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International audience; The advent of complex Cyber-Physical Systems (CPSs) creates the need for more efficient engineering processes. Recently, DevOps promoted the idea of considering a closer continuous integration between system development (including its design) and operational deployment. Despite their use being still currently limited, Artificial Intelligence (AI) techniques are suitable candidates for improving such system engineering activities (cf. AIOps). In this context, AIDOaRT is a large European collaborative project that aims at providing AI-augmented automation capabilities to better support the modelling, coding, testing, monitoring, and continuous development of CPSs. The project proposes to combine Model Driven Engineering principles and techniques with AI-enhanced methods and tools for engineering more trustable CPSs. The resulting framework will 1) enable the dynamic observation and analysis of system data collected at both runtime and design time and 2) provide dedicated AI-augmented solutions that will then be validated in concrete industrial cases. This paper describes the main research objectives and underlying paradigms of the AIDOaRt project. It also introduces the conceptual architecture and proposed approach of the AIDOaRt overall solution. Finally, it reports on the actual project practices and discusses the current results and future plans.

International audience; Our societies are regularly exposed to crisis situations due to natural or industrial disasters. Crisis management teams are involved to overcome these events by taking operational, tactic or strategic decisions. Any strategic decision must take account of various complexity factors e.g. spatial aspects, media or time pressure. The strategic decision is also constraint by human factors particularly those due to unprepared actor’s reaction when facing intensity and rarity of the crisis. The territory concerned by the crisis highlights different resources, means and issues more or less strictly dependent. Decision makers have also to deal with uncertain, complex, missing or ambiguous information. So it seems important to prepare them as much as possible by training exercises. The systemic approach gives the possibility to model the crisis and so to give a tool for trainers. In this article the case of an industrial crisis will be modeled, first by defining the crisis environment system and then its evolution. All of the sub-systems of this environment will be analyzed by identifying their interactions, their internal and external logics, their goals and their missions. This case will be used to highlight a method to determine the consequences of a decision during a training session.

The growing interest in Multi-Energy Systems (MES) leads the scientific community to implement innovative technologies to analyse and simulate these complex systems. Two main research trends are identified in such analysis: i) improve the usability and capability of preexisting reference architectures in the energy field to cope with high-level use case descriptions, and ii) study the interoperability of such reference architectures in order to increase systematic and functional analysis of MES use cases. GAMES is a a general-purpose architectural model for MES engineering application. The aim is twofold: i) GAMES implements an extension of Smart Grid Architecture Model (SGAM) to cope with MES use case descriptions, and ii) it offers a methodology to deal with a systemic description of the use case through a combination of UML and SysML integrated in the proposed architectural model. Furthermore, GAMES will allow the implementation of Domain Specific Language (DSL) and hardware configuration for the specific components described by UML/SysML diagrams. Compared to other solutions, GAMES allows to assess both research trends in a single hierarchical ICT infrastructure.

Errors made during the requirements collection and analysis phase make it very difficult to maintain the software product and cost the company extra costs. The difficulty of directly collecting requirements from stakeholders is due to inconsistencies between the major stakeholder groups, as well as related factors in the collection of requirements itself, as well as the selected methodology for the process of converting stakeholder requirements into development requirements. As a solution, it is necessary to use a high level of prioritization in order to distinguish among many requirements the necessary for successful implementation of the product, as well as to correctly allocate compliance with the requirements in such a way that each group of stakeholders is satisfied, but at the same time setting the goals of the supersystem more priority than the goals of the subsystem. This article discusses the methodology of system engineering to solve issues related to the identification of possible contradictions of requirements. Keywords: System engineering, requirements engineering, business process, requirements, software product, analysis.

The processing of personal data is becoming a key business factor, especially for high-tech system industries such as automotive and healthcare service providers. To protect such data, the European Union (EU) has introduced the General Data Protection Regulation (GDPR), with the aim to standardize and strengthen data protection policies across EU countries. The GDPR defines stringent requirements on the collection and processing of personal data and imposes severe fines and penalties on data controllers and processors for non-compliance. Although the GDPR is enforce since 2018, many public and private organizations are still struggling to fully comply with the regulation. A main reason for this is the lack of usable methodologies that can support developers in designing of GDPR-complaint high-tech systems. This paper examines the growing literature on methodologies for the design of privacy-aware systems, and identifies the main challenges to be addressed in order to facilitate developers in the design of such systems. In particular, we investigate to what extent existing methodologies (i) cover GDPR and privacy-by-design principles, (ii) address different levels of system design concerns, and (iii) have demonstrated their suitability for the purpose. Our literature study shows that the domain landscape appears to be heterogeneous and disconnected, as existing methodologies often focus only on subsets of the GDPR principles and/or on specific angles of system design. Based on our findings, we provide recommendations on the definition of comprehensive methodologies tailored to designing GDPR-compliant high-tech systems.

We propose the system design of a small orbiter of the Jovian moon Europa (Europa Tomography Probe, ETP in short) aimed at unveiling its interior structure. ETP is conceived as a piggyback probe of a larger spacecraft to the Jovian system (such as Europa Clipper). Its payload comprises only a magnetometer and transponder. The former will be used to measure the time-varying, induction magnetic field of the moon at different orbital and rotational frequencies, a measurement inaccessible to a flyby spacecraft. An Inter-Satellite Link (ISL) between ETP and the main spacecraft, enabled by the on-board transponder, will be used to accurately determine Europa's gravity field, rotational state and tidal deformation. By combining magnetic and gravity field measurements, ETP could characterize the interior structure of Europa with an accuracy only attainable by a low-altitude orbiter, thus constraining the thickness and conductivity of the subsurface ocean. Following the announcement that a 250-300-kg mass allowance was available on the upcoming NASA Europa Clipper spacecraft, we propose ETP's mission and spacecraft design assuming Clipper's nominal trajectory as a baseline. The concept can be adapted to a class of missions to the Jovian and Saturnian systems based upon a mother-daughter spacecraft system. The spacecraft design has been pursued under the philosophy of determining the minimum required total mass and volume that allows to meet the scientific requirements, rather than finding out what science return could be obtained with pre-assigned system constraints. Since ETP shall autonomously reach its final orbit, the propulsion system has been one of the primary focuses. The radiation analysis has also been essential because the shielding structure affects both the mission duration and the mass budget. We show that the ETP concept could be, indeed, technically feasible with an overall system mass budget just above 250 kg, thus providing a valuable yet affordable augmentation to a larger flyby mission to Europa.

Sharing of tacit knowledge is a key topic of research within the knowledge management community. Considering its embodied nature, organizations have always struggled with embedding it into their processes. Proper execution of complex processes such as system integration asks for an adequate sharing of tacit knowledge. Acknowledging the importance of lessons learned for system integration and their presence in tacit and explicit form, a case study was conducted within the Netherlands Railways. It was determined that non-sensitivity to the tacit dimension of lessons learned has resulted in their lack of utilization. Consequently, LEAF framework was developed, where LEAF stands for learnability, embraceability, applicability, and findability. The framework suggests that addressing these four features collectively can eventually lead to an adequate knowledge-sharing strategy for lessons learned. Lastly, the chapter presents an example from the Netherlands Railways to emphasize the key role technological solutions of Industry 4.0 can play in facilitating tacit knowledge sharing.

The article describes the systems engineering processes, the current problems encountered in the work of a system engineer, the reasons for their occurrence and the goals, functionality of the new system tool “Product Studio”. «Product Studio» is Design Product Quality Assurance System and it aims to simplify the activities of the system engineer, providing the necessary functionality to perform the relevant processes from requirements definition and management, to the formation of architectural and technical solutions. Keywords: system engineering, system modeling tools, system life cycle process, software system, system engineering activities, architectural design, system modeling languages, current problems in the SE work

Several development approaches have been proposed to handle the growing complexity of software system design. The most popular methods use models as the main artifacts to construct and maintain. The desired role of such models is to facilitate, systematize and standardize the construction of software-based systems. In our work, we propose a model-driven engineering (MDE) methodological approach associated with a pattern-based approach to support the development of secure software systems. We address the idea of using patterns to describe solutions for security as recurring security problems in specific design contexts and present a well-proven generic scheme for their solutions. The proposed approach is based on metamodeling and model transformation techniques to define patterns at different levels of abstraction and generate different representations according to the target domain concerns, respectively. Moreover, we describe an operational architecture for development tools to support the approach. Finally, an empirical evaluation of the proposed approach is presented through a practical application to a use case in the metrology domain with strong security requirements, which is followed by a description of a survey performed among domain experts to better understand their perceptions regarding our approach.

This article proposes a multi-criteria decision support tool fully integrated within system engineering and project management processes that allows decision makers to select an optimal scenario of a project. A model based on an oriented graph includes all the alternative choices of a new system’s conception and realization. These choices take into account the risks inherent to perform project tasks in terms of cost and duration. The model of the graph is constructed by considering all the collaborative decisions of the different actors involved in the project. This decision support tool is based on an Ant Colony Algorithm (ACO) for its ability to provide optimal solutions in a reasonable amount of time. The model developed is a multi-objective new ant colony algorithm based on an innovative learning mechanism (named MONACO) that allows ants to learn from their previous choices in order to influence the future ones. The objectives to be minimized are the total cost of the project, its global duration and the risk associated with these criteria. The risk is modeled as an uncertainty related to the increase of the nominal values of cost and duration. The optimization tool is a part of an integrated and more global process, based on industrial standards (the System Engineering process and the Project Management one) that are widely known and used in companies.

Today, phase A studies of future space systems are often conducted in special design facilities such as the Concurrent Engineering Facility at the German Aerospace Center (DLR). Within these facilities, the studies are performed following a defined process making use of a data model for information exchange. Quite often it remains unclear what exactly such a data model is and how it is implemented and applied. Nowadays, such a data model is usually a software using a formal specification describing its capabilities within a so-called meta-model. This meta-model, often referred as conceptual data model, is finally used and instantiated as system model during these concurrent engineering studies. Such software also provides a user interface for instantiating and sharing the system model within the design team and it provides capabilities to analyze the system model on the fly. This is possible due to the semantics of the underlying conceptual data model creating a common language used to exchange and process design information. This article explains the implementation of the data model at DLR and shows information how it is applied in the concurrent engineering process of the Concurrent Engineering Facility. It highlights important aspects concerning the modeling capabilities during a study and discusses how they can be implemented into a corresponding conceptual data model. Accordingly, the article presents important aspects such as rights management and data consistency and the implications of them to the software’s underlying technology. A special use case of the data model is depicted and shows the flexibility of the implementation proven by a study of a multi-module space station.

A pattern-based approach as a new method for system dependability engineering based on the reuse of patterns.The design a set of DSMLs to specify the dependability patterns.The development of a set of tools to support the proposed approach.The application of the approach in the context of railway systems.These results suggest our work has wider applicability and usefulness. Safety-critical systems require a high level of safety and integrity. Therefore, generating such systems involves specific software building processes. Many domains are not traditionally involved in these types of software problems and must adapt their current processes accordingly. Typically, such requirements are developed ad hoc for each system, preventing further reuse beyond the domain-specific boundaries. This paper proposes a solution for software system development based on the reuse of dedicated subsystems, i.e., so-called dependability patterns that have been pre-engineered to adapt to a specific domain. We use Model-Driven Engineering (MDE) to describe dependability patterns and a methodology for developing dependable software systems using these patterns. Moreover, we describe an operational architecture for development tools to support the approach. An empirical evaluation of the proposed approach is presented through its practical application to a case study in the railway domain, which has strong dependability requirements, to support a pattern-based development approach. This case study is followed by a survey to better understand the perceptions of practitioners regarding our approach.

Automotive Systems and Software Engineering : State of the Art and Future Trends, edited by Yanja Dajsuren, and den Brand, Mark van, Springer International Publishing AG, 2019. ProQuest Ebook Central, http://ebookcentral.proquest.com/lib/polije-ebooks/detail.action?docID=5831085. Created from polije-ebooks on 2019-12-18 22:54:24.

International audience; Throughout its life cycle, systems undergo several modifications in their architecture. These changes target at remaining competitive and responding quickly to new customer requirements. However, any entity change (i.e. component, function or functionality) can produce unexpected consequences, propagated throughout the whole system architecture. It is then necessary to model, predict and control them. System engineering tools and techniques allow dealing with complex systems design. That is why we have developed a novel methodology to analyze changes using a system engineering methodology called ARCADIA, developed by Thales and its associated software Capella. The obtained models allow mapping various kinds of dependencies within a system architecture. The method, presented in this paper, shows how these models are used to integrate change propagation and transform them into Bayesian networks. A set of experiments allows then to obtain insightful pieces of knowledge about the changes propagation. An illustrative case is developed with a focus of particular changes caused by obsolescence of component, function or functionality.

Technological platforms dedicated for digital instrumentation and control of nuclear reactors are quite complex in terms of functionalities and devices. Hence, the design of these platforms requires high-level abstraction layers able to reduce the complexity, to rise the automation and to check the consistency between different development stages. The development of such systems is a challenging task that requires modeling of various components at different levels of abstraction and viewpoints, notably functional, hardware and software levels. In this paper, a new system engineering methodology is proposed to provide high-level models of different components and inter/intra-communication between them. These models are used for system specification, architecture design, performance evaluation or verification and validation. This approach focuses on the internal behavior of different components at different levels of abstraction in order to enable the interoperability of these components and to enhance cooperation between different stakeholders of the development process. An experimental setup has been carried out to validate this approach by customizing an open source model based engineering tool, Eclipse Papyrus, towards a significant reduction of system development cost in terms of engineering resources and equipment devices.

The performance of a radiatively cooled instrument is investigated in the context of optomechanical quantum experiments, where the environment of a macroscopic particle in a quantum-superposition has to be cooled to less than 20\,K in deep space. A heat-transfer analysis between the components of the instrument as well as a transfer-function analysis on thermal oscillations induced by the spacecraft interior and by dissipative sources is performed. The thermal behaviour of the instrument in an orbit around a Lagrangian point and in a highly elliptical Earth orbit is discussed. Finally, we investigate further possible design improvements aiming at lower temperatures of the environment of the macroscopic particle. These include a mirror-based design of the imaging system on the optical bench and the extension of the heat shields., 13 pages, 11 figures, 3 tables

10 pages; International audience; Systems engineering (SE) is a very promising approach to facilitate the development of complex systems. This explains why several SE processes have been already proposed. However, these proposals focus mainly on systems with faultless components. Integration of dependability concerns into SE processes must be supported by a suitable organization of the data which are dealt with during the system life-cycle. A meta-model which defines the concepts used during this cycle as well as the relations between these concepts is a way to rigorously describe this organization. This article proposes such a meta-model developed for power production systems. These systems are phased mission systems composed of repairable and multi-state components; moreover, several redundancy policies shall be defined for each phase. This proposal is illustrated on a small example from a power plant. Last, the merit of this contribution to support the integration of dependability concerns is shown by proposing a method to build systematically, from the instance diagrams derived from the proposed meta-model, the Markov Chains which represent the dysfunctional dynamic behavior of a system.

Studies of systems engineering applications have revealed that systems engineering (SE) has a high potential for transferring economically inefficient oil and gas projects into a profitable zone due to preserving the value created at the concept stage right up to the implementation stage. To implement any project, including an organizational one, the company must have an economic justification for innovation. Studies into the global experience of assessing SE efficiency based on projects of various types have revealed the lack of a universal assessment method, however, individual studies have potential to be used in developing a method for quantifying the value of SE in oil and gas projects. Considering this fact, we developed our own method and prototype to assess the economic effect from the introduction of SE into oil and gas projects. The method is based on a decision tree used to calculate the Net Present Value considering the probability of projects&rsquo, success and failure in terms of budget and deadlines. This allowed us to predict the effect from introducing SE to an oil company&rsquo, s capital project. The results obtained demonstrated the model&rsquo, s performance capability and its possible applications in project resource planning stages.

A digital twin is a digital replica of a physical entity to which it is remotely connected. A digital twin can provide a rich representation of the corresponding physical entity and enables sophisticated control for various purposes. Although the concept of the digital twin is largely known, designing digital twins based systems has not yet been fully explored. In practice, digital twins can be applied in different ways leading to different architectural designs. To guide the architecture design process, we provide a pattern-oriented approach for architecting digital twin-based systems. To this end, we propose a catalog of digital twin architecture design patterns that can be reused in the broad context of systems engineering. The patterns support the various phases in the systems engineering life cycle process, and are described using a well-defined pattern documentation template. For illustrating the application of digital twin patterns, we adopt a multi-case study approach in the agriculture and food domain.

Background Within the current organization of design activities it is difficult to fully realize the potential of BIM (Building Information Modelling). In BIM processes, it is necessary to identify and exchange the specific information that is relevant in the exchange information requirements of each project. The concept of level of detail of the information is a tool for describing and quantifying the information that should be exchanged. But the existing definitions of level of detail of information are not easily usable. Precise definitions of methodology, tools and principles are needed to redefine this concept and to use it in order to define the elements of information that are relevant to be exchanged. Methods The authors propose the use of System Engineering and Requirements Engineering to define BIM uses and the relevant level of detail of information and its modelling concerned by each BIM use. The authors first explain why, in this context, the existing definitions of LOD, which can mean level of detail, level of development, level of definition, etc., are not sufficient and not always coherent. They demonstrate through real use cases that System Engineering and Requirement Engineering are a part of this methodology and propose, using formalisms, to describe each BIM use in detail. Results The authors apply two different approaches to defining the relevant information to each BIM use. Using a top-down conceptual approach they show that Level Of Detail (LOD) is a crucial element in defining the content of a BIM use. They then verify the practicality of their proposal using a bottom-up approach based on three use cases (acoustic studies, safety audit, sizing drainage system). These cases studies allow the authors to address different kinds of systems and objects within a whole infrastructure project. They represent domain use cases (acoustic and drainage) and coordination use cases (safety audit). This part of the work is based on the L2 project in Marseille, which is a Public Private Partnership for expressways. As a result, a methodology is proposed both to redefine the level of detail of information concept and to describe how this concept is used to complete the BIM uses definition. The system engineering and requirement engineering methods are partially adapted to infrastructure projects. These elements facilitate the description of BIM uses expected in BIM Execution Plans. It was necessary to change the definitions of LOD in order to make them compatible with the methods of requirement management. Conclusions Design activities should be reorganized toward the common goal of meeting project needs and requirements. The authors demonstrate that the best way to meet requirements is to define BIM uses using a new definition of the level of detail of information. It has first to consider requirements that have to be reached through BIM and then define the relevant level of detail of information, using the concept of abstraction of reality. To do it well, applying system engineering and requirement engineering, adapted to infrastructure project, is required. To validate this proposal on an entire project, more use cases will be tested in further work.

This paper deals with pre-concept studies of DEMO divertor cassette-to-vacuum vessel locking system under the work program WP13-DAS-07-T06: Divertor Remote Maintenance System pre-concept study. An iterative design process, consistent with Systems Engineering guidelines and named Iterative and Participative Axiomatic Design Process (IPADeP), is used in this paper to propose new innovative solutions for divertor locking system, which can overcome the difficulties in applying the ITER principles to DEMO. The solutions conceived have been analysed from the structural point of view using the software Ansys and, eventually, evaluated using the methodology known as Fuzzy-Analytic Hierarchy Process. Due to the lack and the uncertainty of the requirements in this early conceptual design stage, the aim is to cover a first iteration of an iterative and incremental process to propose an innovative design concept to be developed in more details as the information will be completed.

Methods on multiple configuration sensor is an important theme in this domain. In order to break through the bottleneck of more than a majority to configure the system to achieve continuous transformation areas, the impact of the system close to the theoretical limit and configuration flexibility. Theory is studied based on the theory of Gaussian optical system error distribution and comprehensive balancing algorithm; Established the choose big type staring FPA detector, and adopt continuous design and diffraction technology advanced pure transmission type configurations; Global optimization method, developed at the top of such a system design thought and the optimization model. Results solved the wide spectrum, field, low distortion and MTF matching problem, research and evaluate the other aspects and so on as qualitative criterion to achieve application requirements.

Today, one of the major challenges in full-vehicle model creation is to get domain models from different experts while detecting any potential inconsistency problem before the Integration, Verification, Validation, and Qualification phase. To overcome such challenges, the conceptual design phase has been adapted to the current model development process. For that, the system engineers start to define the most relevant system architecture by respecting quality and time constraints. Next, the simulation model architects design the delivered system architecture in a more formal way with a modeling and simulation point of view to support the integration of domain-level simulation models in a consistent fashion. Finally, the model architects negotiate with different simulation model providers with the aim of specifying vehicle- and domain-level simulation models and their interface connections. To improve knowledge sharing between the mentioned actors, we propose a model identity card (MIC) for classifying simulation model knowledge, including input/output parameters, method, and usage specifications. The fundamental concepts that form the basis of all simulation models are identified and typed for implementation into a computational environment. An industrial case study of the engine–after-treatment model is used to show how MICs and the integrated model design phase might be used in a given scenario. A validation protocol is conducted through a heuristic observation to estimate the rate of model rework and ambiguity reduction.

The article presents information on the history and prospects of systems engineering in criminology . Disclosed the theoretical , methodological and practical aspects of using the system method in the study of crime. Marked with the basic fundamentals of the modeling methodology crime.

International audience; Urban development is a critical issue that many cities are facing, due to the demography growth which results from the economic attractiveness of the urban centers. Based on common standards such as the Urban Development Plans, some projects for transportation systems renewal are progressively launched. In order to allow social cohesion, especially by providing travelers with services which may allow to better organize the transport, it is necessary to structure the transportation system according to sustainability requirements. This paper examines an integrated approach for assessing the sustainability of the current transportation system design, based on a policy making problem, aiming at providing decision makers with a framework allowing them to choose the most eco-responsible policy amongst many alternatives. Since the sustainability indicators may conflict each other, in order to better take into account the requirements of the whole transportation system in its design phase, a system-based approach has been adopted to characterize the complex structure of these indicators. A general methodology for their elicitation is proposed, using a process-object methodology and based on surveys from recent research on sustainable transportation, along with eco-design principles, in order to take into account urban transport priorities, sustainability challenges and the analysis of the whole lifecycle of the transport infrastructure and equipment. To validate this proposal, a multi-criteria decision method, allowing subjectivity, uncertainty, incomplete judgments and group consensus is then performed, based on a case study which shows the flexibility of fuzzy analytical hierarchy process for such assessment.

International audience; Systems Engineering (SE) is a standardized methodological and interdisciplinary approach that has been successfully applied in various industrial fields; this approach serves to support, guide and manage design activities dedicated to complex systems by taking into account stakeholders' advice and expectations throughout the system life cycle. This article focuses on the interoperability feature which has to be seen as a specific requirement in its own right. Indeed, any system need to interact with other systems, thereby forming a heterogeneous environment. All these systems have not necessarily been designed to function properly and efficiently with one another, whether from a conceptual, technical, behavioral or organizational standpoint. This paper highlights what seems to be relevant in terms of conceptual definitions and modeling framework whenever a (group) of engineer(s) intends to design what we call here a “natively interoperable system” or at least a system maximizing its abilities to be interoperable. To proceed, a clear definition of the concept of interoperability applied to complex systems is the first prerequisite. The second prerequisite consists of establishing the needs of a design team assigned to design such system. An interface design pattern model with sufficient generic, formal and pragmatic qualities is proposed.

International audience; Cyber-Physical Systems (CPS) combine discrete computing elements together with physical devices in uncertain environment conditions. There have been many models to capture different aspects of CPS. However, to deal with the increasing complexity of these ubiquitous systems, which invade all the part of our lives, we need an integrated framework able to capture all the different views of such complex systems in a consistent way. We also need to combine tools to analyze their expected properties and guarantee safety issues. Far from handing out a full-fledge solution, we merely explore a possible path that could bring part of the solution. We advocate for relying on uml models as a unifying framework to build a single-source modeling environment with design, exploration and analysis tools. We comment on some useful extensions of UML, including MARTE and SysML, and show how they can together capture different views of CPS. We also report on some recent results obtained and discuss possible evolutions in a near future.

International audience; This paper studies the performance of Peer-to-Peer storage and backup systems (P2PSS). These systems are based on three pillars: data fragmentation and dissemination among the peers, redundancy mechanisms to cope with peers churn and repair mechanisms to recover lost or temporarily unavailable data. Usually, redundancy is achieved either by using replication or by using erasure codes. A new class of network coding (regenerating codes) has been proposed recently. Therefore, we will adapt our work to these three redundancy schemes. We introduce two mechanisms for recovering lost data and evaluate their performance by modeling them through absorbing Markov chains. Specifically, we evaluate the quality of service provided to users in terms of durability and availability of stored data for each recovery mechanism and deduce the impact of its parameters on the system performance. The first mechanism is centralized and based on the use of a single server that can recover multiple losses at once. The second mechanism is distributed: reconstruction of lost fragments is iterated sequentially on many peers until that the required level of redundancy is attained. The key assumptions made in this work, in particular, the assumptions made on the recovery process and peer on-times distribution, are in agreement with the analysis in [1] and in [2] respectively. The models are thereby general enough to be applicable to many distributed environments as shown through numerical computations. We find that, in stable environments such as local area or research institute networks where machines are usually highly available, the distributed-repair scheme in erasure-coded systems offers a reliable, scalable and cheap storage/backup solution. For the case of highly dynamic environments, in general, the distributed-repair scheme is inefficient, in particular to maintain high data availability, unless the data redundancy is high. Using regenerating codes overcomes this limitation of the distributed-repair scheme. P2PSS with centralized-repair scheme are efficient in any environment but have the disadvantage of relying on a centralized authority. However, the analysis of the overhead cost (e.g. computation, bandwidth and complexity cost) resulting from the different redundancy schemes with respect to their advantages (e.g. simplicity), is left for future work.

This paper describes a computing model of a product-service-value system (PSV-S), especially its performance and behavioral models. We have developed PSV-S concepts as an abstraction of engineering solutions and processes. In this paper, we develop a model of a practical PSV-S with an emphasis on value creation for itself as well as for four other sources. This requires exchanges among five currencies. We then model a PSV-S internal structure recursively, containing four internal PSV-Ss, and six internal currencies. Initial models for external sources are based on supply-demand curves. At the end, this paper discusses the application of the computing model for virtual prototyping of PSV-Ss.

International audience; This paper aims to realize an eco-comparison among power-train configurations of hybrid busses in terms of performance, fuel consumption and CO2 emission. The present study has been carried out in the context of the international research program PLACIS (PLAteforme Collaborative d'Ingénierie Systèmes). In this work, experimental data of a pure electric power-train, evaluated in a dedicated laboratory of Istituto Motori – the National Research Council of Italy, have been used to carry out a pre-design phase of the modelling procedure. From that point on, in order to optimize the powertrain performance, a series hybrid vehicles configuration and a parallel one have been modeled and simulated on DYMOLA-MODELICA environment. The vehicle that has been taken into account, as reference for the comparison, is a " RENAULT-Master " minibus. Power-trains have been modeled with a backward-forward configuration in order to have a physical approach to the problem, respecting the required performances. The study has been developed with System Engineering approach that aims to manage the complexity of systems with a multidisciplinary proposal.

In case of natural or man-made disasters it is essential to alert and provide meaningful warning information to enable individuals, communities and organisations at risk to prepare and to act appropriately to reduce the impact in terms of harm and loss. This statement involves: – some prior risk knowledge, that is the capability to understand what events or situations can be or become hazardous to specific communities; – the capability to detect and monitor those hazards in due time; – the capability to compile the relevant information in actionable messages and disseminate them to reach the individuals, communities and organizations at risk; – the preparedness of individuals, communities and organizations at risk to act upon reception of the warning information.

The development of complex mechatronic systems demands an integration of models throughout the virtual product development process. Systems engineering is an approach for enabling the development of successful interdisciplinary products. Traceability, one of the most important aspects of systems engineering, is a method for explicit documentation of logical relationships between development artifacts. In this paper we present a prototype traceability tool, ModelTracer, which aims to reduce the cognitive effort for the creation and maintenance of traceability models in systems engineering.

This paper presents the MDE process in use at Elettronica SpA (ELT) for the development of complex embedded systems integrating software and firmware. The process is based on the adoption of SysML as the system-level modeling language and the use of Simulink for the refinement of selected subsystems. Implementations are generated automatically for both the software (C++ code) and firmware parts, and communication adapters are automatically generated from SysML using a dedicated profile and open-source tools for modeling and code generation. The process starts from a SysML system model, developed according to the platform-based design paradigm, in which a functional model of the system is paired to a model of the execution platform. Subsystems are refined as Simulink models or hand-coded in C++. An implementation for Simulink models is generated as software code or firmware on FPGA. Based on the SysML system architecture specification, our framework drives the generation of Simulink models with consistent interfaces, allows the automatic generation of the communication code among all subsystems (including the HW–FW interface code). In addition, it provides for the automatic generation of connectors for system-level simulation and of test harnesses and mockups to ease the integration and verification stage. We provide early results on the time savings obtained by using these technologies in the development process.

International audience; In response to the challenges related to integrate human considerations within complex interactive systems, the Human-System Integration (HSI) initiative has been proposed. Nevertheless, the HSI approach is difficult to fit efficiently into the system engineering processes because of the lack of shared methodologies, modeling semantics and tools. This paper focuses on the needs for a new methodology and an adapted formalism to improve the collaboration between the system engineers and HSI practitioners. It concludes with the presentation of our methodology based on the Model-Based System Engineering (MBSE) and the SysML modelling language.

There is a growing class of engineering applications for which long-term managed evolution and/or managed sustainability is the primary development objective. The underlying tenet of our work is that neither of these trends will become fully mature without: (1) An understanding for how and why system entities are connected together, and (2) Formal procedures for assessing the correctness of system operations, estimating system performance, and understanding trade spaces involving competing design criteria. To address these concerns, during the past few years we have developed methodologies and tools for ontology-enabled traceability; that is, traceability mechanisms where requirements are connected to models of engineering entities by threading the traceability connection through one or more ontologies. In our proof-of-concept work the engineering entities were restricted to elements of system structure. But, of course, real engineering systems also have behaviors. This paper will report on research to understand the role that software patterns (e.g., model-view-controller) and mixtures of graph and tree visualization can play in the implementation of traceability mechanisms from requirements to elements of finite-state machine behavior (e.g., actions, states, transitions and guard conditions). We will present a simple lamp example.

The purpose of this paper is to analyze the impact of organizational features and context variables on the proneness of University-Industry cooperation (UIC) in the R&D and engineering process. Using survey data of manufacturing enterprises in Guangdong province of China, the paper shows that the probability of cooperation with university significantly depends on various organizational factors including firm size and enterprise absorptive capacity. In addition, the actually pay tax the collection of business-to-market and technical information, and market position are also important driving factors to the engineering research cooperation between enterprises and universities, but their influences vary with the type of product innovation and process innovation.

Most of the research on text categorization didnot consider the characteristics of the emergency domain. Considering the characters of a specific emergency domain, we propose a text classification based on emergency domain words and machine learning technique taking a System Engineering view. With CHI as evaluation function to select text features, the addition of emergency domain words, Maximum Entropy classifier and KNN classifier, we conduct a series of experiments on emergency event texts classification. The experiments show that, the introduction of emergency domain words will increase the average accuracy of maximum entropy classifier and KNN classifier by 4% to 5%. Particularly maximum entropy classifier can still get an average accuracy rate as 97.0% after the introduction of the emergency domain terms.

Organizational emergence from chaotic events has often been described as unpredictable and random, at least when observed over the long term. Through a literature review this paper paves the path for the possible development of a forecasting model for making short term predictions during chaotic events so as to assist business practitioners in navigating their way out of chaos, thereby facilitating organizational emergence. As such, the paper builds on chaos and complexity theory, as its foundational theory, and identifies the most important factors and mechanisms cited in current literature that influence organizational emergence so as to potentially incorporate the factors in the future development of a short term forecasting model.

In order to confirm the factors and the relationship between them in the development of emergency, the System Engineering analysis idea and graphical expression of vensim are used to explore the factors of emergency. The study shows that the emergency evolution process consists of three subsystems: security technology, human resource and environment, which influences each other. And, only these subsystems strengthen coordination, they can improve the management of emergency.

The new field of space architecture is introduced. Defined as the “theory and practice of designing and building inhabited environments in outer space,” the field synthesizes human space flight systems engineering subjects with the long tradition of making environments that support human living, work, and aspiration. The scope of the field is outlined, and its three principal domains differentiated. The current state of the art is described in terms of executed projects. Foreseeable options for 21st century developments in human space flight provide a framework to tease out potential space architecture opportunities for the next century.

This paper presents an ongoing work at the Institute of Aeronautics and Space (IAE) to provide a process and a system to support the management of knowledge and new technologies applied to the conception and development of the Brazilian Satellite Launcher Program. This management is not only necessary to organize the actual research efforts but also to identify communalities and necessities for the strategic planning of future research projects and development activities. The results of the research projects are usually new technologies that ought to be employed in the development of the Launcher Program. The proposed knowledge management system will not only enable assessing these new technologies but also help in defining and planning the research topics in each important area of this multidisciplinary program, according to the Institute's strategic goals and space mission.

International audience; —The ambiguity of natural language is an issue which predates requirement engineering. This issue is, in the general case, obviously unsolvable, nor actually needing a solution. However, we think that in particular contexts, it is feasible and desirable to reduce the ambiguity of free text specifications. We look at how specifications are actually handled in a company to be able to propose an useful but not too disruptive method for writing better specifications. We are currently developing and investigating how to validate this method.

Despite its acknowledged benefits for health promotion, the full potential of persuasive technology is not (yet) reached in regard to usability, effectiveness, and reproducibility. It often lacks an effective combination of technical features and behavior change strategies. This paper presents a multidisciplinary approach, addressing both aspects. It builds on the frameworks of situated Cognitive Engineering and Intervention Mapping. The approach generates building blocks from theory originating from different relevant disciplines; it specifies change objectives and requirements, described in the context of use, for intervention (strategy) and interaction (technology); it evaluates process, effect and impact, whereby claims on interaction and intervention are validated. To cope with language barriers between developers from different disciplines, the approach is presented as a guideline, illustrated with a case study. This approach is expected to contribute to a sound design rationale, a broad reach and ongoing use of the technology, and larger results in regard to health promotion.

Day by day, producers of manufacturing systems are challenged with the need of flexibility and reconfigurability of their products. Being able of rapidly provide various configurations of products in response to customers requests is an important asset in the nowadays competition. Nevertheless, most of the automation software for special machines is built in a monolithic way which does not support rapid reconfigurability to reflect hardware modifications. This paper proposes a modular and reconfigurable approach to software development for the automation to support rapid reconfigurations of the software. The designed strategy consists in a seamless replication of the hardware modularization within the software to allow software generation by assembling pre-built pieces of software. The approach is presented and then applied to a real manufacturing machine.

Recent dismal economic conditions and a ruthlessly competitive environment have forced many companies to restructure, or reorganize their priorities. For such companies, the concentration of various resources upon their particular corporate strong points has become a central strategy. Consequently, there has been a rapid increase in the importance of (1) selecting profitable projects from a wealth of possible alternatives and (2) optimizing the allocation of current resources among the selected projects. This paper proposes an optimization system for project selection that not only yields the most beneficial project set, but also the optimum allocation of human resources for the selected projects. The optimization system consists of two algorithms, namely (1) a project selection algorithm for choosing the set of projects that maximizes the total estimated profit, and (2) a human resource allocation algorithm for optimally placing human resources among the selected projects, having considered the satisfact...

Part 2: Knowledge-Based Services; International audience; Requirements engineering in usually considered a first step before design that is to evolve with each generation or version in a prod- uct line. Nuclear plants however, are subject to modifications during their lifetime, in their design and implementation as well as in the re- quirements they have to satisfy. Economic, technical and safety reasons lead to extending the requirements engineering process through the whole life-cycle of the nuclear plants. This article presents an ontology-based approach to integrating the requirements engineering into a PLM ap- proach for such long-lived, large-scale products.

Part 1: Knowledge Discovery and Sharing; International audience; The IVTV Plan (Integration, Verification, Transition and Validation of the system before its Qualification) is developed and validated during the design stage. It details all the activities, resources, requirements, means, etc. requested during the realization stage so it is the hyphen between these two crucial stages in system life cycle. It is today necessary to help companies to better transfer detailed design models towards realization for many reasons discussed in this paper. Mainly, IVTV plan remains difficult to be exploited. This article proposes a first step towards a Model-Based Realization Plan, that is, a meta-model that represents the links between models that comes from Model-Based System Engineering and information required in the IVTV plan.

International audience; Computer aided techniques widely used as diagnostic and surgical procedures tools are scarcely applied in implantology, which continues using visualization of CT images to define the parameters for dental implant process leaving to the dentist discretion the implant determination, since only the images analysis is non-deterministic. Thus, this research proposes the development of a knowledge-link model integrated to a reasoner system to support dental implant process through information modeling. The system presents an interface that interacts with the user and consists of reasoning mechanisms connected by knowledge-links to a base of knowledge that enables information translation, conversion and sharing. The results obtained using the model showed that it is a valuable tool in the decisions making made by the surgeon in the dental implant planning process as it will be based on concrete and measurable data generated by the system through the analysis of the patient's tomographic images and implants data.

Robot-assisted neurorehabilitation often involves networked systems of sensors ("sensory rooms") and powerful devices in physical interaction with weak users. Safety is unquestionably a primary concern. Some lightweight robot platforms and devices designed on purpose include safety properties using redundant sensors or intrinsic safety design (e.g. compliance and backdrivability, limited exchange of energy). Nonetheless, the entire "sensory room" shall be required to be fail-safe and safely monitored as a system at large. Yet, sensor capabilities and control algorithms used in functional therapies require, in general, frequent updates or re-configurations, making a safety-grade release of such devices hardly sustainable in cost-effectiveness and development time. As such, promising integrated platforms for human-in-the-loop therapies could not find clinical application and manufacturing support because of lacking in the maintenance of global fail-safe properties.Under the general context of cross-machinery safety standards, the paper presents a methodology called SafeNet for helping in extending the safety rate of Human Robot Interaction (HRI) systems using unsafe components, including sensors and controllers. SafeNet considers, in fact, the robotic system as a device at large and applies the principles of functional safety (as in ISO 13489-1) through a set of architectural procedures and implementation rules. The enabled capability of monitoring a network of unsafe devices through redundant computational nodes, allows the usage of any custom sensors and algorithms, usually planned and assembled at therapy planning-time rather than at platform design-time. A case study is presented with an actual implementation of the proposed methodology. A specific architectural solution is applied to an example of robot-assisted upper-limb rehabilitation with online motion tracking. © 2014 Elsevier Ireland Ltd.

Part 1: Knowledge Discovery and Sharing; International audience; This paper puts forward several evolutions in methodological approaches to « project management». Firstly, it aims to bring closer the founding models of different engineering approachesincluding systems engineering and project management recommendations to allow fora greater continuity and enhanced management coherence,from beginning to end of the project. It focuses on operating a generic process, called DECWAYS, based on handling management requirements:(1)analyze the requirements to arrive at a complete inventory of the final product ;(2)associate with each one of these requirements ,an « indicator » setting a target objective for completion, supplemented by a risk function detailing the risk at hand based on the deviation relative to this target objective; (3)share and allocate the responsibility for requirements follow-up between the project team leaders; (4) organize and coordinate the follow up of these indicators throughout the product development as proof of a good work management and,(5) finally, validate the total completion of the target objectivesthrough the final prediction/completion conformity of these indicators. Based on this, several operational recommendations are explained and the practicality of DECWAYS embodying these principles is demonstrated using an experimental example for the design/planning of an electronic key.