The Software Value Chain as an Analytical Framework for the Software Industry and Its Exemplary Application for Vertical Integration Measurement

The value chain concept disaggregates a firm into the various activities it performs. Abstracting from the firm-level thisconcept has also been applied to industries as a whole. In this paper we conceptualize a software specific value chain andprovide a first proof of concept. Our approach aggregates and unifies findings from a literature review on industry-level valuechains, software value chains, and related concepts. The resulting unified software value chain comprises eleven activities:product research, component procurement, product development, user documentation, production and packaging, marketing,implementation, training and certification, maintenance and support, operations, and replacement. A first proof of concept isprovided through expert interviews with software firms. Furthermore, we present an example that shows how the softwarevalue chain can be applied to measure the degree of vertical integration in the software industry

A NEW METHODOLOGICAL APPROACH FOR DESIGNING THE SOFTWARE INDUSTRY VALUE CHAIN

The importance of the software industry today is increasing because of its dispersive effects on the development of other industries. In this context, the software industry value chain analysis is a useful methodological approach that allows better understanding of software industry potentials for achieving increased efficiency and competitiveness. Hence, the main objective of this paper is to offer a new conceptual framework for the software industry value chain that will reflect the contemporary changes in this sector. The new model includes: a) identification of the key activities in the software industry; b) a new approach of sequencing the stages in the value chain; c) systematization of activities within each phase; and d) identification of interrelations and linkages in the chai

THE SOFTWARE VALUE CHAIN: METHODS FOR CONSTRUCTION AND THEIR APPLICATION

The value chain is a widely used framework for industry and firm analysis. To our knowledge, the conceptualisation of value chains is so far guided by soft criteria like intuition of experts rather than clearly stated methods with regard to the value chain boundaries and the granularity as well as the separation of activities. Therefore, we propose a combination of well-known methods - such as the Delphi study approach and clustering algorithms - to (1) ensure a holistic view of the industry at hand by covering all underlying economic concepts, (2) ensure the uniqueness of activities, and (3) provide a hierarchy of activities that allows deriving value chains at different levels of granularity. Since software is a good with specific economic properties, practitioners and researchers require a value chain framework reflecting the industry specifics. This paper contributes by proposing methods for value chain construction and applying these methods to the software industry. The resulting universal and hierarchical software value chain can serve as a sound foundation for further studies of the software industry. Furthermore, practitioners can tailor the proposed methods to their needs and apply the software value chain to their firms

D5.2: Digital-Twin Enabled multi-physics simulation and model matching

This deliverable presents a report on the developed actions and results concerning Digital-Twin-enabled multi-physics simulations and model matching. Enabling meaningful simulations within new human-infrastructure interfaces such as Digital twins is paramount. Accessing the power of simulation opens manifold new ways for observation, understanding, analysis and prediction of numerous scenarios to which the asset may be faced. As a result, managers can access countless ways of acquiring synthetic data for eventually taking better, more informed decisions. The tool MatchFEM is conceived as a fundamental part of this endeavour. From a broad perspective, the tool is aimed at contextualizing information between multi-physics simulations and vaster information constructs such as digital twins. 3D geometries, measurements, simulations, and asset management coexist in such information constructs. This report provides guidance for the generation of comprehensive adequate initial conditions of the assets to be used during their life span using a DT basis. From a more specific focus, this deliverable presents a set of exemplary recommendations for the development of DT-enabled load tests of assets in the form of a white paper. The deliverable also belongs to a vaster suit of documents encountered in WP5 of the Ashvin project in which measurements, models and assessments are described thoroughly.Objectius de Desenvolupament Sostenible::9 - Indústria, Innovació i InfraestructuraPreprin

A Literature Overview on Strategic Information Systems Planning

Strategic Information Systems Planning (SISP) has been among the highest ranked issues on management agendas for many years. As such, SISP should be a major concern for researchers as well. However, SISP does not play that important of a role in the academic discussion, at least in Germany. Leading German textbooks on Information Management devote only small sections to strategy themes. Moreover, the recommendations given for conducting SISP in these textbooks are mainly normative and hardly take international research findings into account. Taking this as a motivation, we conducted a comprehensive literature review of German and Anglo-American information systems journals. Our objective was to understand more fully what we know about SISP through international research. On the flip side, our research aims at identifying fields that are in urgent need for closer academic investigation so that individual speculations and normative recommendations might still substitute for valid research insights. Overall, we found a considerable amount of research conducted in the field of SISP that we organised in five broad thematic fields: Strategic IT impact, approaches to SISP, information systems strategy, and strategic alignment. We give a short overview of research conducted so far and seminal publications available in the research fields. Moreover, based on a sub-sample of our literature base, we compute statistics which indicate the intensity of the academic discussion in the different thematic fields over time. Our statistics show that most attention has been paid to the competitive use of IT. The IS strategy in contrast has only been of limited interest, though it is central to any strategic considerations in IS. Our survey also suggests that German speaking researchers have devoted relatively few efforts to SISP in comparison to their Anglo-American colleagues

Applying Operational Business Intelligence in Production Environments

Operational Business Intelligence (OpBI) discusses a possible support of production-specific decisions by integrating and analyzing production data. The discussion of OpBI focusses thereby rather on common applicability aspects than on certain implementation strategies. This is however less conclusive for a functional reliability of OpBI in production environments and for associated efforts. Therefore, we introduce an OpBI framework to integrate and analyze data of production processes automatically. Following principles of design science research, framework evaluation refers to real-world data from a rod and wire rolling process. In conclusion, our OpBI framework improves information quality perceived by end users analyzing a steel’s rolling behavior

Integrated CO2e assessment and decision support model for supplier selections

The fast growing stakeholder interest in sustainability leads to an increased attention both on the ecological and social perspective of industrial companies and its products. While in the past the focus predominantly laid on the environmental impact of the product use phase, it recently shifted towards the manufacturing phase. Hence, both, focal companies and supply chain members are obliged to create and apply new strategies to reduce greenhouse gas emissions (GHG). From a purchasing perspective, the selection of more environmentally efficient suppliers is a possibility to significantly reduce CO$_{2}$e emissions. Therefore, transparency is required in form of site-specific and comparable data on suppliers’ environmental performance. This data is lacking and the detailed environmental performance criteria has not been integrated in supplier selection decisions yet. In this dissertation a model is developed and applied to close the transparency gap and to integrate CO$_{2}$e as an additional supplier selection criteria in decision-making. For this purpose, a multi-criteria decision analysis approach is developed to derivate criteria weights and a supplier ranking based on expert opinion and quantitative supplier performance data. As decision making based on expert consultation is associated with a certain level of subjectivity, a sensitivity analysis is performed to evaluate the robustness of the model and the results. By means of ‘what-if’ scenario simulations, the dynamic behavior of the model is further investigated to examine how decisions may change when CO$_{2}$e is formulated and considered as a new criteria. In addition, a systematic and modular Life Cycle Assessment (LCA) based approach is developed to enable an efficient evaluation and comparability of the sustainability performance of raw material suppliers on a production site level, based on publically available data. The model combines a bottom-up calculation of technical process flows with top-down reported site-specific CO$_{2}$ emissions, and explicitly considers technical restrictions and trading of inter-mediate products. The developed site-specific performance model is applied in two case studies for primary steel production sites in Europe and primary aluminum sites in Germany. The results, which were validated with industry experts, differ by 58 % for the comparison between the most and least efficient production site for steel and by 9 % for the examined aluminum production sites and show an opportunity to reduce GHG emissions by selecting more environmentally efficient suppliers. The combined, integrated CO$_{2}$e assessment and decision support model is subsequently applied on an automotive case study for the selection of the most adequate supplier for a powertrain part from an environmental and economic efficiency perspective. The results show that in some cases the integration of the CO$_{2}$e performance can have a significant impact on the ranking of the most preferable supplier, despite an initially investigated low importance of the new CO$_{2}$e decision criteria

Towards edge robotics: the progress from cloud-based robotic systems to intelligent and context-aware robotic services

Current robotic systems handle a different range of applications such as video surveillance, delivery of goods, cleaning, material handling, assembly, painting, or pick and place services. These systems have been embraced not only by the general population but also by the vertical industries to help them in performing daily activities. Traditionally, the robotic systems have been deployed in standalone robots that were exclusively dedicated to performing a specific task such as cleaning the floor in indoor environments. In recent years, cloud providers started to offer their infrastructures to robotic systems for offloading some of the robot’s functions. This ultimate form of the distributed robotic system was first introduced 10 years ago as cloud robotics and nowadays a lot of robotic solutions are appearing in this form. As a result, standalone robots became software-enhanced objects with increased reconfigurability as well as decreased complexity and cost. Moreover, by offloading the heavy processing from the robot to the cloud, it is easier to share services and information from various robots or agents to achieve better cooperation and coordination. Cloud robotics is suitable for human-scale responsive and delay-tolerant robotic functionalities (e.g., monitoring, predictive maintenance). However, there is a whole set of real-time robotic applications (e.g., remote control, motion planning, autonomous navigation) that can not be executed with cloud robotics solutions, mainly because cloud facilities traditionally reside far away from the robots. While the cloud providers can ensure certain performance in their infrastructure, very little can be ensured in the network between the robots and the cloud, especially in the last hop where wireless radio access networks are involved. Over the last years advances in edge computing, fog computing, 5G NR, network slicing, Network Function Virtualization (NFV), and network orchestration are stimulating the interest of the industrial sector to satisfy the stringent and real-time requirements of their applications. Robotic systems are a key piece in the industrial digital transformation and their benefits are very well studied in the literature. However, designing and implementing a robotic system that integrates all the emerging technologies and meets the connectivity requirements (e.g., latency, reliability) is an ambitious task. This thesis studies the integration of modern Information andCommunication Technologies (ICTs) in robotic systems and proposes some robotic enhancements that tackle the real-time constraints of robotic services. To evaluate the performance of the proposed enhancements, this thesis departs from the design and prototype implementation of an edge native robotic system that embodies the concepts of edge computing, fog computing, orchestration, and virtualization. The proposed edge robotics system serves to represent two exemplary robotic applications. In particular, autonomous navigation of mobile robots and remote-control of robot manipulator where the end-to-end robotic system is distributed between the robots and the edge server. The open-source prototype implementation of the designed edge native robotic system resulted in the creation of two real-world testbeds that are used in this thesis as a baseline scenario for the evaluation of new innovative solutions in robotic systems. After detailing the design and prototype implementation of the end-to-end edge native robotic system, this thesis proposes several enhancements that can be offered to robotic systems by adapting the concept of edge computing via the Multi-Access Edge Computing (MEC) framework. First, it proposes exemplary network context-aware enhancements in which the real-time information about robot connectivity and location can be used to dynamically adapt the end-to-end system behavior to the actual status of the communication (e.g., radio channel). Three different exemplary context-aware enhancements are proposed that aim to optimize the end-to-end edge native robotic system. Later, the thesis studies the capability of the edge native robotic system to offer potential savings by means of computation offloading for robot manipulators in different deployment configurations. Further, the impact of different wireless channels (e.g., 5G, 4G andWi-Fi) to support the data exchange between a robot manipulator and its remote controller are assessed. In the following part of the thesis, the focus is set on how orchestration solutions can support mobile robot systems to make high quality decisions. The application of OKpi as an orchestration algorithm and DLT-based federation are studied to meet the KPIs that autonomously controlledmobile robots have in order to provide uninterrupted connectivity over the radio access network. The elaborated solutions present high compatibility with the designed edge robotics system where the robot driving range is extended without any interruption of the end-to-end edge robotics service. While the DLT-based federation extends the robot driving range by deploying access point extension on top of external domain infrastructure, OKpi selects the most suitable access point and computing resource in the cloud-to-thing continuum in order to fulfill the latency requirements of autonomously controlled mobile robots. To conclude the thesis the focus is set on how robotic systems can improve their performance by leveraging Artificial Intelligence (AI) and Machine Learning (ML) algorithms to generate smart decisions. To do so, the edge native robotic system is presented as a true embodiment of a Cyber-Physical System (CPS) in Industry 4.0, showing the mission of AI in such concept. It presents the key enabling technologies of the edge robotic system such as edge, fog, and 5G, where the physical processes are integrated with computing and network domains. The role of AI in each technology domain is identified by analyzing a set of AI agents at the application and infrastructure level. In the last part of the thesis, the movement prediction is selected to study the feasibility of applying a forecast-based recovery mechanism for real-time remote control of robotic manipulators (FoReCo) that uses ML to infer lost commands caused by interference in the wireless channel. The obtained results are showcasing the its potential in simulation and real-world experimentation.Programa de Doctorado en Ingeniería Telemática por la Universidad Carlos III de MadridPresidente: Karl Holger.- Secretario: Joerg Widmer.- Vocal: Claudio Cicconett

Knowledge Management in the Fourth Industrial Revolution: Mapping the Literature and Scoping Future Avenues

Due to increased competitive pressure, modern organizations tend to rely on knowledge and its exploitation to sustain a long-term advantage. This calls for a precise understanding of knowledge management (KM) processes and, specifically, how knowledge is created, shared/transferred, acquired, stored/retrieved, and applied throughout an organizational system. However, since the beginning of the new millennium, such KM processes have been deeply affected and molded by the advent of the fourth industrial revolution, also called Industry 4.0, which involves the interconnectedness of machines and their ability to learn and share data autonomously. For this reason, the present study investigates the intellectual structure and trends of KM in Industry 4.0. Bibliometric analysis and a systematic literature review are conducted on a total of 90 relevant articles. The results reveal 6 clusters of keywords, subsequently explored via a systematic literature review to identify potential stream of this emergent field and future research avenues capable of producing meaningful advances in managerial knowledge of Industry 4.0 and its consequences

Modelling Event-Based Interactions in Component-Based Architectures for Quantitative System Evaluation

This dissertation thesis presents an approach enabling the modelling and quality-of-service prediction of event-based systems at the architecture-level. Applying a two-step model refinement transformation, the approach integrates platform-specific performance influences of the underlying middleware while enabling the use of different existing analytical and simulation-based prediction techniques