg insertion. The proposed RCC architecture comprises a set of flexural hinges, whose behavior is simulated via a CAE tool that provides built-in functions for modelling the motion of compliant members. For given friction coefficients of the contact surfaces, these numerical simulations allow to determine the maximum lateral and angular misalignments effectively manageable by the RCC device.


2016 - A signal based approach for condition monitoring and predictive maintenance of a capsule filler machine [Relazione in Atti di Convegno]
Cormio, Mauro; Costantino, Antonio; Gadaleta, Michele; Pellicciari, Marcello
abstract

The need to increase manufacturing systems productivity and reduce their downtimes has led researchers to investigate and develop Predictive Maintenance practices. One of the major challenges to cope with Predictive Maintenance is related with the health assessment and analytics (i.e.: diagnostic and prognostic methods): the identification of the incoming faults is difficult and hard to deploy in complex automated machinery operating in real life conditions. At state of the art, established approaches are based on locating specific sensors as near as possible to the potential failure. However, such approach is expensive and often hard to realize due to machine topologies. The present work deals with a fault detection signal based approach, which analyses the vibrations of a complete pharmaceutical capsule filler machine and detects the signature of a fault on a critical stage to build a pattern threshold for Predictive Maintenance. The main novelty and strength of the proposed engineering method is that the detection can be achieved despite the sensor position and in presence of many sources, as it is in real life industrial environments. An industrial case study, on a pharmaceutical capsule filler is presented


2016 - Energy-optimal motions for Servo-Systems: A comparison of spline interpolants and performance indexes using a CAD-based approach [Articolo su rivista]
Berselli, Giovanni; Balugani, Federico; Pellicciari, Marcello; Gadaleta, Michele
abstract

Position-controlled Servo-Systems (SeSs) may be envisaged as a key technology to keep the manufacturing industry at the leading edge. Unfortunately, based on the current state-of-the-art, these mechatronic devices are well performing but intrinsically energy intensive, thus compromising the overall system sustainability. Therefore, traditional design and optimization paradigms, previously focused on productivity and quality improvement, should be critically reviewed so as to introduce energy efficiency as an optimality criterion alongside with the global production rate. In particular, focusing on mono-actuator systems with one degree-of-freedom, among the several design factors that can influence the SeS overall performance, the end-effector motion law can be easily modified without either hardware substitution or further investments. In this context, the purpose of the present paper is twofold. On one side, an effective method for the quick set-up of an energy-predictive CAD-based virtual prototype is discussed. In parallel, an energy comparison of some commonly employed Point-To-Point motions and optimization cost functions is provided. For what concerns the trajectory interpolation scheme, a standard optimization problem based on the aforementioned virtual model is solved by means of either algebraic or trigonometric splines. For what concerns the optimality criterion, either the system energy consumption or the root-means square value of the actuator torque are taken into account. In general, torque-based approaches, which may be preferred since they do not require a full knowledge of the SeS electrical parameters, can be effectively employed only when friction effects are negligible as compared to purely inertial loads. In parallel, cubic algebraic splines outperform other types of trajectories, although losing continuity of the resulting jerk profile.


2015 - Increasing Position Accuracy and Energy Efficiency of Servo-Actuated Mechanisms [Relazione in Atti di Convegno]
Pellicciari, Marcello; Berselli, Giovanni; Balugani, Federico; Gadaleta, Michele
abstract

This paper quantitatively reports about a practical method to improve both position accuracy and energy efficiency of Servo-Actuated Mechanisms (SAMs) for automated machinery. The method, which is readily applicable on existing systems, is based on the ”smart programming” of the actuator trajectory, which is optimized in order to lower the electric energy consumption, whenever possible, and to improve position accuracy along those portions of the motion law which are process relevant. Both energy demand and tracking precision are computed by means of a virtual prototype of the system. The optimization problem is tackled via a traditional SequentialQuadratic-Programming algorithm, that varies the position of a series of virtual points subsequently interpolated by means of cubic splines. The optimal trajectory is then implemented on a physical prototype for validation purposes. Experimental data confirm the practical viability of the proposed methodology.


2015 - Towards Energy-Optimal Layout Design of Robotic Work Cells [Relazione in Atti di Convegno]
Gadaleta, Michele; Pellicciari, Marcello; Andrisano, Angelo Oreste
abstract

This paper presents a new method for optimizing the layout position of an Industrial Robot (IR) in order to execute a specified task with the minimum energy consumption. First, using the Modelica language, an IR mechatronic model is developed, focusing on computational efficiency: addressing the power flow from the electrical network, the sub-system components are modeled with the level of detail strictly necessary for an accurate prediction of the power consumption, while assuring efficient computational efforts. Once a robot task is assigned, the optimal layout IR position is calculated using optimization techniques that retrieve the robot base position corresponding to the minimum energy consumption. Additionally, the designer can optimize the overall robotic work cell with the aid of a set of colour/contour maps that depict the energy demand along with the time required for the task completion. Development, simulation and optimization phases are performed in Dymola environment.