Wolfgang Boos
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Institute
The automotive industry's transition to electromobility, marked by the replacement of traditional combustion engines with electric drives, significantly disrupts the existing product range of many companies. This transition is especially impactful in Germany, a major automotive hub employing about 786,000 people in 2021, where it's projected that around 21 percent of these jobs could be at risk by 2030. Therefore, there is an urgent need for German automotive suppliers to adapt to the evolving electromobility landscape, further intensified by concurrent trends like digitalization, work changes and sustainability. A notable gap in the current literature is the absence of a comprehensive capability model for these suppliers to manage this transformation effectively. This research aims to close this gap by identifying the essential transformation capabilities and developing a capability model, emphasizing 30 key capabilities clustered into superordinate dimensions and structured along the fields of action of human, technology and organization, the MTO approach.
In recent times, both geopolitical challenges and the need to counteract climate change have led to an increase in generated renewable energy as well as an increased demand for clean electrical energy. The resulting variability of electricity production and demand as well as an overall demand increase, put additional stress on the existing grid infrastructure. This leads to strongly increased maintenance demands for distribution system operators (DSOs). Today, condition monitoring is used to address these challenges. Researchers have already explored solutions for monitoring critical assets like switchgear and circuit breakers. However, with a shrinking knowledgeable technical workforce and increasing maintenance requirements, mere monitoring is insufficient. Already today, DSOs ask for actionable recommendations, optimization strategies, and prioritization methods to manage the growing task backlog effectively. In this paper we propose a vision of a grid-level cognitive assistance system that translates the outcome of diagnosis and prognosis systems into actionable work tasks for the grid operator. The solution is highly interdisciplinary and based on empirical studies of real-world requirements. We also describe the related work relevant to the multi-disciplinary aspects and summarize the research gaps that need to be closed over the next years.
In diesem Expert-Paper stellen wir Ihnen den SolutiKo-Ordnungsrahmen vor, der Unternehmen wie ein Kompass auf dem Weg vom Produkt- zum Lösungsanbieter unterstützen soll. Als Orientierungspunkt im Projekt SolutiKo bietet das Paper eine thematische Einführung sowie einen Überblick über die Themen, die im Projekt adressiert werden. Das Expert-Paper richtet sich an Führungskräfte und Mitarbeitende in Unternehmen, die das Lösungsgeschäft aufbauen und optimieren wollen.
Reinforced through the pandemic and shaped by digitalization, today's professional working environment is in a state of transformation. Working remotely has become a vital component of many professions' regular routines. The design of remote work environments presents challenges to organizations of all sizes. By providing a classification, this paper reveals a comprehensive understanding of the fields of design to be considered to establish lasting remote work concepts in organizations. A hierarchical classification with four dimensions consisting of human, technology, organization, and culture, seven design elements and, twenty design parameters indicates to organizations the fields of design that need to be examined. To satisfy both the theoretical foundation and the practical application, design elements are derived by implementing a systematic review of the literature that represents key areas of interest for remote work. Additionally, these are verified and complemented by a dedicated case study research to incorporate practice-oriented design parameters.
Die pandemiebedingt angestiegene Homeofficequote in produzierenden
Unternehmen ist seit Juli 2020 deutlich rückläufig und indiziert ein
geringes Maß an langfristig gestalteten hybriden Arbeitsplatzkonzepten.
Angesichts des Fachkräftemangels besteht Handlungsdruck, eine
attraktive Arbeitsumgebung mit industriellen Tätigkeiten zu vereinbaren.
Um zukunftsorientierte Arbeitsplatzkonzepte zu gestalten, nennt
das vorgestellte Vorgehen systematisch die menschlichen Tätigkeiten
in produzierenden Unternehmen und bewertet deren Remotefähigkeit.
The agricultural industry is facing unprecedented challenges in meeting the growing demand for food while minimizing its impact on the environment. To address these challenges, the industry is embracing technological advancements such as 5G networks to improve efficiency and productivity. However, the benefits of 5G technology must be weighed against the costs of implementing a suitable network. This paper presents cost-benefit dimensions that are needed to assess the economic feasibility of implementing 5G networks for several agricultural applications. The paper describes the costs of deploying and maintaining a 5G network and the benefits of several 5G-specific use cases, including precision agriculture, livestock monitoring, and swarm robotics. Using industry reports and case studies, the model quantifies the benefits of 5G networks, such as enabling new digital agricultural processes, increased productivity, and improved sustainability. It also considers the costs associated with equipment and infrastructure, as well as the challenges of deploying a network in rural areas. The results demonstrate that 5G networks can provide significant benefits to agricultural businesses and provide an overview about the cost factors. Both benefit and cost dimensions are analyzed for the 5G-specific agricultural use cases.
Companies in the manufacturing sector are confronted with an increasingly dynamic environment. Thus, corporate processes and, consequently, the supporting IT landscape must change. This need is not yet fully met in the development of information systems. While best-of-breed approaches are available, monolithic systems that no longer meet the manufacturing industry's requirements are still prevalent in practical use. A modular structure of IT landscapes could combine the advantages of individual and standard information systems and meet the need for adaptability. At present, however, there is no established standard for the modular design of IT landscapes in the field of manufacturing companies' information systems. This paper presents different ways of the modular design of IT landscapes and information systems and analyzes their objects of modularization. For this purpose, a systematic literature research is carried out in the subject area of software and modularization. Starting from the V-model as a reference model, a framework for different levels of modularization was developed by identifying that most scientific approaches carry out modularization at the data structure-based and source code-based levels. Only a few sources address the consideration of modularization at the level of the software environment-based and software function-based level. In particular, no domain-specific application of these levels of modularization, e.g., for manufacturing, was identified. (Literature base: https://epub.fir.de/frontdoor/index/index/docId/2704)
More and more companies in the mechanical and plant engineering industry are transforming their business model and evolving from product to solution providers. Subscription business models play a key role in this development. They enable companies to enter long-term collaborative relationships with customers and thus monetize the potential of Industry 4.0. However, this development is not easy for many companies and is associated with numerous hurdles. One of these hurdles is the development of a suitable range of services tailored to customer needs. In this context, the bundling of individual services to service modules plays a key role in realizing new value propositions. In practice, however, companies often lack an understanding of which services need to be combined in what way to be able to realize new value propositions. Accordingly, the goal of this work is to identify relevant services for subscription business models, to cluster them into meaningful value-adding bundles, and to derive new value propositions accordingly. The new value propositions in turn enable mechanical and plant engineering companies to strengthen customer loyalty and thus achieve long-term economic success.
Crisis situations can lead to extreme consequences for society and the economy, such as the disruption of supply chains and the collapse of critical infrastructure. The challenge for optimal crisis preparation lies in the unpredictability of causes, duration and scope, and severity. AI-based resilience services can aid in crisis preparation by providing software-based warnings, recommendations, and countermeasures. The aim of this paper is to present a method for evaluating such services in terms of their usefulness and acceptance. A questionnaire is presented, and the results of its piloting phase are disseminated. With these results, existing and projected AI-based services for crisis prevention can be evaluated.
Based on the increasingly complex value creation networks, more and more event-based systems are being used for decision support. One example of a category of event-based systems is supply chain event management. The aim is to enable the best possible reaction to critical exceptional events based on event data. The central element is the event, which represents the information basis for mapping and matching the process flows in the event-based systems. However, since the data quality is insufficient in numerous application cases and the identification of incorrect data in supply chain event management is considered in the literature, this paper deals with the theoretical derivation of the necessary data attributes for the identification of incorrect event data. In particular, the types of errors that require complex identification strategies are considered. Accordingly, the relevant existing error types of event data are specified in subtypes in this paper. Subsequently, the necessary information requirements and information available regarding identification are considered using a GAP analysis. Based on this gap, the necessary data attributes can then be derived. Finally, an approach is presented that enables the generation of the complete data set. This serves as a basis for the recognition and filtering out of erroneous events in contrast to standard and exception events.