Traceability is transversal to the various pillars of industry 4.0, as it provides essential information to plant operation management, and facilitates post-production audits. Recently, blockchain technology has been widely explored as a solution to enhance the immutability and transparency of industrial traceability systems, thereby increasing trust among stakeholders. However, most existing studies evaluate the performance of blockchain itself rather than its impact on the industrial system. In this work, we propose a discrete-event modeling and collaborative approach that can be adapted to any industrial production plant. Through a case study, we demonstrate how it can be used to analyze the impact of a recently proposed blockchain-based traceability solution in terms of various custom metrics, such as storage requirements, energy consumption and even environmental impact. The parameters used in the simulator for the blockchain component were obtained through a real implementation with Multichain. Moreover, it enables further evaluations by integrating additional factory data and parameters whose impact on blockchain deployment would otherwise require long and costly prototyping in a real implementation.

In recent decades, manufacturing system, particularly small and medium-sized enterprises (SMEs) have faced rising challenges due to increased demand for customization and shorter delivery times. To adapt, many firms rely on temporary workforce teams, yet determining optimal staffing remains complex due to budget limits, contractual constraints, and forecast uncertainties. Although Advanced Planning and Scheduling (APS) systems have long been proposed to address such issues, they often focus on complex mathematical models with limited practical implementation guidance. This work introduces a practical APS framework built around three modules. The first handles data structuring, analysis, and demand forecasting. The second focuses on production planning, combining a multi-objective lot-sizing optimization sub-module for aggregated planning and a discrete-event simulation sub-module for operational scheduling. A regulation heuristic corrects forecast deviations in real time. The third module offers decision support, assessing the impact of strategies on KPIs such as service level, inventory, and workforce use. The results from the case study demonstrate that the proposed system consistently achieves a 100

In this article, we propose a new formal language called the Formal Parallel-DEVS Modeling Language (FPDEVSML) as a platform-independent specification of the Parallel-DEVS (PDEVS) formalism. The DEVS (Discrete Event Systems Specification) formalism enables the specification of discrete event models in a hierarchical and modular manner, providing a solid foundation for the modeling, simulation, and analysis of discrete systems. FPDEVSML is based on a grammar with a rigorous mathematical structure that formalizes the sets and mathematical objects used in PDEVS modeling. The main objective of the proposed approach is to provide a formal framework for specifying and analyzing a system and to improve interoperability between PDEVS simulators. FPDEVSML can be used as an intermediate target language for DSLs. The specified models can then be translated into different forms of code using code generators and then executed with various tools for model verification and execution.

The fifth and beyond generations of communications (B5G/6G) aim to support massive connected objects and mission-critical applications. In the context of disaster management, the vehicles coordinating rescue operations in each area can also serve as local communication relays for the other participants. The evaluation of such applications at a city scale requires accurate modelling of both urban mobility and vehicular communications. Most works propose either analytical models providing a big picture of the performance expected in large-scale deployments, or real-world testing at a lower scale showing performance for concrete but limited scenarios. This paper proposes a simulation approach to the evaluation of 5G relay-empowered communications, which uses an event-based urban traffic modelling in order to accelerate large-scale simulations. It also uses propagation models designed from real-world measurements performed on mobile operators’ 5G infrastructure, which allows to envision the 5G communication performance that could be expected for applications such as cooperative localization and extended perception between the participating vehicles. The evaluations over a relay-empowered 5G network including one base station (gNB), 180 relays, and up to 350 vehicles in an urban city show that the relays improve downlink communications speed and end-to-end delay, while the gNB provides higher speeds in uplink communications overall. These evaluation results draw the performance expected from existing 5G deployments, and offer insight for communication management policy regarding the applications involved in rescue operations.

Among the strategies of the fifth and beyond generations of communications (B5G/6G) to manage massive connected objects and their increased experience requirements, using relays is gaining much interest. Particularly, the infrastructure supporting applications such as Rescue Operations can beneficially use relay-empowered approaches for efficient disaster management in a city. Several works propose analytical models providing a big picture of the performance expected in large scale deployments. Conversely, real-world testings at a lower scale show performance for more concrete but very limited scenarios. This paper proposes a simulation based approach to evaluation of such applications. It uses an event-based urban traffic modelling that accelerates large-scale simulation, even at the level of a city. It also uses propagation models designed from real-world measurements performed on mobile operator 5G infrastructure to obtain performance results close to reality. The evaluations over a relay-empowered 5G network including one base station, 180 relays and up to 350 vehicles in an urban city, show the gain on metrics such as end-to-end delay and communication speed when using relays.

In this work, we present a new approach based on a discrete event formalism to model and simulate micro-scale urban traffic systems. The formalism is a coupling between the P-DEVS (Parallel-Discrete Event System Specification) formalism and UML (Unified Modeling Language) state machines. A system is represented by a set of coupled components. Each component supports the dynamics and logic of a system element. The models presented include the streets, intersections and traffic signs, all of which can be synchronized together through specific mechanisms. These models can be applied to real-world OpenStreetMap networks. A discrete event-driven adaptation of the simplified Gipps car-following model is introduced, and subsequently compared to its discrete time counterpart. The results show that our discrete event model follows dynamics which are similar to those of a discrete time model with a low update time step of 0.1s, despite not taking certain non-linearities of the latter into account. In terms of vehicle state changes and computation time, our approach outperforms the discrete time one with an update time step of 1s, both on a simple case study and on a real network.

Industry 4.0 involves major changes in manufacturing process management. Both the Internet of Things and cloud computing allow online interactions between third parties, such as providers, customers and suppliers, with the traceability system of a factory. Several blockchain-based approaches have been proposed to increase confidence in traceability data and reinforce trust. However, the transparency brought may be at the cost of risks to factory's confidential data exposure. This paper investigates the way these critical data, which are necessary to post-assembly audit, could be included into traceability data, and validated through the related transactions by the third parties, without compromising their confidentiality. Accordingly, this proposal includes the description of a blockchain-based traceability system and its implementation using the Multichain platform. In addition to its confidentiality-preserving feature, we discuss the way energy consumption and storage volume induced could be managed so as to favor its effective adoption by manufacturing factories.

Industry 4.0 brings major changes in manufacturing process management. Third parties, such as providers, customers and suppliers are more prone to interact with the traceability system of a factory in order to obtain full transparency on a product manufacturing process. Several solutions, including blockchain-based approaches, have been proposed in order to reinforce trust in such systems. However, many factory owners are still sceptic about deploying such solutions, notably due to confidentiality threats to the factory’s data that could be included in traceability data. This paper investigates a way to include critical data of a factory in a blockchain-based traceability system, and to validate the related transactions with third parties without compromising confidentiality. We describe our proposal for a digital ledger based traceability system using the Multichain platform. In addition to confidentiality-preserving properties, we show how other issues such as energy consumption and storage volume could be controlled through Multichain functionalities.

Vehicular ad hoc network (VANET) routing protocols resort to clustering in order to optimize broadcast traffic flooding. Clustering schemes usually rely on rules which apply to each vehicle in order to reach a targeted organization in a VANET. Most of the literature works which evaluate clustering for VANET focus on performance analysis. However, with autonomous vehicles coming to roadways, more rigorous relationships will be required between clustering rules and the resulting organization, so as to anticipate road safety in a better way. We propose a formal description of the properties which are expected in a VANET, while considering the rules of a given clustering scheme. Using Event-B, we first present a description of the VANET, the vehicles movement and the traffic generated by both routing and application messages. Then, based on an Event-B model of a basic routing protocol of the literature, we describe how the specific rules of a clustering scheme can be modeled along with the properties expected in the resulting organization. Finally, we propose a validation process of the model. This paper aims at showing how our proposals have been applied to the Chain-Branch-Leaf scheme, although they can be adapted to any rule-based clustering scheme for VANET.

Industry 4.0 is a revolution in manufacturing by introducing disruptive technologies such as Internet of Things (IoT) and cloud-computing into the heart of the factory. The resulting increased automation and the improved production synergy between stocks, supply chains and customer demands, come along with the threats and attacks from the Internet. Despite extensive literature on the cybersecurity topic, many actors in manufacturing factories are just realizing the impact of cybersecurity in the preservation of their business. This paper introduces step-by-step the concepts and practical aspects of an Industry 4.0 manufacturing factory that are related to cybersecurity. Based on a subdivision of a typical factory into several generic perimeters, we present the vulnerabilities and threats regarding the network and devices usually found in each perimeter. Therefore, it is more efficient to present the recent proposals of the literature regarding cybersecurity guidelines and solutions in Industry 4.0. Instead of spreading a lot of references regarding every aspect of cybersecurity, we focused on a limited number of papers among the recent references. However, for each paper, we provide the details about the purpose of the proposal, the methodology adopted, the technical solution developed and its evaluation by the authors. These solutions range from classical cybersecurity countermeasures to innovative ones, such as those based on honeypots and digital twins. In order to deliver a review also useful to non scientists, we present our guidelines along with those of some organizations involved in cybersecurity harmonization and standardization in the world.

In agriculture, plant cultivation requires to take numerous decisions. One of the major problems is irrigation: an adequate irrigation decision must be made accordingly to the hydric status of the plant and soil, and the weather forecasts. In precision agronomy, this leads to the use of hydric sensors combined with a numerical growth plant model. Such models can not often be tuned by experts. We proposed an automatic parameter calibration of the potato growth model based on data collected in several open fields. As these parameter calibration problems are ill-posed, the associated black-box optimization problem is supposed to be multi-modal. We then compare the performances of two state-of-the-art Evolution Strategies which use different restart mechanisms to automatically tune the set of parameters on different crops and shows that multi-modal optimization methods may be recommended for such class of optimization problems.

Since the 2004 and 2005 airport reforms in France, the air transport market has been undergoing major changes. Low cost airlines have become key players in competition with traditional airlines. For their part, local authorities, which now manage decentralized airports, must adopt the best strategies to develop and/or sustain their infrastructures. Based on a multi-agent computer simulation using the theory of spatial and evolutionary games, we analyze the effects for the different actors (airport managers, airlines and by extension the territories) of the implementation of cooperative strategies (main objective of the airport reform) for regional and decentralized airports. While this simulation shows that cooperation between regional and local airports is unlikely, it underlines that cooperation between airports of the same category (local/local, regional/regional) increases their resilience. In this perspective, it could be in the interest of local authorities to promote this type of strategy. The simulation shows, however, that the counterpart of cooperation is a lower average gain for the airports that have chosen to coalesce. Also, the recent transfer of some regional airports as well as the delegation of many local airports to the private sector could go against the stated objective of the reform.

Evolution of Intelligent Transportation Systems (ITS) towards connected and autonomous vehicles requires robust communication protocols with proven or at least verified properties. In a recent work, we pointed out the advantages and limitations of both formal and simulation approaches when they are used separately during the design and evaluation processes of communication protocols dedicated to ITS. Our goal is to develop new tools combining formal methods such as Event-B with simulation formalism such as DEVS (Discrete Event System Specification) for proving and verifying the properties of ITS components models in large-scale scenarios. Previously, we presented the simulation models of a Vehicular Ad hoc Network (VANET) in a DEVS-based environment, where the Optimized Link State Routing (OLSR) protocol was used with a recently proposed clustering scheme, namely Chain-Branch-Leaf (CBL). Pursuing our objectives, this paper presents an equivalent model realized with Rodin, a formal tool based on a variant of the B method: Event-B. It shows how the specific properties of CBL clustering scheme are introduced in an Event-B model of OLSR from the literature, and how the numerous resulting proof obligations are discharged using the B prover in Rodin.

Protocol design is usually based on the functional models developed according to the needs of the system. In Intelligent Transport Systems (ITS), the features studied regarding Vehicular Ad hoc Networks (VANET) include self-organizing, routing, reliability, quality of service, and security. Simulation studies on ITS-dedicated routing protocols usually focus on their performance in specific scenarios. However, the evolution of transportation systems towards autonomous vehicles requires robust protocols with proven or at least guaranteed properties. Though formal approaches provide powerful tools for system design, they cannot be used for every types of ITS components. Our goal is to develop new tools combining formal tools such as Event-B with DEVS-based (Discrete Event System Specification) virtual laboratories in order to design the models of ITS components which simulation would allow proving and verifying their properties in large-scale scenarios. This paper presents the models of the different components of a VANET realized with the Virtual Laboratory Environment (VLE). We point out the component models fitting to formal modeling, and proceed to the validation of all designed models through a simulation scenario based on real-world road traffic data.