A5036512005- Digital Transformation in Industry
- Fault Detection and Control Systems
- VLSI and Analog Circuit Testing
- Flexible and Reconfigurable Manufacturing Systems
- Radiation Effects in Electronics
- Anomaly Detection Techniques and Applications
- Manufacturing Process and Optimization
- Industrial Vision Systems and Defect Detection
- Real-time simulation and control systems
- Integrated Circuits and Semiconductor Failure Analysis
- Software Reliability and Analysis Research
- Low-power high-performance VLSI design
- Time Series Analysis and Forecasting
- Machine Fault Diagnosis Techniques
- Electrostatic Discharge in Electronics
- VLSI and FPGA Design Techniques
- Advancements in Semiconductor Devices and Circuit Design
- Smart Grid Security and Resilience
- Embedded Systems Design Techniques
- Advanced Chemical Sensor Technologies
- Simulation Techniques and Applications
- Plant Diversity and Evolution
- Advanced Machining and Optimization Techniques
- Robotics and Sensor-Based Localization
- Semiconductor materials and devices
University of Verona
2018-2025
IRD Fuel Cells (Denmark)
2024
Predictive maintenance in a manufacturing company is strategic, order to maintain high production quality and avoid unexpected downtimes. In this scenario, the prediction of future machineries health status necessary plan cycles optimize production. The proposed approach relies on use Electronic Design Automation (EDA) techniques mapped from electronic domain line domain. This paper proposes general framework based EDA that allows set-up strategy by analyzing data retrieved sensors. An MSM,...
Since the last century, exponential growth of semiconductor industry has led to creation tiny and complex integrated circuits, e.g., sensors, actuators, smart power. Innovative techniques are needed ensure correct functionality analog devices that ubiquitous in every system. The ISO 26262 standard for functional safety automotive context specifies fault injection is necessary validate all electronic devices. For decades, standardization defect modeling mainly focused on digital circuits and,...
Predictive maintenance is a strategic activity in the context of Industry 4.0 order to maintain certain level quality production and avoid unexpected equipment downtimes. In this scenario, analysis IIOT data necessary achieve prediction on future machinery' status. The proposed approach relies use Electronic Design Automation (EDA) techniques mapped from electronic domain line domain. These EDA are combined with field knowledge, especially for Maintenance analysis. This presentation...
Over the last decade, industrial world has been involved in a massive revolution guided by adoption of digital technologies. In this context, complex systems like cyber-physical play fundamental role since they were designed and realized composing heterogeneous components. The combined simulation behavioral models these components allows to reproduce nominal behavior real system. Similarly, smart system is device that integrates but miniaturized form factor. development or systems,...
In the context of Industry 4.0, it is strategic to build a simulable model an Industrial Cyber-Physical System (CPS) ensure proper maintenance and early risk assessment avoid monetary losses. To achieve this, necessary use dedicated techniques for modeling injecting faults into simulative model. However, generally too complex due heterogeneous components, e.g., analog digital parts. Verilog-AMS suitable solution overcome this problem since allows covering different physical descriptions,...
Customizing computer vision applications for embedded systems is a common and widespread problem in the cyber-physical community. Such customization means parametrizing algorithm by considering external environment mapping Software application to heterogeneous Hardware resources satisfying non-functional constraints like performance, power, energy consumption. This work presents framework design simulation of that integrates OpenVX standard platform with Robot Operating System (ROS). The...
There are several languages for modeling a Cyber-Physical System (CPS). One of them is Verilog-AMS, which allows representing system belonging to the electrical and mechanical physical domains in single model through different disciplines. A framework automatic fault injection proposed this context. In particular, starting from system, it possible represent as an circuit by exploiting analogies. domain, techniques more advanced than other domains. Extending analogies models makes apply...
In modern industrial contexts, a factory becomes complex and heterogeneous ecosystem, where many technologies, systems, workers cooperate. Such class of systems is named Cyber-Physical Production Systems (CPPSs), since their design requires to merge control, network, physical aspects. such context, it fundamental guarantee safe human-machine interactions. Therefore, evaluating adopting techniques necessary ensure functional safety. This article analyzes the challenges creating digital twins...
Analog Hardware Description Languages (AHDLs) provide a valuable alternative to existing proprietary means of implementing defect models and generic templates. modeling in SPICE engines event-driven digital simulators is discussed, with review the state-of-the-art, an analysis possibilities, proposals for future enhancements tools standards meet challenges achieving good coverage estimations at system level. Moreover, we discuss possibilities using EDACurry open-source framework instrument...
The Industry 4.0 paradigm has deeply changed classical manufacturing by introducing data-based analytics and decision-support strategies. At the state of art, data used for monitoring is mostly originated sensors, that undergo a fusion step to align different sources. However, this only relative monitored process, it does not include corresponding operating conditions parameters, are known Manufacturing Execution System (MES). Such information currently either included or labeled hand, thus...
Detecting complex anomalies on massive amounts of data is a crucial task in Industry 4.0, best addressed by deep learning. However, available solutions are computationally demanding, requiring cloud architectures prone to latency and bandwidth issues. This work presents VARADE, novel solution implementing light autoregressive framework based variational inference, which suited for real-time execution the edge. The proposed approach was validated robotic arm, part pilot production line,...
With functional safety being increasingly important in the development of mixed-signal products for automotive applications, EDA solutions have appeared striving to help designers setup and execution fault injection campaigns. Despite ongoing work standardize definition defect models coverage calculation methods IEEE P2427 draft standard, there is a lack unified portable method define templates that can be used inject systematic way defects an analog circuit. Each existing tool sets proposes...
Constructing a holistic digital twin of system composed multiple physical domains is crucial for various tasks. In particular, when the simulation extended with faults, it becomes very important resource to achieve robust functional safety analysis. This article proposes new methodology build non-electrical fault models thermal domain. Such faults are defined through an electrical circuit representing behavior system, known as Cauer network, based on analogies between two domains. Including...
Industry 4.0 involves the integration of digital technologies, such as IoT, Big Data, and AI, into manufacturing industrial processes to increase efficiency productivity. As these technologies become more interconnected interdependent, systems complex, which brings difficulty identifying stopping anomalies that may cause disturbances in process. This paper aims propose a diffusion-based model for real-time anomaly prediction processes. Using neuro-symbolic approach, we integrate ontologies...
In this paper, we present the project "VIR2EM: VIrtualization and Remotization for Resilient Efficient Manufacturing" by providing details on its research themes scientific technological output. The project, centered virtualization remotization in industrial sector, was promoted Regione Veneto Italy, it has seen participation collaboration of 3 universities, 1 public entity, 10 companies composed end users digital solutions high knowledge-intensive service providers. aims to develop use...
The early detection of anomalous behaviors from a production line is fundamental aspect Industry 4.0, facilitated by the collection massive amounts data enabled Industrial Internet Things. Nonetheless, design and validation anomaly algorithms, mostly based on sophisticated Machine Learning models, heavily rely availability annotated datasets realistic anomalies, which very difficult to obtain in real line. To address this problem, we introduce Robotic Arm Dataset (RoAD), specifically...
In this article, a predictive fault grouping based on the collection of faulty AC matrices at fault-free operating points is presented as means to approximate final distribution faults in equivalence classes using minimal computational effort. The method computationally cheap because it avoids performing DC or transient simulations with injected and limits itself only activated. technique provides an approximation, since does not characterize corresponding point but instead looks how they...
Constructing a simulable model of production line is crucial to ensure adequate maintenance, but it nonetheless too complex due the presence highly heterogeneous components. In this perspective, Verilog-AMS promising solution, as allows cover different levels details, from transistor-level and digital components multi-physical dynamics. This paper shows how can be used by exploiting multiple disciplines effectively. Furthermore, we will prove that efficient modeling faults inserting...