Industry 4.0 is becoming more and more important for manufacturers as the developments in the area of Internet of Things advance. Another technology gaining more attention is data stream processing systems. Although such streaming frameworks seem to be a natural fit for Industry 4.0 scenarios, their application in this context is still low. The contributions in this paper are threefold. Firstly, we present industry findings that we derived from site inspections with a focus on Industry 4.0. Moreover, our view on Industry 4.0 and important related aspects is elaborated. As a third contribution, we illustrate our opinion on why data stream processing technologies could act as an enabler for Industry 4.0 and point out possible obstacles on this way.
Another work presents design principles for Industry 4.0 that are derived through text analysis and literature studies @cite_5 . Thereby, it is aimed to help both, the scientific community and practitioners with this result. In total, four design principles were identified, namely technical assistance, interconnection, decentralized decisions, and information transparency.
@cite_5
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The increasing integration of the Internet of Everything into the industrial value chain has built the foundation for the next industrial revolution called Industrie 4.0. Although Industrie 4.0 is currently a top priority for many companies, research centers, and universities, a generally accepted understanding of the term does not exist. As a result, discussing the topic on an academic level is difficult, and so is implementing Industrie 4.0 scenarios. Based on a quantitative text analysis and a qualitative literature review, the paper identifies design principles of Industrie 4.0. Taking into account these principles, academics may be enabled to further investigate on the topic, while practitioners may find assistance in identifying appropriate scenarios. A case study illustrates how the identified design principles support practitioners in identifying Industrie 4.0 scenarios. Whether a marketing campaign or a museum exhibit, a video game or a complex control system, the design we see is the culmination of many concepts and practices brought together from a variety of disciplines. Because no one can be an expert on everything, designers have always had to scramble to find the information and know-how required to make a design work-until now. Universal Principles of Design is the first comprehensive, cross-disciplinary encyclopedia of design. Richly illustrated and easy to navigate, it pairs clear explanations of every design concept with visual examples of the concepts applied in practice. From the "80 20" rule to chunking, from baby-face bias to Occam's razor, and from self-similarity to storytelling, every major design concept is defined and illustrated for readers to expand their knowledge. This landmark reference will become the standard for designers, engineers, architects, and students who seek to broaden and improve their design expertise. This book is an introductory text on design science, intended to support both graduate students and researchers in structuring, undertaking and presenting design science work. It builds on established design science methods as well as recent work on presenting design science studies and ethical principles for design science, and also offers novel instruments for visualizing the results, both in the form of process diagrams and through a canvas format. While the book does not presume any prior knowledge of design science, it provides readers with a thorough understanding of the subject and enables them to delve into much deeper detail, thanks to extensive sections on further reading. Design science in information systems and technology aims to create novel artifacts in the form of models, methods, and systems that support people in developing, using and maintaining IT solutions. This work focuses on design science as applied to information systems and technology, but it also includes examples from, and perspectives of, other fields of human practice. Chapter 1 provides an overview of design science and outlines its ties with empirical research. Chapter 2 discusses the various types and forms of knowledge that can be used and produced by design science research, while Chapter 3 presents a brief overview of common empirical research strategies and methods. Chapter 4 introduces a methodological framework for supporting researchers in doing design science research as well as in presenting their results. This framework includes five core activities, which are described in detail in Chapters 5 to 9. Chapter 10 discusses how to communicate design science results, while Chapter 11 compares the proposed methodological framework with methods for systems development and shows how they can be combined. Chapter 12 discusses how design science relates to research paradigms, in particular to positivism and interpretivism. Lastly, Chapter 13 discusses ethical issues and principles for design science research. Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizontal, and decentralized item-level production control framework. Structured interoperability via precise formulations on an appropriate degree is crucial to achieve engineering efficiency in the system life cycle. However, selecting the degree of formalization can be challenging, as it crucially depends on the desired common understanding (semantic degree) between multiple parties. In this paper, we categorize different semantic degrees and map a set of technologies in industrial automation to their associated degrees. Furthermore, we created guidelines to assist engineers selecting appropriate semantic degrees in their design. We applied these guidelines on publically available scenarios to examine the validity of the approach, and identified semantic elements over internally developed use cases targeting semantically-enabled plug-and-produce. Under the context of Industrie 4.0 (I4.0), future production systems provide balanced operations between manufacturing flexibility and efficiency, realized in an autonomous, horizontal, and decentralized item-level production control framework. Structured interoperability via precise formulations on an appropriate degree is crucial to achieve software engineering efficiency in the system life cycle. However, selecting the degree of formalization can be challenging, as it crucially depends on the desired common understanding (semantic degree) between multiple parties. In this paper, we categorize different semantic degrees and map a set of technologies in industrial automation to their associated degrees. Furthermore, we created guidelines to assist engineers selecting appropriate semantic degrees in their design. We applied these guidelines on publicly available scenarios to examine the validity of the approach, and identified semantic elements over internally developed use cases concerning plug-and-produce. In this paper, we propose a new framework for the organization of the electric power industry, based on extensive use of information technology (IT) and on interactive decision making, where consumers and distributed producers join the traditional actors, utilities in particular, in making decisions. While many ideas considered in this paper have been put forward in recent years, such as the need to manage intermittency of renewable resources by means of proactive forecasting, and coordination with responsive demand and storage, we introduce a possible systematic IT-enabled mechanism necessary for the actual implementation of these technologies. We point out that in order to achieve a long-term sustainable energy utilization, it is essential to provide on-line information to internalize the value of just-in-time, just-in-place, and just-in-context distributed adaptation across the entire supply chain, ranging from the smallest consumers and energy providers, through their aggregators and system coordinators. We illustrate using our model-based novel simulator, how a carefully designed multidirectional and multitemporal information exchange could enable sustainable decision making while accounting for unique needs and capabilities of various resources and users. At the same time, information incentivizes the resources and users to contribute to system-wide sustainability objectives at value. We illustrate the dependence of such decisions-driven industry evolution on the industry rules (choice of performance objectives), as well as on the operating and planning practices for implementing the industry rules (temporal and spatial factors). Our model-based simulator could be used as a means of designing novel regulation defining rules, rights, and responsibilities regarding the type and rate of information to be exchanged in support of sustainable industry evolution. Abstract Context For many years, we have observed industry struggling in defining a high quality requirements engineering (RE) and researchers trying to understand industrial expectations and problems. Although we are investigating the discipline with a plethora of empirical studies, they still do not allow for empirical generalisations. Objective To lay an empirical and externally valid foundation about the state of the practice in RE, we aim at a series of open and reproducible surveys that allow us to steer future research in a problem-driven manner. Method We designed a globally distributed family of surveys in joint collaborations with different researchers and completed the first run in Germany. The instrument is based on a theory in the form of a set of hypotheses inferred from our experiences and available studies. We test each hypothesis in our theory and identify further candidates to extend the theory by correlation and Grounded Theory analysis. Results In this article, we report on the design of the family of surveys, its underlying theory, and the full results obtained from Germany with participants from 58 companies. The results reveal, for example, a tendency to improve RE via internally defined qualitative methods rather than relying on normative approaches like CMMI. We also discovered various RE problems that are statistically significant in practice. For instance, we could corroborate communication flaws or moving targets as problems in practice. Our results are not yet fully representative but already give first insights into current practices and problems in RE, and they allow us to draw lessons learnt for future replications. Conclusion Our results obtained from this first run in Germany make us confident that the survey design and instrument are well-suited to be replicated and, thereby, to create a generalisable empirical basis of RE in practice. Information shying and decision coordination arc central problems for collaborative product dcvclopmcnt and enterprise-wide coordination. Designcrs, manufacturing cnginccrs, and marketing engineers nccd to assess the impact of their decisions and notify affected parties as the product evolves. Yct, cxisting CAD tools tend to isolate information at tool boundarics, or make overly-strong commitmcnts to an all-encompassing common model. Furthcrmorc, there is oftcn no automatcd support outside of thc design function. The SHADE (SHAred Dcpcndcncy Engineering) project is working on knowlcdge-b cd methods to improve the communication in the product dcvclopmcnt process. Thcre arc three mare components of SHADE: a shared knowledge representation (language and domain-specific vocabulary); protocols for information cxch,’mgc enabling change notification and subscription; and facilitation scrviccs such ,as contcnt-dircctcd routing , nd intelligent matching of information consumers and producers. SHADE is being applied to sew’r d real domains, including the Palo Alto Collaborative Tcstbcd. 0 Introduction.- I Themes and Problems.- 1.0 Introduction.- 1.1 The theory of finance capital.- 1.2 Interlocking directorates and economic power.- 1.3 Financial groups.- 1.4 Corporate elite and capitalist class.- 1.5 Summary.- II Between Market and Hierarchy.- 2.0 Introduction.- 2.1 The organization of firms and markets: a neo-classical explanation.- 2.2 Some definitions of firms.- 2.3 Power and control.- 2.4 Ownership and control.- 2.5 Competition, cooperation and control.- 2.5.1 Concentration and centralization.- 2.5.2 The level-of-analysis problem.- 2.6 Summary.- III Imperialism in the Seventies: two models.- 3.0 Introduction.- 3.1 Theories of imperialism.- 3.1.1 Their origins.- 3.1.2 After World War II.- 3.2 Two models.- 3.3 Research design.- 3.4 Summary.- IV The International Corporate Elite.- 4.0 Introduction.- 4.1 The organization of the supervising and executive function in different countries.- 4.2 Selection of the international corporate elite.- 4.3 Network characteristics of the international corporate elite.- 4.3.0 Introduction.- 4.3.1 The finance capitalists.- 4.3.2 The big linkers.- 4.4 Types of interlocking directorates.- 4.4.0 Introduction.- 4.4.1 Multiple interlocks.- 4.5 Summary.- V National Versus International Integration.- 5.0 Introduction to some graph-theoretical concepts.- 5.1 General patterns in the international network.- 5.1.1 Compactness of the international network.- 5.1.2 International integration of national networks.- 5.2 The international network of Western firms.- 5.2.0 Introduction.- 5.2.1 Local centrality.- 5.2.2 Global centrality.- 5.2.3 Overall centrality.- 5.3 Industrial concentration versus economic centralization.- 5.4 Summary.- VI Domination and Control.- 6.0 Introduction.- 6.1 Clusters of heavily interlocked firms.- 6.1.1 The network at multiplicity-level two.- 6.1.2 The network at multiplicity-level three.- 6.1.3 Conclusions.- 6.2 The network of officer-interlocks.- 6.2.0 Introduction.- 6.2.1 Domination and control.- 6.2.1.1 The network of all officer-interlocks.- 6.2.1.2 The network of control.- 6.2.2 Financial groups.- 6.2.3 Constellations of interests.- 6.3 Summary.- VII Competition and Cooperation: the role of banks.- 7.0 Introduction.- 7.1 Interlocks among banks.- 7.2 Overlapping spheres of interests.- 7.3 International bank consortia.- 7.4 The American banks.- 7.5 Summary.- VIII The Impact of World Crisis: changes in the network.- 8.0 Introduction.- 8.1 A new economic world order?.- 8.2 Selection of the 1976 sample.- 8.3 The international corporate elite.- 8.3.1 Finance capitalists.- 8.3.2 Big linkers.- 8.4 International versus national integration.- 8.5 Centrality in the nested networks (1976).- 8.6 Domination and control in the 1976 network.- 8.7 Summary.- IX Summary and Conclusions.- 9.1 Introduction.- 9.2 The structure of the international corporate elite.- 9.3 Conflict or cooperation.- 9.4 The meaning of interlocking directorates.- 9.5 The international corporate elite.- References.- Authors Index.- Firms Index.- Appendix A. Abstract This paper is a study on the importance of drawing (both formal drafting and informal sketching) during the process of mechanical design. Five hypotheses, focused on the types of drawings, their necessity in mechanical problem solving, and their relation to the external representation medium, are presented and supported. Support is through referenced studies in other domains and the results of protocol studies performed on five mechanical designers. Videotapes of all the marks-on-paper made by designers in representative sections of the design process were studied in detail for their type and purpose. The resulting data is supportive of the hypotheses. These results also give requirements for future computer aided design tools and graphics education, and goals for further studies. The publication of the work on design science by Alan Hevner and his colleagues has fostered much discussion on what is and what is not considered to be design science in Information Systems (IS) research. Anecdotal evidence suggests that some authors claim design science as a methodology in their work, without much consideration of theoretical or methodological aspects, or the appropriateness of their artefact. Also it would appear that design science papers have been proliferating rapidly of late. Accordingly, we were interested to identify the proliferation, nature and quality of design science research in Information Systems conference publications since the publication of ’s work in 2004. We examine design science articles published at five major IS conferences over the last three years. We subject 83 articles, identified as relevant via a rigorous analysis process, to three types of analysis - statistical, thematic and methodological. The results of these analyses indicate that design science appears to be a growing stream of research in IS. We also found design science research to be strongly prevalent in the research domains of process, knowledge and information management. The most interesting results stem out of our methodological analysis, which suggests that only a small percentage of the papers discuss a concise and consistent implementation of the design science methodology suggested by The Industry 4.0 is a vision that includes connecting more intensively physical systems with their virtual counterparts in computers. This computerization of manufacturing will bring many advantages, including allowing data gathering, integration and analysis in the scale not seen earlier. In this paper we describe our Semantic Big Data Historian that is intended to handle large volumes of heterogeneous data gathered from distributed data sources. We describe the approach and implementation with a special focus on using Semantic Web technologies for integrating the data. Structured design methodologies provide a disciplined and organized guide to the construction of software systems. However, while the methodology structures and documents the points at which design decisions are made, it does not provide a specific, quantitative basis for making these decisions. Typically, the designers' only guidelines are qualitative, perhaps even vague, principles such as "functionality," "data transparency," or "clarity." This paper, like several recent publications, defines and validates a set of software metrics which are appropriate for evaluating the structure of large-scale systems. These metrics are based on the measurement of information flow between system components. Specific metrics are defined for procedure complexity, module complexity, and module coupling. The validation, using the source code for the UNIX operating system, shows that the complexity measures are strongly correlated with the occurrence of changes. Further, the metrics for procedures and modules can be interpreted to reveal various types of structural flaws in the design and implementation. A growing number of information technology systems and services are being developed to change users’ attitudes or behavior or both. Despite the fact that attitudinal theories from social psychology have been quite extensively applied to the study of user intentions and behavior, these theories have been developed for predicting user acceptance of the information technology rather than for providing systematic analysis and design methods for developing persuasive software solutions. This article is conceptual and theory-creating by its nature, suggesting a framework for Persuasive Systems Design (PSD). It discusses the process of designing and evaluating persuasive systems and describes what kind of content and software functionality may be found in the final product. It also highlights seven underlying postulates behind persuasive systems and ways to analyze the persuasion context (the intent, the event, and the strategy). The article further lists 28 design principles for persuasive system content and functionality, describing example software requirements and implementations. Some of the design principles are novel. Moreover, a new categorization of these principles is proposed, consisting of the primary task, dialogue, system credibility, and social support categories. In the field of infrastructures’ surveillance and protection, it is important to make decisions based on activities occurring in the environment and its local context and conditions. In this paper we use an active rule based event processing architecture in order to make sense of situations from the combination of different signals received by the rule engine. However obtaining some high level information automatically is not without risks, especially in sensitive environments, and detection mistakes can happen for various reasons: the signal’s source can be defective, whether it is human—miss-interpretation of the signal—or computed—material malfunction; the aggregation rules can be wrong syntaxically, for example when a rule will never be triggered or a situation never detected; the interpretation given to the combination of signals does not correspond to the reality on the field—because the knowledge of the rule designer is subjective or because the environment evolves over-time—the rules are therefore incorrect semantically. In this paper, a new approach is proposed to avoid the third kind of error sources. We present a hybrid machine learning technique adapted to the complexity of the rules’ representation, in order to create a system more conform to reality. The proposed approach uses a combination of an Association Rule Mining algorithm and Inductive Logic Programming for rule induction. Empirical studies on simulated datasets demonstrate how our method can contribute to sensible systems such as the security of a public or semi-public place. Design studies are an increasingly popular form of problem-driven visualization research, yet there is little guidance available about how to do them effectively. In this paper we reflect on our combined experience of conducting twenty-one design studies, as well as reading and reviewing many more, and on an extensive literature review of other field work methods and methodologies. Based on this foundation we provide definitions, propose a methodological framework, and provide practical guidance for conducting design studies. We define a design study as a project in which visualization researchers analyze a specific real-world problem faced by domain experts, design a visualization system that supports solving this problem, validate the design, and reflect about lessons learned in order to refine visualization design guidelines. We characterize two axes - a task clarity axis from fuzzy to crisp and an information location axis from the domain expert's head to the computer - and use these axes to reason about design study contributions, their suitability, and uniqueness from other approaches. The proposed methodological framework consists of 9 stages: learn, winnow, cast, discover, design, implement, deploy, reflect, and write. For each stage we provide practical guidance and outline potential pitfalls. We also conducted an extensive literature survey of related methodological approaches that involve a significant amount of qualitative field work, and compare design study methodology to that of ethnography, grounded theory, and action research. Context: The global software industry and the software engineering (SE) academia are two large communities. However, unfortunately, the level of joint industry-academia collaborations in SE is still relatively very low, compared to the amount of activity in each of the two communities. It seems that the two 'camps' show only limited interest motivation to collaborate with one other. Many researchers and practitioners have written about the challenges, success patterns (what to do, i.e., how to collaborate) and anti-patterns (what not do do) for industry-academia collaborations.Objective: To identify (a) the challenges to avoid risks to the collaboration by being aware of the challenges, (b) the best practices to provide an inventory of practices (patterns) allowing for an informed choice of practices to use when planning and conducting collaborative projects.Method: A systematic review has been conducted. Synthesis has been done using grounded-theory based coding procedures.Results: Through thematic analysis we identified 10 challenge themes and 17 best practice themes. A key outcome was the inventory of best practices, the most common ones recommended in different contexts were to hold regular workshops and seminars with industry, assure continuous learning from industry and academic sides, ensure management engagement, the need for a champion, basing research on real-world problems, showing explicit benefits to the industry partner, be agile during the collaboration, and the co-location of the researcher on the industry side.Conclusion: Given the importance of industry-academia collaboration to conduct research of high practical relevance we provide a synthesis of challenges and best practices, which can be used by researchers and practitioners to make informed decisions on how to structure their collaborations. From the Publisher: Difficult to learn and awkward to use, today's information systems often change our activities in ways that we do not need or want. The problem lies in the software development process. In this book John Carroll shows how a pervasive but underused element of design practice, the scenario, can transform information systems design. Traditional textbook approaches manage the complexity of the design process via abstraction, treating design problems as if they were composites of puzzles. Scenario-based design uses concretization. A scenario is a concrete story about use. For example: "A person turned on a computer; the screen displayed a button labeled Start; the person used the mouse to select the button." Scenarios are a vocabulary for coordinating the central tasks of system developmentunderstanding people's needs, envisioning new activities and technologies, designing effective systems and software, and drawing general lessons from systems as they are developed and used. Instead of designing software by listing requirements, functions, and code modules, the designer focuses first on the activities that need to be supported and then allows descriptions of those activities to drive everything else. In addition to a comprehensive discussion of the principles of scenario-based design, the book includes in-depth examples of its application. URLLC is an important new feature brought by 5G, with a potential to support a vast set of applications that rely on mission-critical links. In this article, we first discuss the principles for supporting URLLC from the perspective of the traditional assumptions and models applied in communication information theory. We then discuss how these principles are applied in various elements of system design, such as use of various diversity sources, design of packets, and access protocols. The important message is that there is a need to optimize the transmission of signaling information, as well as a need for lean use of various sources of diversity. This paper presents a novel argumentation framework to support Issue-Based Information System style debates on design alternatives, by providing an automatic quantitative evaluation of the positions put forward. It also identifies several formal properties of the proposed quantitative argumentation framework and compares it with existing non-numerical abstract argumentation formalisms. Finally, the paper describes the integration of the proposed approach within the design Visual Understanding Environment software tool along with three case studies in engineering design. The case studies show the potential for a competitive advantage of the proposed approach with respect to state-of-the-art engineering design methods.