The French defence industry in the knowledge management era: A historical overview and evidence from empirical data

In the defence industry the recent development of ‘market for technology', the creation of new European high-technology companies as well as transformations in government agencies have conducted firms to reposition their technological and organisational skills. Our objective is to show that the transformations that have occurred in the past ten years have not only redefined skills and the organisation of production but have also given a more strategic place to knowledge management practices. Thus, we provide a contextual and historical overview with qualitative interviews in order to better understand the relation between KM and innovative behaviour in this industry. We have also built an original industrial and technological database with various samples that provides quantitative information concerning KM and innovative practices. The results of the statistical analysis reveal the specificity of firms in the defence industry. Taking into account the size of the firms and their technological intensity, we show that the behaviour of firms in the defence industry in terms of KM practices is different to that of other firms. The technological performances, the innovation intensity and the patent intensity also show the specificity of this industry. This structural tendency is explained as an innovative behaviour of the French NIS rather than as a mere “trend”Defence industry, Knowledge management practices, R&D, innovation, technological performance.

A knowledge based reengineering approach via ontology and description logic.

Traditional software reengineering often involves a great deal of manual effort by software maintainers. This is time consuming and error prone. Due to the knowledge intensive properties of software reengineering, a knowledge-based solution is proposed in this thesis to semi-automate some of this manual effort. This thesis aims to explore the principle research question: “How can software systems be described by knowledge representation techniques in order to semi-automate the manual effort in software reengineering?” The underlying research procedure of this thesis is scientific method, which consists of: observation, proposition, test and conclusion. Ontology and description logic are employed to model and represent the knowledge in different software systems, which is integrated with domain knowledge. Model transformation is used to support ontology development. Description logic is used to implement ontology mapping algorithms, in which the problem of detecting semantic relationships is converted into the problem of deducing the satisfiability of logical formulae. Operating system ontology has been built with a top-down approach, and it was deployed to support platform specific software migration [132] and portable software development [18]. Data-dominant software ontology has been built via a bottom-up approach, and it was deployed to support program comprehension [131] and modularisation [130]. This thesis suggests that software systems can be represented by ontology and description logic. Consequently, it will help in semi-automating some of the manual tasks in software reengineering. However, there are also limitations: bottom-up ontology development may sacrifice some complexity of systems; top-down ontology development may become time consuming and complicated. In terms of future work, a greater number of diverse software system categories could be involved and different software system knowledge could be explored

Building Information Modeling and Building Performance Simulation-Based Decision Support Systems for Improved Built Heritage Operation

Adapting outdated building stocks’ operations to meet current environmental and economic demands poses significant challenges that, to be faced, require a shift toward digitalization in the architecture, engineering, construction, and operation sectors. Digital tools capable of acquiring, structuring, sharing, processing, and visualizing built assets’ data in the form of knowledge need to be conceptualized and developed to inform asset managers in decision-making and strategic planning. This paper explores how building information modeling and building performance simulation technologies can be integrated into digital decision support systems (DSS) to make building data accessible and usable by non-digital expert operators through user-friendly services. The method followed to develop the digital DSS is illustrated and then demonstrated with a simulation-based application conducted on the heritage case study of the Faculty of Engineering in Bologna, Italy. The analysis allows insights into the building’s energy performance at the space and hour scale and explores its relationship with the planned occupancy through a data visualization approach. In addition, the conceptualization of the DSS within a digital twin vision lays the foundations for future extensions to other technologies and data, including, for example, live sensor measurements, occupant feedback, and forecasting algorithms

HybridMDSD: Multi-Domain Engineering with Model-Driven Software Development using Ontological Foundations

Software development is a complex task. Executable applications comprise a mutlitude of diverse components that are developed with various frameworks, libraries, or communication platforms. The technical complexity in development retains resources, hampers efficient problem solving, and thus increases the overall cost of software production. Another significant challenge in market-driven software engineering is the variety of customer needs. It necessitates a maximum of flexibility in software implementations to facilitate the deployment of different products that are based on one single core. To reduce technical complexity, the paradigm of Model-Driven Software Development (MDSD) facilitates the abstract specification of software based on modeling languages. Corresponding models are used to generate actual programming code without the need for creating manually written, error-prone assets. Modeling languages that are tailored towards a particular domain are called domain-specific languages (DSLs). Domain-specific modeling (DSM) approximates technical solutions with intentional problems and fosters the unfolding of specialized expertise. To cope with feature diversity in applications, the Software Product Line Engineering (SPLE) community provides means for the management of variability in software products, such as feature models and appropriate tools for mapping features to implementation assets. Model-driven development, domain-specific modeling, and the dedicated management of variability in SPLE are vital for the success of software enterprises. Yet, these paradigms exist in isolation and need to be integrated in order to exhaust the advantages of every single approach. In this thesis, we propose a way to do so. We introduce the paradigm of Multi-Domain Engineering (MDE) which means model-driven development with multiple domain-specific languages in variability-intensive scenarios. MDE strongly emphasize the advantages of MDSD with multiple DSLs as a neccessity for efficiency in software development and treats the paradigm of SPLE as indispensable means to achieve a maximum degree of reuse and flexibility. We present HybridMDSD as our solution approach to implement the MDE paradigm. The core idea of HybidMDSD is to capture the semantics of particular DSLs based on properly defined semantics for software models contained in a central upper ontology. Then, the resulting semantic foundation can be used to establish references between arbitrary domain-specific models (DSMs) and sophisticated instance level reasoning ensures integrity and allows to handle partiucular change adaptation scenarios. Moreover, we present an approach to automatically generate composition code that integrates generated assets from separate DSLs. All necessary development tasks are arranged in a comprehensive development process. Finally, we validate the introduced approach with a profound prototypical implementation and an industrial-scale case study.Softwareentwicklung ist komplex: ausführbare Anwendungen beinhalten und vereinen eine Vielzahl an Komponenten, die mit unterschiedlichen Frameworks, Bibliotheken oder Kommunikationsplattformen entwickelt werden. Die technische Komplexität in der Entwicklung bindet Ressourcen, verhindert effiziente Problemlösung und führt zu insgesamt hohen Kosten bei der Produktion von Software. Zusätzliche Herausforderungen entstehen durch die Vielfalt und Unterschiedlichkeit an Kundenwünschen, die der Entwicklung ein hohes Maß an Flexibilität in Software-Implementierungen abverlangen und die Auslieferung verschiedener Produkte auf Grundlage einer Basis-Implementierung nötig machen. Zur Reduktion der technischen Komplexität bietet sich das Paradigma der modellgetriebenen Softwareentwicklung (MDSD) an. Software-Spezifikationen in Form abstrakter Modelle werden hier verwendet um Programmcode zu generieren, was die fehleranfällige, manuelle Programmierung ähnlicher Komponenten überflüssig macht. Modellierungssprachen, die auf eine bestimmte Problemdomäne zugeschnitten sind, nennt man domänenspezifische Sprachen (DSLs). Domänenspezifische Modellierung (DSM) vereint technische Lösungen mit intentionalen Problemen und ermöglicht die Entfaltung spezialisierter Expertise. Um der Funktionsvielfalt in Software Herr zu werden, bietet der Forschungszweig der Softwareproduktlinienentwicklung (SPLE) verschiedene Mittel zur Verwaltung von Variabilität in Software-Produkten an. Hierzu zählen Feature-Modelle sowie passende Werkzeuge, um Features auf Implementierungsbestandteile abzubilden. Modellgetriebene Entwicklung, domänenspezifische Modellierung und eine spezielle Handhabung von Variabilität in Softwareproduktlinien sind von entscheidender Bedeutung für den Erfolg von Softwarefirmen. Zur Zeit bestehen diese Paradigmen losgelöst voneinander und müssen integriert werden, damit die Vorteile jedes einzelnen für die Gesamtheit der Softwareentwicklung entfaltet werden können. In dieser Arbeit wird ein Ansatz vorgestellt, der dies ermöglicht. Es wird das Multi-Domain Engineering Paradigma (MDE) eingeführt, welches die modellgetriebene Softwareentwicklung mit mehreren domänenspezifischen Sprachen in variabilitätszentrierten Szenarien beschreibt. MDE stellt die Vorteile modellgetriebener Entwicklung mit mehreren DSLs als eine Notwendigkeit für Effizienz in der Entwicklung heraus und betrachtet das SPLE-Paradigma als unabdingbares Mittel um ein Maximum an Wiederverwendbarkeit und Flexibilität zu erzielen. In der Arbeit wird ein Ansatz zur Implementierung des MDE-Paradigmas, mit dem Namen HybridMDSD, vorgestellt

Benchmarking and identification of best practice associated with industrial water use in UK

In the wake of the phenomenal growth rate of fresh water use globally, the need to ensure security of supply and maintain optimal competiveness in water business has heralded the increasing awareness to measure and compare water use by means of meaningful metrics, performance indicators and benchmarks. Thus, in view of the historically intensive use of water by UK industry, this research set out to benchmark the sector’s water use; the overarching aim being to deduce performance gaps in water use by industry, identify best-in-class practices associated with industrial water use, and proffer efficient improvement strategies for optimal performance in the sector. To achieve this aim, and in line with the research funder’s anticipated outcome of this study, a benchmarking software called “i-Water Benchmarking Tool” was developed. Although, few tools and methodologies are available for benchmarking performance with respect to water usage, but most of these tools are mainly domestic water use specific, developed by, and are within the ownership of commercial organizations. Hence, the rationale behind the software development is to provide a robust, user-friendly and accessible tool that can be used to benchmark water use across industrial subsectors and establish the basis for improvement in performance. Based on the foregoing, comprehensive data were sourced from UK water undertakings, trade bodies and environmental agencies, and used to conduct statistical data analyses and performance benchmarking. Results of the analyses revealed that in England and Wales, from 2003 – 2013, “Metals” constituted the highest consumptive water user (43% water use in the manufacturing sector alone), even with the sub-sector’s 51.31% decline in water use during this period; followed by “Chemicals” (20.52%) with a 45.86% decrease in water use. The third, “Petrochemicals” (15.15%), with a 54.02% water use reduction; fourth, “Paper and printing” (6.15%), showing a 51.64% decline; then, “Food and Drinks” being the fifth most intensive water user (5.32%) also indicated a 17.73% decrease in water use. For Scotland, from 2008/09 to 2014/15, “Distilled potable alcoholic beverages” took up the largest consumptive water (30.21%), but exhibited a 16.51% water use decline; the second, “Basic pharmaceutical products” (26.61%) had an 18.51% water use decrease; the third, “Paper and paperboard” (19.35%), revealing a 31.90% increase in water use; fourth, “Beer” (4.91%) with an 18.42% water use decline; then the fifth, “Liquid milk and cream” (4.26%) with a 0.42% reduction in water use between 2008/09 and 2014/15 also. Lastly, in Northern Ireland, from 2011-12 to 2013-14, “Food” used the largest water (57.39%) showing a 3.823% decline in water use during this period; “Non Metals” (10%) with 5.32% decrease; “Electronics” (8.77%) with 20.42% reduction; “Chemical” (8.76%) with a 10.12% water use increase; and lastly, “Drink” (6.33%) with an 11.68% decline in water use. To this end, with 80% of the products indicating a decline in water use, it is inferred that industrial water use in the UK is significantly declining. Accordingly, of the 53 benchmarked companies, 3 companies’ water use performance were ranked “Excellent”; 20 companies, “Average”; while the remaining 30 companies’ performance were “Poor”. In sum, it is envisaged that this project will lead to the definition of a methodology that can be applied to produce same outputs for sectors not covered in this initial project

Consistency of UML based designs using ontology reasoners

Software plays an important role in our society and economy. Software development is an intricate process, and it comprises many different tasks: gathering requirements, designing new solutions that fulfill these requirements, as well as implementing these designs using a programming language into a working system. As a consequence, the development of high quality software is a core problem in software engineering. This thesis focuses on the validation of software designs. The issue of the analysis of designs is of great importance, since errors originating from designs may appear in the final system. It is considered economical to rectify the problems as early in the software development process as possible. Practitioners often create and visualize designs using modeling languages, one of the more popular being the Uni ed Modeling Language (UML). The analysis of the designs can be done manually, but in case of large systems, the need of mechanisms that automatically analyze these designs arises. In this thesis, we propose an automatic approach to analyze UML based designs using logic reasoners. This approach firstly proposes the translations of the UML based designs into a language understandable by reasoners in the form of logic facts, and secondly shows how to use the logic reasoners to infer the logical consequences of these logic facts. We have implemented the proposed translations in the form of a tool that can be used with any standard compliant UML modeling tool. Moreover, we authenticate the proposed approach by automatically validating hundreds of UML based designs that consist of thousands of model elements available in an online model repository. The proposed approach is limited in scope, but is fully automatic and does not require any expertise of logic languages from the user. We exemplify the proposed approach with two applications, which include the validation of domain specific languages and the validation of web service interfaces

Efficient Decision Support Systems

This series is directed to diverse managerial professionals who are leading the transformation of individual domains by using expert information and domain knowledge to drive decision support systems (DSSs). The series offers a broad range of subjects addressed in specific areas such as health care, business management, banking, agriculture, environmental improvement, natural resource and spatial management, aviation administration, and hybrid applications of information technology aimed to interdisciplinary issues. This book series is composed of three volumes: Volume 1 consists of general concepts and methodology of DSSs; Volume 2 consists of applications of DSSs in the biomedical domain; Volume 3 consists of hybrid applications of DSSs in multidisciplinary domains. The book is shaped upon decision support strategies in the new infrastructure that assists the readers in full use of the creative technology to manipulate input data and to transform information into useful decisions for decision makers

Metodología dirigida por modelos para las pruebas de un sistema distribuido multiagente de fabricación

Las presiones del mercado han empujado a las empresas de fabricación a reducir costes a la vez que mejoran sus productos, especializándose en las actividades sobre las que pueden añadir valor y colaborando con especialistas de las otras áreas para el resto. Estos sistemas distribuidos de fabricación conllevan nuevos retos, dado que es difícil integrar los distintos sistemas de información y organizarlos de forma coherente. Esto ha llevado a los investigadores a proponer una variedad de abstracciones, arquitecturas y especificaciones que tratan de atacar esta complejidad. Entre ellas, los sistemas de fabricación holónicos han recibido una atención especial: ven las empresas como redes de holones, entidades que a la vez están formados y forman parte de varios otros holones. Hasta ahora, los holones se han implementado para control de fabricación como agentes inteligentes autoconscientes, pero su curva de aprendizaje y las dificultades a la hora de integrarlos con sistemas tradicionales han dificultado su adopción en la industria. Por otro lado, su comportamiento emergente puede que no sea deseable si se necesita que las tareas cumplan ciertas garantías, como ocurren en las relaciones de negocio a negocio o de negocio a cliente y en las operaciones de alto nivel de gestión de planta. Esta tesis propone una visión más flexible del concepto de holón, permitiendo que se sitúe en un espectro más amplio de niveles de inteligencia, y defiende que sea mejor implementar los holones de negocio como servicios, componentes software que pueden ser reutilizados a través de tecnologías estándar desde cualquier parte de la organización. Estos servicios suelen organizarse como catálogos coherentes, conocidos como Arquitecturas Orientadas a Servicios (‘Service Oriented Architectures’ o SOA). Una iniciativa SOA exitosa puede reportar importantes beneficios, pero no es una tarea trivial. Por este motivo, se han propuesto muchas metodologías SOA en la literatura, pero ninguna de ellas cubre explícitamente la necesidad de probar los servicios. Considerando que la meta de las SOA es incrementar la reutilización del software en la organización, es una carencia importante: tener servicios de alta calidad es crucial para una SOA exitosa. Por este motivo, el objetivo principal de la presente Tesis es definir una metodología extendida que ayude a los usuarios a probar los servicios que implementan a sus holones de negocio. Tras considerar las opciones disponibles, se tomó la metodología dirigida por modelos SODM como punto de partida y se reescribió en su mayor parte con el framework Epsilon de código abierto, permitiendo a los usuarios que modelen su conocimiento parcial sobre el rendimiento esperado de los servicios. Este conocimiento parcial es aprovechado por varios nuevos algoritmos de inferencia de requisitos de rendimiento, que extraen los requisitos específicos de cada servicio. Aunque el algoritmo de inferencia de peticiones por segundo es sencillo, el algoritmo de inferencia de tiempos límite pasó por numerosas revisiones hasta obtener el nivel deseado de funcionalidad y rendimiento. Tras una primera formulación basada en programación lineal, se reemplazó con un algoritmo sencillo ad-hoc que recorría el grafo y después con un algoritmo incremental mucho más rápido y avanzado. El algoritmo incremental produce resultados equivalentes y tarda mucho menos, incluso con modelos grandes. Para sacar más partidos de los modelos, esta Tesis también propone un enfoque general para generar artefactos de prueba para múltiples tecnologías a partir de los modelos anotados por los algoritmos. Para evaluar la viabilidad de este enfoque, se implementó para dos posibles usos: reutilizar pruebas unitarias escritas en Java como pruebas de rendimiento, y generar proyectos completos de prueba de rendimiento usando el framework The Grinder para cualquier Servicio Web que esté descrito usando el estándar Web Services Description Language. La metodología completa es finalmente aplicada con éxito a un caso de estudio basado en un área de fabricación de losas cerámicas rectificadas de un grupo de empresas español. En este caso de estudio se parte de una descripción de alto nivel del negocio y se termina con la implementación de parte de uno de los holones y la generación de pruebas de rendimiento para uno de sus Servicios Web. Con su soporte para tanto diseñar como implementar pruebas de rendimiento de los servicios, se puede concluir que SODM+T ayuda a que los usuarios tengan una mayor confianza en sus implementaciones de los holones de negocio observados en sus empresas

Information systems framework for enterprise agility

Modern day enterprises operate and transact in an increasingly dynamic business environment. As a result, they are vulnerable to spontaneous changes and uncertainties. These usually reduce effectiveness and optimal performances in enterprises, and can have negative impacts such as loss of competitiveness, and bankruptcy. Enterprise agility, i.e., the ability of enterprises to respond to changes, is a core imperative for effective change management. Yet, it is challenging, difficult to achieve, and a major concern for corporate executives. Enterprises would thus require novel approaches to manage changes and enhance agility. In order to facility or achieve enterprise agility, it would be necessary and vital to develop frameworks or processes that can support effective change management. Such frameworks or processes should include techniques for modelling enterprises changes explicitly, so as to enhance the understanding of how changes relate to or affect enterprises. In addition, there should be techniques for deriving the elements of an enterprise, e.g., business process and data entities, that are required to adapt a given enterprise change. However, concepts, constructs, and techniques for representing changes are often neglected, if available at all, in the existing enterprise modelling approaches such as TOGAF and ZACHMAN. This contributes to the difficulty in applying the existing enterprise modelling approaches to enhance enterprise agility and effective change management. The work described in this thesis provides a novel approach for supporting enterprise agility and change management. Therefore, this thesis contributes a conceptual process or framework for representing enterprise changes, and deriving enterprise elements such as data entity, business goal, and business process required to adapt a given change. Other contributions made by this approach include a novel conceptual modelling language for representing enterprise changes, an enterprise modelling language, and a set of procedures and rules that can be used to derive the new domain elements required to adapt changes. An industry case study has been used to test the utility of this framework. The results obtained from this case study shows that this framework supports enterprise agility and change management in a number of ways