ECONOMIC TRADEOFF ANALYSIS OF A PRODUCT LINE ARCHITECTURE APPROACH THROUGH MODEL-BASED SYSTEMS ENGINEERING: A CASE STUDY OF FUTURE MINE COUNTERMEASURES UNMANNED UNDERWATER VEHICLES

The defense sector often develops systems to operate for at least 15 years, which can reach 40 or even 50 years. Those systems tend to be cheaper, more rapidly developed, and reliable when developed on product lines (PL). Product line architecture surges with potential to improve the acquisition process, resulting in a more rapid insertion of cost-effective warfighting capabilities. This thesis investigates the impact of the PL approach by analyzing the future generation of mine countermeasure (MCM) unmanned underwater vehicle (UUV) architecture alternatives, employing a detailed reuse model based on the COPLIMO framework. The research integrates parametric cost modeling with model-based systems engineering (MBSE), feeding the existing baseline knowledge regarding PL architecture. Furthermore, this can improve systems acquisition processes, deliver more agile capability, and reduce total life cycle costs (LCC). The integration of models highlights significant differences among the architectural variations considered early in the acquisition process before substantial financial commitments. Early decisions determine most of the total LCC and establish a baseline for long-term system performance. Hence, the choice of favorable design alternatives is crucial to program success. The results demonstrate that up-front investments in product lines generate a significant return on investment (ROI).Capitao-Tenente, Brazilian NavyApproved for public release. Distribution is unlimited

Cybersecurity Architectural Analysis for Complex Cyber-Physical Systems

In the modern military’s highly interconnected and technology-reliant operational environment, cybersecurity is rapidly growing in importance. Moreover, as a number of highly publicized attacks have occurred against complex cyber-physical systems such as automobiles and airplanes, cybersecurity is no longer limited to traditional computer systems and IT networks. While architectural analysis approaches are critical to improving cybersecurity, these approaches are often poorly understood and applied in ad hoc fashion. This work addresses these gaps by answering the questions: 1. “What is cybersecurity architectural analysis?” and 2. “How can architectural analysis be used to more effectively support cybersecurity decision making for complex cyber-physical systems?” First, a readily understandable description of key architectural concepts and definitions is provided which culminates in a working definition of “cybersecurity architectural analysis,” since none is available in the literature. Next, we survey several architectural analysis approaches to provide the reader with an understanding of the various approaches being used across government and industry. Based on our proposed definition, the previously introduced key concepts, and our survey results, we establish desirable characteristics for evaluating cybersecurity architectural analysis approaches. Lastly, each of the surveyed approaches is assessed against the characteristics and areas of future work are identified

Evolution of Model-Based System Engineering Methodologies for the Design of Space Systems in the Advanced Stages of the Project (Phases B-C)

The main topic of the present work is addressed to the evaluation of the possible improvements that can be achieved with the integration of Model Based System Engineering Methodologies in the advanced phases of space project. In particular a model based approach will be proposed for two main aspects directly affecting the design phases of complex systems. The first one is represented by the management of design options that becomes difficult to monitor as the project proceeds, increasing the amount of data to take into consideration. The other one is represented by the integration between Multidisciplinary Design Optimization (MDO) techniques and a Model Based System Engineering (MBSE) environment. The aim of the research activity concerns the feasibility of such connection in order to assess actual advantages and possible drawbacks. In this last case the objective is to show how the Multidisciplinary Design Optimization (MDO) methods may be managed in the context of a MBSE environment with respect to the traditional design approach. In particular this analysis is addressed to the demonstration of the benefits of MBSE methodology and MDO techniques considering a space system reference case. In the first part of the thesis a briefly description of the problem statement is introduced to better explain the subjects of the following chapters. In particular the reasons and the related purposes that have animated this work are considered. In the next sec..on the state of the art about the considered approach is presented, providing a background for the following activities. In this context a wider analysis of the motivations and thesis objectives is considered. The following chapters deals with the survey and critical assessment of the main work related to this thesis. The analysis, design and implementation of the proposed framework are considered in the next sections. At the end of this part the results obtained are presented without arguing about the related benefits or drawbacks, which are considered in the following. A critical assessment of the results is then presented, analyzing the main contributions and related disadvantages with respect to the current approaches. In the next sec..on the incoming activities and further developments are presented. The final part concerns at last the summary conclusions of the work done

Digitalization as a Paradigm Changer in Machine-Building Industry

Digitalization is a contemporary societal topic among businessmen, scholars, politicians, and citizens. The way Uber has changed the taxi business and subsequently is providing new models for the entire transportation industry or even changing urban planning principles is a practical example of the impact of digitalization. This example illustrates that digitalization offers major returns for some and ultimate losses for others, which is similar to Schumpeter’s “Creative Destruction” that he coined in 1942. Digitalization does not refer to a product or service; it is multiple technology-based products, services, and concepts as a systemic whole. Many of the impacts of digitalization are difficult to observe beforehand, as the impact rendered is systemic rather than a straightforward causal relation. Traditional strategic management theories and frameworks are used to analyze company performance and to explain which strategies individual firms or group of firms should implement to succeed. Many of the tools for top management aid in understanding changes in business environments and offer guidance for making the correct strategic choices, but in many cases, they fail to aid in the detection of systemic phenomena. At the same time, making these strategic choices is difficult, as explained by behavioral economics and management cognition, as the choices involve changing the status quo.This dissertation examines the digitalization impact on the machine-building industry that serves global container handling customers - ports and terminals. It is a traditional capital intensive business-to-business industry that has a relatively small number of global players. The investigation adopted a value chain view in which machine builders are actors, actors apply digital technologies provided by enablers. The end customers, ports and terminals are referred as users. The objective of the research was to increase understanding of digitalization’s potential for disruption or paradigm change as well as to identify the most important concepts that drive and inhibit this change. As the change brought about by digitalization is underway, it is necessary to understand whether the views regarding its impact differ between enablers, actors, and users. Mixed methods were applied that partly overlapped for triangulation purposes. The primary methodology included two rounds of Delphi interviews that were complemented by a survey and three case descriptions.Big Data/Artificial Intelligence emerged as the most prominent digital technology that can enable disruption in machine-building. Empirical results have shown that Big Data/Artificial Intelligence challenges the ways knowledge is created; it is more effective when machines and their components are connected to data networks, and the technology is both rapidly advancing and becoming more affordable. The cost, speed, availability, and features of Big Data/Artificial Intelligence development are driven by multiple industries where machine builders can have a relatively small impact.Empirical results have also shown that discipline and industry-based platforms are the most powerful economic drivers. The current management of the incumbents has little experience with these new elements, which have a major influence on industry dynamics. The platforms are especially powerful for change, as they enable a global network economy in which entrepreneurial knowledge workers can contribute to value creation in collaboration with startups and multinational corporations. Platform development cannot be stopped or delayed by incumbents in machine-building. They can ignore the development, adapt to it, or pursue a platform strategy of their own if the opportunities match the companies’ capabilities.Examples of the sub-drivers pushing the digital concepts forward are classical and rational productivity, lead times, features, quality, and cost. In addition, some of the inhibitive sub-drivers are relatively easy to identify, such as 3D printing speed or users providing access to their data. Concerns regarding data security delay investment, and changing legacy processes and systems requires time; however, empirical results have indicated that the strongest inertia is related directly to people and decision making. Three of the strongest people-related inhibitive sub-drivers are lack of systemic understanding, management beliefs, and lack of capabilities. The practical contribution for management is twofold. First, it must be believed that digitalization will somehow disrupt the current business, and second that the transformation is too complex to be only planned, but instead requires also experimental learning. A successful combination that has been suggested by books and articles as well as the results and comments from the Delphi interviews is developing an entrepreneurial mindset, conducting multiple small experiments, and applying the knowledge of external networks. This enables strategy formation through learning, which simultaneously develops the capabilities that are needed in data and user-centric business environments.Digitalisaatio on ajankohtainen aihe liikemiesten, tutkijoiden, poliitikkojen ja yksittäisten ihmisten keskuudessa. Yksi käytännön esimerkki digitalisaation vaikutuksista on Uber, jonka toimintatapa muuttaa taksiliiketoimintaa luoden samalla malleja koko kuljetustoimialalle ja vaikuttaen jopa kaupunkisuunnitteluun. Esimerkki valaisee myös sitä, miten digitalisaatio tarjoaa merkittäviä voittoja yksille ja kohtalokkaita tappioita toisille, kuten Schumpeter kuvasi ”luovan tuhon” ajatuksessaan jo vuonna 1942. Digitalisaatio ei ole yksittäinen tuote tai palvelu, vaan se on tuotteita, palveluita ja konsepteja, joita useat digitaaliset teknologiat systeemisesti mahdollistavat. Systeemisyys yksinkertaisten syy–seuraus-suhteiden sijaan tekee vaikutusten ymmärtämisen ja ennustamisen vaikeaksi. Perinteisiä strategisen johtamisen teorioita ja viitekehyksiä käytetään yritysten suorituskyvyn analysointiin ja sen ymmärtämiseksi, millä toimenpiteillä yritykset menestyisivät. Lisäksi monet ylimmät johdon työkalut helpottavat näkemään liiketoimintaympäristön muutoksia ja tarjoavat tukea oikeiden strategisten valintojen tekemiseen, mutta niissä on heikkouksia systeemisten ilmiöiden havaitsemiseksi. Behavioristinen taloustiede ja johtamisen kognitiotieteet auttavat ymmärtämään, miksi oikeat strategiset valinnat, jotka muuttavat vallitsevia uskomuksia, ovat vaikeita yksilötasolla.Tämä väitöstutkimus tutki digitalisaation vaikutusta koneenrakennustoimialaan, joka palvelee maailmanlaajuista kontinkäsittelyä – satamia ja terminaaleja. Toimiala on perinteinen, siinä on suhteellisen vähän globaaleja toimijoita ja se sitoo paljon pääomaa. Tutkimus lähestyi ongelmaa arvoketjun näkökulmasta siten, että koneenrakentajat ovat toimijoita, jotka soveltavat digitaalisia teknologioita, joita puolestaan mahdollistajat toimittavat. Arvo syntyy lopullisesti käyttäjille, joita ovat satamat ja terminaalit. Tutkimuksen tavoitteena oli lisätä ymmärrystä digitalisaation mahdollisesti aiheuttamasta murroksesta tai muutoksesta nykyiseen arvonluontimalliin sekä siitä, mitkä tekijät hidastavat tätä kehitystä. Koska mahdollinen muutos on meneillään, käsitysten erovaisuuksien ymmärtäminen arvoketjussa mahdollistajien, toimijoiden ja käyttäjien kesken on tärkeää. Tutkimuksen päämenetelmä oli kahden haastattelukierroksen Delfoi-tekniikka sekä tulosten validiteetin parantamiseksi käytetyt kyselytutkimus sekä kolme case-kuvausta.Tietomassojen suurtehokäsittely (Big Data) yhdessä tekoälyn (Artificial Intelligence) kanssa nousi tärkeimmäksi mahdollisen murroksen aikaansaavaksi digitaaliseksi teknologiaksi. Empiiriset tulokset osoittivat, että kyseiset teknologiat vaikuttavat uuden tietämyksen syntyyn ja että ilmiö kiihtyy, koska koneet ja niiden komponentit liittyvät kiihtyvässä tahdissa tietoverkkoihin. Kyseiset teknologiat kehittyvät edelleen samalla kun niiden käytön kustannukset laskevat. Nämä teknologiat palvelevat useita toimialoja, mutta koneenrakentajilla itsellään on vähäinen vaikutus teknologian kustannuksiin, nopeuteen, saatavuuteen, ominaisuuksiin tai niiden kehittymiseen.Empiiriset tulokset osoittivat myös, että tieteenhaara tai toimialapohjaiset alustat ovat voimakkaimmat potentiaalista murrosta aiheuttavat taloudelliset konseptit tämän tutkimuksen rajauksella. Alustat ovat uusia elementtejä, joilla on merkittävä vaikutus toimialan dynamiikkaan, mutta perinteisten yritysten johdolla on harvoin omaan opiskeluun tai kokemukseen perustuvaa osaamista niistä. Alustat saavat voimansa verkostovaikutuksista, joissa tietotyöläiset, startupit ja monikansalliset yritykset luovat yhdessä arvoa. Koneenrakentajat eivät pysty estämään alustojen syntymistä tai merkittävästi hidastamaan niiden kehitystä. Ne voivat ohittaa ilmiön, sopeutua siihen tai mahdollisuuksiensa ja kyvykkyyksiensä puitteissa luoda oman alustastrategiansa.Merkittävä osa ajureista, jotka kiihdyttävät digitaalisia konsepteja, ovat perinteisiä ja rationaalisia, kuten tuottavuus, läpimenoajat, ominaisuudet, laatu tai kustannukset. Osa kehitystä hidastavista ajureista on helposti tunnistettavissa, kuten 3D-tulostimen nopeus tai kuinka moni käyttäjä antaa pääsyn dataansa. Huoli tietoturvasta hidastaa investointeja, ja olemassa olevien prosessien ja järjestelmien vaihtaminen on aikaa vievää. Empiiriset tulokset osoittivat kuitenkin, että voimakkaimmat hidasteet liittyivät suoraan ihmisiin ja päätöksentekoon. Kolme merkittävintä ihmisiin liittyvää hidastetta olivat systeemisten ilmiöiden huono ymmärtäminen, johdon uskomukset ja kyvykkyyksien puute. Tulosten merkitys käytännön strategiselle johtamiselle kiteytyy kahteen asiaan. Ensinnäkin johdon pitää ymmärtää ja uskoa, että digitaalisuus murtaa joiltakin osin nykyisen liiketoiminnan, ja toiseksi kehitys on niin monisyistä, ettei menestystä voi kovinkaan tarkasti suunnitella etukäteen. Osa tutkimuksessa käytetystä kirjallisuudesta ja Delfoihaastatteluista saadut tulokset painottavat tällaisessa tilanteessa yrittäjyysmäistä ajattelutapaa ja paljon pieniä kokeiluja, joissa hyödynnetään ulkoisten verkostojen tietämystä. Toimintatapa mahdollistaa sen, että strategia voidaan luoda oppimalla, mikä samanaikaisesti kehittää kyvykkyyksiä, joita tarvitaan tieto- ja käyttäjäkeskeisissä liiketoimintaympäristöissä

AGILE Paradigm: The next generation collaborative MDO for the development of aeronautical systems

The research and innovation EU funded AGILE project has developed the next generation of aircraft Multidisciplinary Design and Optimization (MDO) processes, which target significant reductions in aircraft development costs and time to market, leading to more cost-effective and greener aircraft solutions. 19 industry, research and academia partners from Europe, Canada and Russia have developed solutions to cope with the challenges of collaborative design and optimization of complex aeronautical products. In order to accelerate the deployment of large-scale, collaborative multidisciplinary design and optimization, a novel approach, the so-called “AGILE Paradigm”, has been conceived. The AGILE Paradigm is defined as a “blueprint for MDO”, accelerating the deployment and the operations of collaborative “MDO systems” and enabling the development of complex products practiced by multi-site and cross-organizational design teams, having heterogeneous expertise. A set of technologies has been developed by the AGILE consortium to enable the implementation of the AGILE Paradigm principles, thus delivering not only an abstract formalization of the approach, but also an applicable framework. The collection of all the technologies constitutes the so-called “AGILE Framework”, which has been applied for the design and the optimization of multiple aircraft configurations. The ambition of the AGILE Paradigm was set to reduce the lead time of 40% with respect to the current state-of-the-art. This work reviews the evolution of the MDO systems, underlines the open challenges tackled by the AGILE project, and introduces the main architectural concepts behind the AGILE Paradigm. Thereafter, an overview of the application design cases is presented, focusing of the main challenges and achievements. The AGILE technologies enabled the consortium to formulate and to solve in 15 months 7 MDO applications in parallel for the development of 7 novel aircraft configurations, demonstrating time savings beyond the 40% goal

The Essence of Software Engineering

Software Engineering; Software Development; Software Processes; Software Architectures; Software Managemen

More than 10 years of industry 4.0 in the Netherlands:an opinion on promises, achievements, and emerging challenges

The concept of Industry 4.0, as a means to move forward in the industrial ecosystem, has reached an important turning point. Where do we stand now in terms of industrial innovation and transition? This opinion paper provides an overview of the situation in the Netherlands, a reflection on what has been achieved by the Industry 4.0 paradigm, and the necessary way forward to solidify its implementation. Tentative results reveal that the pervasiveness of Industry 4.0 applications is sector-specific. This work provides industrial stakeholders and academics with useful suggestions and a possible path to move towards better integration of Industry 4.0 in company reality. In this opinion paper, we employ a mixed methods research methodology to argue that, based on our findings on industrial adaptation in The Netherlands, Industry 4.0 is the outcome of an evolutionary process and not of a revolution, as it is often claimed