Refine
Year of publication
- 2019 (52) (remove)
Document Type
- Journal article (24)
- Conference proceeding (14)
- Book chapter (9)
- Book (3)
- Doctoral Thesis (1)
- Anthology (1)
Language
- English (52) (remove)
Is part of the Bibliography
- yes (52) (remove)
Institute
- ESB Business School (52) (remove)
Publisher
- Elsevier (12)
- Stellenbosch University (6)
- Hochschule Reutlingen (4)
- Springer (4)
- Wiley (4)
- IEEE (2)
- MDPI (2)
- MIT (2)
- MIT Center for Information Systems Research (2)
- Taylor & Francis (2)
Manufacturing has to adapt to changing situations in order to stay competitive.It demands a flexible and easy-to-use integration of production equipment and ICT systems. The contribution of this paper is the presentation of the implementation of the Manufacturing Integration Assistant (MIALinx). The integration steps range from integrating sensors over collecting and rule-based processing of sensor information to the execution of required actions. Furthermore, we describe the implementation of MIALinx by commissioning it in a manufacturing environment to retrofit legacy machines for Industrie 4.0. Finally, we validate the suitability of our approach by applying our solution in a medium-size company.
Digitalization changes the manufacturing dramatically. In regard of employees’ demands, global trends and the technological vision of future factories, automotive manufacturing faces a huge number of diverse challenges. Currently, research focuses on technological aspects of future factories in terms of digitalization. New ways of work and new organizational models for future factories have not been described yet. There are assumptions on how to develop the organization of work in a future factory but up to now, literature shows deficits in scientifically substantiated answers in this research area. Consequently, the objective of this paper is to present an approach on a work organization design for automotive Industry 4.0 manufacturing. Future requirements were analyzed and deducted to criteria that determine future agile organization design. These criteria were then transformed into functional mechanisms, which define the approach for shopfloor organization design
The sound of brands
(2019)
The aim of this research paper is to both examine and conceptualise the concept of audio branding. Audio branding is an important part of the overall brand management concept and corporate identity. Strong brands ease the choice for customers and convey values and a certain quality promise. Branding is of vital importance. It needs to be acknowledged that only 0.004% of all outer stimuli reach the human consciousness. Therefore, audio branding is a way to further strengthen the overall brand awareness. This leads to an emotional connection with a brand.
This study strives to determine the characteristics of audio branding and to analyse the corporate audio branding of Audi. The result of this research study is the suggestion of the use of audio branding in a way that fits the overall brand picture. Otherwise, the brand communication is inconsistent, and this could lead to a misunderstanding of the brand values for customers. The analysis of the Audi corporate sound design might be beneficial for practitioners. The overall evaluation of the concept of audio branding contributes to the existing body of literature in branding.
Research organisations are not only contributing to sustainable development but also contribute to scientific findings. As key influencers of innovation; employers and publicly funded research organisations not only have the social mandate to deal with their responsibilities regarding the environment and society, but also drive to understand their social responsibility for their employees and the impact on research and operational processes. Sponsored by the German Federal Ministry for Education and Research (BMBF), this paper presents the results of the joint research project; LENA—Guidelines for Sustainability Management and describes how 3 of Germany’s biggest research organisations (Fraunhofer-Gesellschaft, Leibniz Association and Helmholtz Association) face current challenges in human resource management of research organisations by the integration of a common understanding of sustainability and a broad-based framework. The empirical basis is built by a qualitative organisational ethnographical study which reflects the expert knowledge, everyday experiences and the subject-oriented interpretation of sustainability in human resource management. The result derives concrete recommendations for the institutional practice and offers structured and methodologically proven options for action addressing the stakeholders in human resource management in research institutions.
Theory predicts that market‐timing activities bias Jensen's alpha (JA). However, empirical studies have failed to find consistent evidence of this bias. We tackle this puzzle in a nested model analysis and show that the bias contains an exogenous market component that is unrelated to market‐timing skill. In a comprehensive empirical analysis of US mutual funds, we find that the timing‐induced bias in JA is mainly driven by this market component, which is uncorrelated with measured timing activities. Measures of total performance that allow for timing activities are virtually identical to JA, even if timing activities are present in the evaluated fund. Hence, we conclude that JA is a sufficient measure of total performance.
In smart factories, maintenance is still an important aspect to safeguard the performance of their production. Especially in case of failures of machine components diagnosis is a time-consuming task. This paper presents an approach for a cyber-physical failure management system, which uses information from machines such as programmable logic controller or sensor data and IT systems to support the diagnosis and repairing process. Key element is a model combining the different information sources to detect deviations and to determine a probable failed component. Furthermore, the approach is prototypically implemented for leakage detection in compressed air networks.
Design thinking is inherently and invariably oriented towards the future in that all design is for products, services or events that will exist in the future, and be used by people in the future. This creates an overlap between the domains of design thinking and strategic foresight. A small but significant literature has grown up in the strategic foresight field as to how design thinking may be used to improve its processes. This paper considers the other side of the relationship: how methods from the strategic foresight field may advance design thinking, improving insight into the needs and preferences of users of tomorrow, including how contextual change may suddenly and fundamentally reshape these. A side-by-side comparison of representative models from each field is presented, and it is shown how these may be assembled together to create foresight-informed design-based innovation.
The flexible and easy-to-use integration of production equipment and IT systems on the shop floor becomes more and more a success factor for manufacturing to adapt rapidly to changing situations. The approach of the Manufacturing Integration Assistant (MIALinx) is to simplify this challenge. The integration steps range from integrating sensors over collecting and rule-based processing of sensor information to the execution of required actions. This paper presents the implementation of MIALinx to retrofit legacy machines for Industry 4.0 in a manufacturing environment and focus on the concept and implementation of the easy-to-use user interface as a key element.
The paper describes a new stimulus using learning factories and an academic research programme - an M.Sc. in Digital Industrial Management and Engineering (DIME) comprising a double degree - to enhance international collaboration between four partner universities. The programme will be structured in such a way as to maintain or improve the level of innovation at the learning factories of each partner. The partners agreed to use Learning Factory focus areas along with DIME learning modules to stimulate international collaboration. Furthermore, they identified several research areas within the framework of the DIME program to encourage horizontal and vertical collaboration. Vertical collaboration connects faculty expertise across the Learning Factory network to advance knowledge in one of the focus areas, while Horizontal collaboration connects knowledge and expertise across multiple focus areas. Together they offer a platform for students to develop disciplinary and cross-disciplinary applied research skills necessary for addressing the complex challenges faced by industry. Hence, the university partners have the opportunity to develop the learning factory capabilities in alignment with the smart manufacturing concept. The learning factory is thus an important pillar in this venture. While postgraduate students/researchers in the DIME program are the enablers to ensure the success of entire projects, the learning factory provides a learning environment which is entirely conducive to fostering these successful collaborations. Ultimately, the partners are focussed on utilising smart technologies in line with the digitalization of the production process.
It has not yet been possible to achieve the desired aim of decoupling economic growth from global material demand. Small and medium sized enterprises (SMEs) represent the backbone of most industrialized economies. Although material efficiency is of vital importance for many SMEs, few of them actually treat it as their top priority. There is a cornucopia of tools and methods available which can be used for material efficiency purposes. These, however, have gained little ground in the SME-field. This work deals with the enabling factors for material efficiency improvements in manufacturing SMEs and projections towards aspects of supply chain and circular economy. A multi-disciplinary decoupling approach for manufacturing SMEs and an implementation roadmap for further practical development are proposed. The approach combines appropriate complexity of technology and socio-economic considerations. It enables a connection of existing methods and the implementation of established information technologies.