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This contribution presents an approach for requirement oriented team building in industrial processes like product development. This will be based on the knowledge modelling and description language (KMDL(R)) that enables the modelling and analysis of knowledge intensive business processes. First the basic elements of the modelling technique are described, presenting the concept and the description language. Furthermore it is shown how the KMDL(R) process models can be used as a basis for the team building component. Therefore, an algorithm was developed that is able to propose a team composition for a specific task by analyzing the knowledge and skills of the employees, which will be contrasted to the process requirements. This can be used as guidance for team building decisions.
Modern production infrastructures of globally operating companies usually consist of multiple distributed production sites. While the organization of individual sites consisting of Industry 4.0 components itself is demanding, new questions regarding the organization and allocation of resources emerge considering the total production network. In an attempt to face the challenge of efficient distribution and processing both within and across sites, we aim to provide a hybrid simulation approach as a first step towards optimization. Using hybrid simulation allows us to include real and simulated concepts and thereby benchmark different approaches with reasonable effort. A simulation concept is conceptualized and demonstrated qualitatively using a global multi-site example.
Existing factories face multiple problems due to their hierarchical structure of decision making and control. Cyber-physical systems principally allow to increase the degree of autonomy to new heights. But which degree of autonomy is really useful and beneficiary? This paper differentiates diverse definitions of autonomy and approaches to determine them. Some experimental findings in a lab environment help to answer the question raised in this paper.
Dieses Buch bietet eine Einführung in die Wirtschaftsinformatik in kommentierter Form. Es richtet sich in erster Linie an Studierende der Betriebswirtschaftslehre und der Wirtschaftsinformatik.
Band 1 beinhaltet eine Betrachtung der nachfolgenden Themenpunkte: Der erste Abschnitt gibt eine Einführung in die Bedeutung der Wirtschaftsinformatik als Wissenschaftsfach und damit verbunden in ihre praktische Anwendungsorientierung. Der folgende Abschnitt liefert einen Überblick über die der Informatik zugrunde liegenden Konzepte und Techniken von Computer-Hardware und -Software sowie Begriffsbestimmungen und Beschreibungsmerkmale der Daten, Datenhaltung und -speicherung. Ein weiterer Abschnitt ist dem Komplex Netzwerke und Internet gewidmet. In kompakter Form werden Grundlagen der Netze und Netzwerkdienste erklärt. Das Thema Datenmodellierung bildet den Schwerpunkt dieses Bandes. Die Vorgehensweise zur Erstellung und Bearbeitung von Modellen wird in sehr ausführlicher Form dargelegt. Den Abschluss bildet die Verbindung zwischen Datenbanken und betrieblichen Anwedungssystemen.
Dieses Buch bietet eine Einführung in die Wirtschaftsinformatik in kommentierter Form. Es richtet sich in erster Linie an Studierende der Betriebswirtschaftslehre und der Wirtschaftsinformatik. Zu Beginn dieses Bandes wird eine Einführung in die Funktionalität einer Oracle-Datenbank am Beispiel der Version Oracle 10g XE als frei verfügbare Version des relationalen Datenbanksystems Oracle 10g gegeben. Der thematische Schwerpunkt im Band 2, die Datenbankabfragesprache SQL, baut auf dem Teil der Datenmodellierung des Bandes 1 auf. Zum besseren Verständnis der Zusammenhänge ist ein durchgehend verwendbares Beispiel gewählt worden. An Hand dieses Beispiels werden sowohl Begriffe als auch Zusammenhänge in der Umsetzung vom relationalen Datenmodell zur Datenbank erläutert. Im Detail werden sowohl Syntax als auch Semantik der Datenbeschreibungssprache SQL erläutert.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
In response to the impending spread of COVID-19, universities worldwide abruptly stopped face-to-face teaching and switched to technology-mediated teaching. As a result, the use of technology in the learning processes of students of different disciplines became essential and the only way to teach, communicate and collaborate for months. In this crisis context, we conducted a longitudinal study in four German universities, in which we collected a total of 875 responses from students of information systems and music and arts at four points in time during the spring–summer 2020 semester. Our study focused on (1) the students’ acceptance of technology-mediated learning, (2) any change in this acceptance during the semester and (3) the differences in acceptance between the two disciplines. We applied the Technology Acceptance Model and were able to validate it for the extreme situation of the COVID-19 pandemic. We extended the model with three new variables (time flexibility, learning flexibility and social isolation) that influenced the construct of perceived usefulness. Furthermore, we detected differences between the disciplines and over time. In this paper, we present and discuss our study’s results and derive short- and long-term implications for science and practice.
Audit - and then what?
(2019)
Current trends such as digital transformation, Internet of Things, or Industry 4.0 are challenging the majority of learning factories. Regardless of whether a conventional learning factory, a model factory, or a digital learning factory, traditional approaches such as the monotonous execution of specific instructions don‘t suffice the learner’s needs, market requirements as well as especially current technological developments. Contemporary teaching environments need a clear strategy, a road to follow for being able to successfully cope with the changes and develop towards digitized learning factories. This demand driven necessity of transformation leads to another obstacle: Assessing the status quo and developing and implementing adequate action plans. Within this paper, details of a maturity-based audit of the hybrid learning factory in the Research and Application Centre Industry 4.0 and a thereof derived roadmap for the digitization of a learning factory are presented.
Faced with the increasing needs of companies, optimal dimensioning of IT hardware is becoming challenging for decision makers. In terms of analytical infrastructures, a highly evolutionary environment causes volatile, time dependent workloads in its components, and intelligent, flexible task distribution between local systems and cloud services is attractive. With the aim of developing a flexible and efficient design for analytical infrastructures, this paper proposes a flexible architecture model, which allocates tasks following a machine-specific decision heuristic. A simulation benchmarks this system with existing strategies and identifies the new decision maxim as superior in a first scenario-based simulation.
Subject-oriented learning
(2019)
The transformation to a digitized company changes not only the work but also social context for the employees and requires inter alia new knowledge and skills from them. Additionally, individual action problems arise. This contribution proposes the subject-oriented learning theory, in which the employees´ action problems are the starting point of training activities in learning factories. In this contribution, the subject-oriented learning theory is exemplified and respective advantages for vocational training in learning factories are pointed out both theoretically and practically. Thereby, especially the individual action problems of learners and the infrastructure are emphasized as starting point for learning processes and competence development.
In the copyright industries of the 21st century, metadata is the grease required to make the engine of copyright run smoothly and powerfully for the benefit of creators, copyright industries and users alike. However, metadata is difficult to acquire and even more difficult to keep up to date as the rights in content are mostly multi-layered, fragmented, international and volatile. This article explores the idea of a neutral metadata search and enhancement tool that could constitute a buffer to safeguard the interests of the various proprietary database owners and avoid the shortcomings of centralised databases.