Antonella Petrillo

By Fabio De Felice, Antonella Petrillo and Stanislao Monfreda

Part of the book: Operations Management

By Fabio De Felice, Antonella Petrillo and Domenico Falcone

One of the most critical issues related to safety in industrial plant is to manage accidents that occur in industries. In general, the causes of accidents are twofold: the presence of dangerous equipment and human errors. The aim of this study is to propose a novel approach to ensure safety in emergency conditions in industrial plant considering both of these factors. The proposed idea aims to integrate the human reliability analysis (HRA) and the failure modes and effects analysis (FMEA). The human errors and failure modes are categorized using a multicriteria approach based on analytic hierarchy process (AHP). The final aim is to present a novel methodological approach based on AHP to prioritize actions to carry out in emergency conditions taking into account both qualitative and quantitative factors. A real case study is analyzed. The analysis allowed to identify possible failure modes connected with human error process.

Part of the book: Applications and Theory of Analytic Hierarchy Process

By Marco Frascio, Francesca Mandolfino, Federico Zomparelli and Antonella Petrillo

Hospitals play a critical role in providing communities with essential medical care during all types of disasters. Any accident that damages systems or people often requires a multifunctional response and recovery effort. Without an appropriate emergency planning, it is impossible to provide good care during a critical event. In fact, during a disaster condition, the same “critical” severity could occur for patients. Thus, it is essential to categorize and to prioritize patients with the aim to provide the best care to as many patients as possible with the available resources. Triage assesses the severity of patients to give an order of medical visit. The purpose of the present research is to develop a hybrid algorithm, called triage algorithm for emergency management (TAEM). The goal is twofold: First, to assess the priority of treatment; second, to assess in which hospital it is preferable to conduct patients. The triage models proposed in the literature are qualitative. The proposed algorithm aims to cover this gap. The model presented exceeds the limits of literature by developing a quantitative algorithm, which performs a numerical index. The hybrid model is implemented in a real scenario concerning the accident management in a petrochemical plant.

Part of the book: Theory and Application on Cognitive Factors and Risk Management

By Domenico Falcone, Fabio De Felice, Antonella Petrillo and Alessandro Silvestri

Serious incidents that occur inside or caused by industrial plants represent a very critical issue. In this context, the human reliability analysis (HRA) is an important tool to assess human factors that influence human behaviour in disasters scenario. In fact, the reliability assessment of interaction between human-machine systems is an important factor that affects the overall performance and safety in industrial plants. However, even though HRA techniques have been available for decades, there is not a universal method/procedure to reduce human errors that affect human performance. This study aims to design a novel approach to investigate the relationship between human reliability and operator performance considering the dependence on the available time to make decisions.

Part of the book: Theory and Application on Cognitive Factors and Risk Management

By Antonella Petrillo, Fabio De Felice, Raffaele Cioffi and Federico Zomparelli

The globalization and the competitiveness are forcing companies to rethink and to innovate their production processes following the so-called Industry 4.0 paradigm. It represents the integration of tools already used in the past (big data, cloud, robot, 3D printing, simulation, etc.) that are now connected into a global network by transmitting digital data. The implementation of this new paradigm represents a huge change for companies, which are faced with big investments. In order to benefit from the opportunities offered by the smart revolution, companies must have the prerequisites needed to withstand changes generated by “smart” system. In addition, new workers who face the world of work 4.0 must have new skills in automation, digitization, and information technology, without forgetting soft skills. This chapter aims to present the main good practices, challenges, and opportunities related to Industry 4.0 paradigm.

Part of the book: Digital Transformation in Smart Manufacturing

By Antonella Petrillo, Salvatore Mellino, Fabio De Felice and Iolanda Scudo

Transport is one of the economic sectors within the European Union with the most detrimental effects on climate change. In this context, electric bicycles (e-bikes) are considered as a potentially effective technological innovation to reduce carbon impacts. The present research aims to propose a life cycle assessment study to quantify which components of a bicycle have the highest environmental impact. The use in Italy of two different bicycles, an electric pedal-assisted bike and a hydrogen-fuel cell-operated one, is analyzed. The final aim of the study is to quantify and to evaluate the bike’s energetic and environmental performances, focusing the analysis on the vehicle production and use phases. To achieve the abovementioned purpose, two approaches, the “from cradle to grave” approach and “well to wheel” approach, are considered.

Part of the book: New Frontiers on Life Cycle Assessment

By Antonella Petrillo, Fabio De Felice and Laura Petrillo

Complex industrial plants are characterized by digitalization and innovation. In this context it is strategic to ensure the systematic design, implementation, and continuous improvement of all processes (operations management). One of the most obvious ways to improve operations performance is to reduce the risk of accidents and human errors. In this pilot study the Functional Resonance Analysis Method (FRAM) is proposed to analyze the complexity of safety in industrial plants. This research integrates FRAM with Analytic Hierarchy Process (AHP), a multi criteria technique, to overcome the limits of the FRAM. The result is a proposal of an alternative approach to risk assessment based on principles of resilience engineering. A real case study in a petrochemical company is analyzed.

Part of the book: Operations Management

By Fabio De Felice and Antonella Petrillo

Digitalization and sustainability are the drivers of the global development of the future that have slowly conquered the agendas of governments and organizations on every continent. In this context, the pandemic has proved to be a powerful technological accelerator, helping to give a greater boost to these drivers, “guiding” leading the productive and economic sector throughout the world. Today the sustainability and digitalization represent the indispensable prerequisites to add economic, environmental, and social sovereignty. In fact, the scenario that the Coronavirus is leaving us foreshadows the need not to be satisfied with reaching targets for reducing greenhouse gas emissions, but to imagine “global” governance for the development of business models based on the new digital frontiers. Thus, what are the challenges for achieving the paradigms of sustainability and digitization in this new era? And what are the tools for a “digicircular” transformation? The aim of this chapter is to investigate these issues. To this end, it should be noted that, in this chapter, our aim is not to present an analysis of literature in the classical sense but rather political and social reflections.

Part of the book: Product Life Cycle

By Fabio De Felice, Aniello Ferraro and Antonella Petrillo

Digital Twin technology is increasingly recognized as a strategic enabler of Industry 4.0, combining efficiency, resilience, and sustainability. By replicating physical assets and processes in dynamic digital environments, Digital Twins enable real-time monitoring, predictive maintenance, and energy optimization. This chapter provides a scenario-based analysis on digital twin. Evidence from existing implementations shows measurable sustainability outcomes: energy savings of 15–30%, CO₂ emission reductions up to 25%, and maintenance cost decreases between 20 and 30%. These benefits are most evident in energy-intensive and complex industries, where Digital Twins have already demonstrated tangible impacts on operational performance and ecological transition. At the same time, barriers such as high initial costs, lack of standardization, and cybersecurity risks remain critical challenges. The chapter emphasizes the role of Digital Twins not only as technological tools but as catalysts of systemic transformation toward greener, more resilient industrial and urban models.

Part of the book: Performance Analysis in Engineering

By Mizna Rehman, Antonella Petrillo, Antonio Forcina and Fabio De Felice

This study introduces the PILAR framework (Physical Integration, Intermodal Transport, Logic & Control, Adaptive Service, Responsive Interface), a multi-layered logistics architecture grounded in the Physical Internet (PI) to enhance multimodal supply chains through decentralized, data-driven coordination. The framework integrates agent-based modeling (ABM), IoT-enabled π-containers, autonomous π-movers, and intelligent π-nodes within a Geographic Information System (GIS)-based simulation environment that models both forward and reverse coffee logistics flows. Using Q-learning, Monte Carlo analysis, and mixed-integer linear programming (MILP), the system dynamically optimizes routing, disruption recovery, and Pareto-efficient decision-making. Quantitative outcomes—derived from 10,000 Monte Carlo simulation runs calibrated with empirical transport data and optimization parameters—show a 30% reduction in logistics costs through improved routing and vehicle utilization, and a 50% improvement in spent coffee grounds (SCG) recovery efficiency enabled by IoT-based collection and decentralized processing hubs. The model further incorporates kanban-based flow control, stochastic demand forecasting, and adaptive energy-aware scheduling. Its technical implementation leverages RESTful APIs, TLS-encrypted MQTT communication, and edge computing for secure, real-time coordination. Results confirm the PILAR model’s ability to achieve high asset utilization (82.4%), lower CO₂ emissions by up to 25%, and enable scalable, resilient logistics systems aligned with circular economy goals.

Part of the book: Sustainable Development Annual Volume 2025