The Digital Twin – Birth of an Integrated System in the Digital Age

Today we live in a time where new technologies are developing rapidly. Digitalization and automation are finding their way into various industrial sectors, especially in the area of Industry 4.0. As in previous digitalization efforts in the manufacturing sector, it can be observed that the discourse is strongly concentrated on technological themes, neglecting the overall integration of technologies into the organization. In this paper, we conduct a literature review on the concept of a digital twin, i.e. a simulation-oriented closed loop system consisting of physical and digital components. We map the identified themes to the elements of a socio-technical system to show which issues in the discourse are underrepresented from a managerial point of view in order to provide indications for a more holistic discourse

Analytics Use Cases for Mass Customization – A Process-based Approach for Systematic Discovery

Nowadays, mass customization (MC) is shaped by the application of digital technologies like computer-aided design, computer aided manufacturing, and distribution planning. Within a MC process, various data is created, which can be used to gain knowledge about past and future business activities by means of modern data analytics methods. The paper at hand applies design science research and presents a process-based approach for identifying potential analytics use cases for MC. For this purpose, a generic MC process is derived from previous literature and a systematic analysis is carried out using the work systems method. The resulting artifact offers a differentiated view on customers, products, activities, participants, technologies, and information as well as on the information flows within the MC process. It enables manufacturers to identify valuable opportunities for analytics and to optimize current MC processes. Furthermore, it can be used to develop a systematic process for the discovery and evaluation of analytics use cases and novel business models in the future

The Impact of Digital Technology on Network Value Co-creation

In recent years, the discussion about how companies integrate new technologies into their value creation and how this affects their business has intensified. The trend towards digitalization is particularly challenging for smaller, value co-creating (VCC) companies in networks, yet little research has been done in this context. In response, this paper identifies four key technologies for promoting network VCC: (1) a service configuration system, (2) a centralized knowledge base, (3) an analytics system, and (4) a shared IT platform. We conducted a single embedded case study in a company network introducing these key technologies and thereby digitally transforming its VCC. Our results show how the companies in the network are approaching their transformation and what the impact and role of the technologies in their network VCC are

Teaching Big Data Management – An Active Learning Approach for Higher Education

Since big data analytics has become an imperative for business success in the digital economy, universities face the challenge to train data scientists and data engineers on various technological and managerial skills. In addition to traditional lectures, active learning formats ensure a practice-oriented education enabling students to handle novel big data technologies. In this paper, we present a big data management syllabus for master students in the field of big data analytics, which includes various hands-on and action learning elements. The course encompasses seven lectures and nine tutorials and takes place at Chemnitz University of Technology. It covers a broad range of big data applications and facilitates knowledge on various cognitive levels. The paper gives an overview of the course content and assigns learning objectives to lectures and tutorials using Krathwohl’s revised taxonomy. Finally, we present the feedback, which we have received by the students over the years

Closing the Implementation Gap of Digital Twins

Since the manufacturing industry is facing increasingly advancing digitalization, digital twins (DT) have become a popular means for integrating various actors\u27 value creation using a smart product. DTs are information systems that connect the physical and virtual worlds. The design of DTs is time-consuming, expensive, and lacks appropriate prescriptive design knowledge for its development. Design principles (DP) represent a mechanism to codify design knowledge into prescriptive knowledge. However, the mostly abstract DPs are often difficult for practitioners to operationalize during software development projects, rendering the design knowledge difficult to access. The paper at hand addresses these issues by providing a reference model for DT development as a semi-abstract artifact. The model has been constructed by drawing on a literature review and empirical cases in the manufacturing industry. The reference model includes multiple adaptation mechanisms to ensure a flexible development of company-specific DTs

Exploring the Abstraction Levels of Design Principles: The Case of Chatbots

Formulating design principles is the primary mechanism to codify design knowledge which elevates its meaning to a general level and applicability. Although we can observe a great variety of abstraction levels in available design principles, spanning from more situated to more generic levels, there is only limited knowledge about the corresponding (dis-)advantages of using a certain level of abstraction. That is problematic because it hinders researchers in making informed decisions regarding the (intended) level of abstraction and practitioners in being oriented whether the principles are already contextualized or still require effort to apply them within their situation. Against this backdrop, this paper (1) explores different abstraction levels of design principles based on a sample of 69 principles from the chatbot domain, as well as (2) provides a preliminary positioning framework and lessons learned. We aim to complement methodological guidance and strengthen the principles\u27 applicability, ultimately leading to knowledge reuse

It\u27s Time to Smarten Up! - A Framework for Building Smart Service Systems

Smart service systems are a network of people, technologies, as well as processes and rely on learning, adaptivity, and decision-making to provide smart services to their users. The complexity of designing smart service systems results in a plethora of potential implementation obstacles, often leading to an overly technical focus and resulting in isolated solutions. There is, therefore, a need for a guideline for companies that helps them facilitate the development of complex smart service systems. To this end, we apply action design research used in a multi-year design study for digital twins in the manufacturing industry. The resulting four-quadrant framework (domain, system design, organization, and ecosystem) can help researchers and companies guide the development of smart service systems or evaluate past progress. The evaluation of the framework shows that there might be dominant quadrants and certain paths in the framework, which we would like to investigate in further research

Digital Twins at the Heart of Smart Service Systems - An Action Design Research Study

Today’s rapidly advancing technology is shaping many aspects of our personal and working lives. In the context of the continuing digitalization of the manufacturing industry Digital Twins (DT) have emerged as a new kind of networked information system, which converges real-world assets with virtual counterparts. Smart service systems (SSS) provide a new perspective on these information systems enabling a connection between the technical concepts of industry 4.0 with service science. We conduct an action design research study in the machine manufacturing industry and use the SSS as a guiding perspective for our DT design. This paper contributes three design principles for DTs in manufacturing: (1) cyber-physical (re-) configurability, (2) smartness of the product, and (3) IT platform as a boundary object. The design was evaluated with several manufacturing companies based on a user interface prototype