Reconfigurable Manufacturing Systems (RMS) provide a flexible and responsive manufacturing environment to face changing market demands, increasing product complexity, and technological advancements. Implementing them remains challenging due to the wideness and complexity of the domain. There miss methods and tools to make RMS applicable to industry and especially Small and Medium Entreprises with non-expert users. This article contributes to practionner’s design toolbox by providing software language solution to define RMS and evaluate their performance. It is illustrated on an academic fictive production line.

Reconfigurable Manufacturing Systems (RMS) have emerged as a flexible and cost-effective solution to meet dynamic production requirements. Built on the principle of modularity, RMS allow for rapid reconfiguration of both hardware and software components, enabling swift adaptation to market changes, evolving product designs, or system disturbances. While the design of reconfigurable systems has been extensively studied, the challenge of selecting the optimal configuration during a system’s lifecycle—known as configuration selection—remains a complex and underexplored topic. The modular nature of RMS leads to a combinatorial explosion of possible configurations, fostering a large panel of possible evaluation methods. This paper focuses on current research efforts addressing configuration selection, highlighting the dominant role of combinatorial optimization approaches in literature. We critically examine their limitations, particularly in terms of human involvement and system uncertainty. Through a simulation-based example, we highlight the need for more integrated and operator-centric methods. Finally, we propose future research directions to support more effective and adaptive reconfiguration strategies.

Performance management of manufacturing systems requires applicable methodologies to be implemented in practice. Both the literature and the experiments we led in this paper show the need of a precise methodological tool to support the setting-up of dashboards. In a previous work, we proposed a KPI meta-model framework as a means to implement KPI computations in practice. In this article we go one step further and focus on the methodological aspects of this framework to build performance dashboards using the DMAIC (Define, Measure/Analyse, Improve/Control) method from 6 sigma. Starting from strategic objectives, we drive KPI trees until measure means to collect performance feedback. The methodology has been evaluated by an experimentation with students on the Lampex learning factory from Strasbourg University.

Business-IT Alignment (BITA) is an important mean of evaluating the performance of IT systems operating within a business organisation. In this context, it remains challenging for software architects to represent, analyse and interpret the alignment situations, before trying to fix potential misalignments. Despite different initiatives in the last two decades, current solutions are too diverse and limited, making their generalisation difficult, if not impossible. We consider that more methodological guidelines are still needed to improve the support for BITA. In this chapter, we address practical tracks for Core Operational BITA (COBITA), a subset of BITA which targets the operational integration of business and application artefacts. To this end, we first propose a general framework, in the line of Enterprise Architecture, to establish a cartography of the as-is state: business and application layer modelling and linking. We then propose to evaluate the alignment state using different evaluation means (metrics, consistency rules, anti-patterns). The objective is to provide indicators for domain experts and software architects to assess the quality of the alignment between the two layers. The practical aspects include principles, techniques and tooling: a partial version of the approach has been implemented in the Archi tool and experimented on the SoftSlate Open-Source Java Ecommerce Solution.

Reconfigurable Manufacturing Systems (RMS) have emerged as a promising approach to address the dynamic demands and uncertainties in modern manufacturing. However, the lack of a comprehensive and universally accepted definition of the notion of configuration in RMS poses challenges for researchers and practitioners. This research article aims to bridge this gap by suggesting a core reference model for RMS, allowing to exhibit a generic modelling of configurations. The article critically examines existing definitions and approaches to configuration, providing a comprehensive overview of the different dimensions and components of configuration in RMS. By addressing the lack of a consistent understanding of configuration in RMS, this article contributes to the development of a shared knowledge base and paves the way for further advancements in the field. It also highlights the importance of establishing a clear and holistic definition of configuration for effective implementation and utilisation of RMS in practice.

In terms of competitiveness, Business-IT Alignment (BITA) is still a crucial challenge for business leaders and CIOs, especially in the context of Digital Transformation and time-to-market challenges. Core Operational BITA is a projection of BITA to the Enterprise Information System perimeter, i.e., the operational alignment between the business processes and supporting IT. It is a major source of issues (e.g., strong couplings, maintenance costs, technical debt, slow adaptation). These issues cause a misalignment and thus contribute to the well-known Business-IT Gap. In this paper, we review the current state of this operational alignment in the context of Enterprise Architecture (EA) i.e. between the Business Process layer and the Application layer. Our analysis focuses on five facets: modelling notations used at the Business Process and Application layers, existence of explicit and implicit links between these layers, potential of these links in terms of alignment or misalignment in the information system, tooling and support. As a result, we notably outline some current limitations, such as modelling disparities, misuse of links between the two layers and an under-coverage of real alignment processes. We also discuss some lessons learned and future challenges, mainly around modelling needs and consistency management between the two considered layers for core operational BITA.

Security code smells are receiving increasing attention in the domain of Android app development. They serve as coding guidelines aimed at identifying vulnerabilities originating from the application's source code. Numerous related tools have been proposed to align with DevSecOps guidelines. However, they lack of comparable effort in creating benchmarks for open-source apps, making the thorough evaluation of these tools challenging, and requiring time-consuming manual effort. In this paper, we propose Privbench, an evolving benchmark that captures vulnerabilities related to the Android ecosystem. It incorporates multiple code patterns for each vulnerability. To showcase its significance, we used it to evaluate two well-known tools used to identify Android security code smells. This evaluation focused on Privilege Escalation (PE) vulnerabilities and we present their performance in detecting the vulnerabilities within their scopes. We believe that our benchmark can be useful for advancing the capabilities of state-of-the-art tools, enhancing their effectiveness in vulnerability detection, and increasing developers awareness to evade privilege escalation vulnerabilities.

Model driven engineering aims to shorten the development cycle by focusing on abstractions and partially automating code generation. We long lived in the myth of automatic Model Driven Development (MDD) with promising approaches, techniques, and tools. Describing models should be a main concern in software development as well as model verification and model transformation to get running applications from high level models. We revisit the subject of MDD through the prism of experimentation and open mindness. In this article, we explore assistance for the stepwise transition from the model to the code to reduce the time between the analysis model and implementation. The current state of practice requires methods and tools. We provide a general process and detailed transformation specifications where reverse-engineering may play its part. We advocate a model transformation approach in which transformations remain simple, the complexity lies in the process of transformation that is adaptable and configurable. We demonstrate the usefulness, and scalability of our proposed MDD process by conducting experiments. We conduct experiments within a simple case study in software automation systems. It is both representative and scalable. The models are written in UML; the transformations are implemented mainly using ATL, and the programs are deployed on Android and Lego EV3. Last we report the lessons learned from experimentation for future community work.

Key Performance Indicators (KPIs) and their implementation are crucial for the continuous improvement of manufacturing systems (MSs). In this article, we develop a KPI framework as a means to implement KPI computations in a convenient way. The idea is to go beyond the simple, standard definition of the KPIs by linking them explicitly with their instrumentation, that it to say the data required to calculate them. To do so, we present a set of metamodels: a KPI metamodel, a KPI-capture metamodel and a KPI-instrumentation metamodel. These are defined independently from any MS implementation, but are generic enough to be implemented in various Manufacturing Execution Systems. The use of the framework is illustrated on the Lampex learning factory from Strasbourg University.

Plasma diagnostics is a key tool to support the further development of plasma-induced chemical conversion of greenhouse gases (such as CO 2 ) into high-value chemicals. For this reason, spectroscopic and electric measurements of low current (below 1.7 A), stationary arc plasmas in CO 2 at atmospheric pressure with addition of N 2 or H 2 O are reported. High-speed photography, imaging emission spectroscopy and time-resolved electrical measurements are used to obtain time-space resolved gas temperatures as well as the electric-field current characteristics of the discharge. It is found that the lowest average electric field in a CO 2 arc plasma at atmospheric pressure is ∼20 kV mm −1 at a current between 0.8 and 1 A. If the current decreases below this level, the arc remains in vibrational–translational (VT) equilibrium by increasing the electric field. However, VT equilibrium conditions can be only maintained until a threshold minimum current of 0.33 ± 0.05 A, at which the arc transitions into a non-equilibrium condition with further increasing electric fields (reaching 68 ± 15 V mm −1 at 0.03 A). The addition of N 2 or H 2 O did not influence the electrical characteristics of the CO 2 arc within to the tested mixtures. However, there is only a significant decrease in the electric field of the formed transition arcs and the threshold minimum current in the presence of N 2 . The spectra of the low-current CO 2 arc is found to be dominated by emission from the C 2 Swan band system and the O I 777 nm triplet peak. However, the CN band dominates the spectra even when small amounts (0.5 wt%) of N 2 is present in the plasma. The gas temperature at the axis of the CO 2 arc plasma decreased slightly with decreasing current, from an estimated 7000 K at 1 A down to 6300 K at 0.4 A. The thermal radius of the arc is estimated to be larger than 1.2 mm, more than two times larger than the optical radius obtained from the emitted radiation. The addition of N 2 and H 2 O (up to 7 and 9 wt% respectively) lead to only to a 500 K decrease in the axial arc temperature.

Various works propose solutions addressing the sustainability of IoT technologies to reduce their energy consumption, especially in the domain of wireless sensor networks. The diversity of applications, as well as the variability of their long-term constraints, forces them to dynamically adapt the network through time. Accordingly, this study formalizes the SADHoA-WSN framework to tackle the reconfiguration process. This proposal is a dynamic Holonic Control Architecture, linking the physical network evolution to the decisions made by a virtual multi-agent control system. The potential of such an approach is demonstrated by applying this framework to the energy optimization of communicating materials, i.e., materials equipped with inner wireless sensor nodes. The first implemented components of SADHoA-WSN and their related experimental results validate it as a promising energy-efficient dynamic methodology. This work lays the groundwork for optimized energy control in IoT networks.

In the dynamic Android application security landscape, traditional vulnerability assessment faces challenges posed by the increasing complexity of execution environments. These environments encompass a diverse array of contextual factors that influence application behavior, highlighting the imperative for adaptive testing. Current security analysis techniques for Android apps often struggle to capture the intricate interplay between static and dynamic contexts, impeding precise vulnerability detection. This constraint becomes more evident as execution environments diversify. To address these limitations, this paper introduces DroidSecTester, a novel toolchain for testing Android application security by focusing on context-driven vulnerability modeling. Our innovation lies in developing three Domain Specific Languages (DSLs): Context Definition Language (CDL), Context-Driven Modelling Language (CDML), and Vulnerability Pattern (VPat) for Model-Based Security Testing (MBST). Collectively, these DSLs provide a framework for security assessment by embracing both static and dynamic contexts intrinsic to smartphone environments. Our work resulted in VPatChecker, a tool designed to identify vulnerabilities and generate abstract exploits. Merging application and context models with a vulnerability pattern library - dynamic and expandable to accommodate new Common Vulnerability and Exposure (CVE) entries - the tool offers limitless extensibility. We evaluated the tool on the GHERA benchmark and found that at least 38% of the vulnerabilities in the benchmark can be modelled and detected. This work underscores the pivotal role of context in Android security testing and presents a solution for vulnerability identification through the integration of MBST and DSLs.

During the last twenty years, many innovative control architectures of manufacturing systems have been developed and promoted in literature. One of the main attributes, in correlation with the aims of Industry 4.0 paradigm, is to define control architectures where both the actors and the interactions between these actors could cope with an evolution of the environment. To do so, dynamic architectures are being recently developed, where the hierarchy of decision can be jeopardized at any time during the normal behaviour of the system. However, the deployment of such architectures faces major software development issues, that a proper initial modelling could help solving. The objective of this paper is to exhibit good practices in the modelling of dynamic architectures in order to enable an automatic reconfiguration when needed.

In terms of competitiveness, Business-IT Alignment (BITA) is still a crucial challenge for busi- ness leaders and CIOs, especially in the context of Digital Transformation and time-to-market challenges. Core Operational BITA can be seen as a projection of BITA to the Enterprise In- formation System perimeter, i.e., the operational alignment between the business processes and supporting IT. It is a major source of issues (e.g., strong couplings, maintenance costs, tech- nical debt, slow adaptation). These cause a misalignment and thus contribute to the well-known Business-IT Gap. In this paper, we review the current state of this operational alignment in the context of Enterprise Architecture (EA) i.e. between the Business Process layer and the Applic- ation layer. Our analysis focuses on the models used at the Business Process and Application layers, the existing or potential links between these layers, and the use of these links to carry out a core operational alignment and facilitate the detection of potential divergence points. As a res- ult, we notably outline some current limitations, such as modelling disparities, misuse of links between the two layers and an under-coverage of real alignment processes. We also discuss some lessons learned and future challenges, mainly around modelling needs and consistency management between the two considered layers.

Privilege Escalation (PE) attacks are common security issues in Android ecosystem. They typically involve the exploitation of vulnerabilities to gain unauthorized access to sensitive data. Preventing their related vulnerabilities is complex and hard to be understood and mitigated by developers. In a previous research, we performed an empirical study to investigate the effectiveness of existing IDE plugins in detecting known Android related vulnerabilities. We found that most of PE vulnerabilities are not covered by these IDE plugins. In order to assist developers to evade these issues, we present in this paper PrivDroid, an up to date and available IDE plugin for secure Android development. The tool combines static analysis techniques on the Android project source files to identify security code smells related to PE. Finally, PrivDroid is tested against more than 200 real Android applications and demonstrates that it gives additional capabilities to prevent Privilege Escalation related vulnerabilities.

Transport coefficients in non-equilibrium argon-hydrogen thermal plasmas, where the kinetic temperature of electrons Te is different from that of heavy species Th , are calculated at atmospheric pressure from a recent theoretical approach of Rat et al. The latter consists in deriving transport properties in thermal plasmas from the solution of the Boltzmann's equation according to the Chapman-Enskog method keeping the coupling between electrons and heavy species. Plasma composition is obtained from a non-equilibrium constant method and a stationary kinetic calculation. First, electrical and translational thermal conductivities are compared with those evaluated with the simplified theory of transport properties of Devoto and Bonnefoi. Non-negligible discrepancies occur reaching more than 30 and 40 % respectively for the electrical and electron thermal conductivities at Te = 15000 ? for θ = 2. Second, the dependence with Te of electrical and total thermal conductivities (including translational, internal and reactional contributions) and viscosity is examined as a function of the method of calculation of plasma composition and the non-equilibrium parameter θ = Te /Th . It is emphasized that non-equilibrium transport coefficients are strongly dependent on the method of plasma composition.