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Software scripts for sensor data extraction in Rasberry Pi: user-space and kernel-space comparison
No full textThis paper compares two popular scripting implementations for hardware prototyping: Python scripts execut from User-Space and C-based Linux-Driver processes executed from Kernel-Space, which can provide information to researchers when considering one or another in their implementations. Conclusions exhibit that deploying software scripts in the kernel space makes it possible to grant a certain quality of sensor information using a Raspberry Pi without the need for advanced real-time operational systems
Leveraging digitilisation and machine learning for improved railway operations and maintenance
Get PDFThe efficient and safe movement of goods and people require reliable railway systems. Quality assurance of manufactured and assembled systems and correct maintenance of such systems are required to keep rolling stock in good operational condition. Quality assurance and maintenance in the railway industry can be costly and time-consuming, but the expansive growth of data due to smart sensors and monitoring technologies makes it possible to leverage the potential of machine learning to reduce cost and labour. Improved reliability and safety, and reduced costs are benefits that the use of “Big Data” and machine learning techniques can realise. However, despite these potential benefits for manufacturers, rail operators, and passengers, the rail industry is still labelled for its lack of innovation, while in most other industries, data is regarded as a strategic asset for competitive advantage.
This paper demonstrates how machine learning and data analysis can be used to benefit railway industry manufacturers and operators when applied to rolling stock data. It also illustrates the lost opportunity in the rail industry for not applying data-driven solutions to their full potential. The paper also discusses the current applications of machine learning in the railway industry and provides the requirements for the implementation of machine learning techniques. Machine learning is applied to pantograph data of a South African railway operator's rolling stock. Classification – a machine learning technique – is used to identify and categorise events within the dataset to discover whether pantograph bounce occurs due to faulty sensors, faulty pantographs, or defective infrastructure. In this paper it is demonstrated how machine learning can benefit rail manufacturers and operators to improve manufacturing and assembly processes, as well as maintenance practices. It is concluded that railways should treat data similarly to other railway assets, with suitable management and governance practices
Anomaly detection in hobbing tool images: using an unsupervised deep learning approach in manufacturing industry
Get PDFThis study explores the application of the PatchCore algorithm for anomaly classification in hobbing tools, an area of keen interest in industrial artificial intelligence application. Despite utilizing limited training images, the algorithm demonstrates capability in recognizing a variety of anomalies, promising to reduce the time-intensive labeling process traditionally undertaken by domain experts. The algorithm demonstrated an accuracy of 92%, precision of 84%, recall of 100%, and a balanced F1 score of 91%, showcasing its proficiency in identifying anomalies. However, the investigation also highlights that while the algorithm effectively identifies anomalies, it doesn't primarily recognize domain-specific wear issues. Thus, the presented approach is used only for pre-classification, with domain experts subsequently segmenting the images indicating significant wear. The intention is to employ a supervised learning procedure to identify actual wear. This premise will be further investigated in future research studies
Higher-order externalities in multi-platform ecosystems
Get PDFPlatforms have become pivotal business models and involve a different logic than traditional pipeline business models. Important factors for understanding their emergence and growth are externalities such as network effects and complementarities. At present, these concepts are focused on the effects on a single platform, but with the diffusion of platforms and their maturity, platforms are increasingly linked to each other. This interconnection of multiple platforms towards multi-platform ecosystems poses two key challenges. First, their networked structure exceeds traditional analytical approaches that are based on dyadic relationships. Second, individual choices drive externalities in these ecosystems, giving rise to emergent structures. To address these issues, the present research proposes a network science-based methodology that augments existing approaches to understand and visualize ecosystems (“ecosystem intelligence”). It presents a network conceptualization that captures the structure of multi-platform ecosystems and proposes a method for data collection and detailed network modeling. Among the main findings are three new types of externalities referred to as higher-order externalities. These include remote externalities that indicate value creation across platforms, transitive externalities representing chains between platforms, and polyadic externalities capturing value creation in n-ary relationships. They contribute to the understanding and management of the intricacies of multi-platform ecosystems, which can open new avenues in ecosystem intelligence
Employee proactive personality and career growth: the role of proactive behavior and leader proactive personality
Get PDFBased on social information processing theory, this research examines whether and how an employee’s proactive personality influences intrinsic and extrinsic career growth. It also examines the mediating effects of two types of proactive behaviors (voice behavior and taking charge) and the moderating effect of a leader’s proactive personality. A sample of 307 employee-leader dyads participated in this survey. Structural equation modeling was used to test the hypotheses, and the bootstrap procedure was used to test the indirect effects. Results show that an employee’s proactive personality has significant positive effects on both intrinsic and extrinsic career growth. The mediating effect of taking charge was confirmed, while the mediating effect of voice behavior was not. Leader proactive personality weakens the relationship between employee proactive personality and the two types of proactive behaviors. Employee proactive personality is more positively related to intrinsic and extrinsic career growth via proactive behaviors when a leader’s proactive personality is low. This study extends the literature on proactive personality, proactive behavior, and career development by examining the underlying determination, mediation, and moderation mechanisms
Performance management system components and the role of the management accountant
No full textPurpose: While extant research does mention performance management systems as antecedent to a management accountant’s role, and that there is tension between both, there is little detailed research. Thus, this paper aims to investigate the extent to which a performance management system interacts with the role of a management accountant.
Design/methodology/approach: The study is a cross-sectional field study, using interviews with paired management accountants and operative managers in 16 multinational organisations in Germany. The perspectives of both management accountants and operative managers are analysed separately. The role episode model theoretically informs the study.
Findings: The findings reveal management accountants distinguish between three roles of scorekeeping, controlling and business support, similar to prior literature. By contrast, operating managers are concerned with the value-adding and non-value-adding character of activities and thus support a dichotomy of management accountants’ roles. Drawing upon the role episode model, this study elucidates the interplay between performance management systems and the roles of management accountants, which encompass both role-taking and role-making dynamics. Additionally, this study contributes to management control literature by operationalising the components of a performance management system framework and linking them to the role of management accountants, as proposed by role antecedents in previous literature. The study also uncovers factors influencing role-taking and role-making, alongside examining the repercussions of role consensus or conflict based on the interaction with the operating manager.
Research limitations/implications: This paper is subject to the normal limitations of case study research and generalisation. The findings may also be influenced by the cultural context of the study.
Originality/value: An updated role episode model is presented, highlighting further performance management systems’ components. The study also reveals factors enabling and/or inhibiting the management accountants’ business support role and the impact of role consensus/conflict
Robot-based 6D bioprinting for soft tissue biomedical applications
Get PDFWithin this interdisciplinary study, we demonstrate the applicability of a 6D printer for soft tissue engineering models. For this purpose, a special plant was constructed, combining the technical requirements for 6D printing with the biological necessities, especially for soft tissue. Therefore, a commercial 6D robot arm was combined with a sterilizable housing (including a high-efficiency particulate air (HEPA) filter and ultraviolet radiation (UVC) lamps) and a custom-made printhead and printbed. Both components allow cooling and heating, which is desirable for working with viable cells. In addition, a spraying unit was installed that allows the distribution of fine droplets of a liquid. Advanced geometries on uneven or angled surfaces can be created with the use of all six axes. Based on often used bioinks in the field of soft tissue engineering (gellan gum, collagen, and gelatin methacryloyl) with very different material properties, we could demonstrate the flexibility of the printing system. Furthermore, cell-containing constructs using primary human adipose-derived stem cells (ASCs) could be produced in an automated manner. In addition to cell survival, the ability to differentiate along the adipogenic lineage could also be demonstrated as a representative of soft tissue engineering
Textilforschung 2023 : Bericht 70
Get PDFSeit 70 Jahren treiben Wirtschaft und Forschung im Rahmen der Förderrichtlinie der Industriellen Gemeinschaftsforschung (IGF) gemeinsam Innovationen voran und bilden eine wichtige Säule für die Wettbewerbsfähigkeit des deutschen Mittelstands. Der Bund, heute das Bundesministerium für Wirtschaft und Klimaschutz (BMWK), fördert dieses Engagement von Beginn an finanziell. Als Koordinator der Forschungsaktivitäten sowie als Motor für den Transfer der Forschungsergebnisse wurde die Arbeitsgemeinschaft industrieller Forschungsvereinigungen Otto von Guericke (AiF) von der Textilbranche und anderen deutschen Industrieverbänden gegründet. Das Forschungskuratorium ist als eines der Gründungsmitglieder von Anfang an mit dabei. Es hat sich ein starkes Netzwerk aus mittelständischen Unternehmen und unzähligen Forschungseinrichtungen gebildet. In den vergangenen Monaten hat sich für die IGF viel verändert. Im Januar 2024 gab die AiF ihre Projektträgerschaft ab: Der DLR-Projektträger hat die Administration der IGF vollständig übernommen. Das stellt die Forschungsvereinigungen vor große Herausforderungen. Strukturen, Software und natürlich Ansprechpartner für die Projektadministration haben sich geändert. Viele Verantwortlichkeiten, die bislang bei der AiF lagen, wie zum Beispiel die gesamte Mittelverwaltung, werden nun von den Forschungsvereinigungen übernommen. Sowohl Strukturen als auch Software des DLR-Projektträgers sind nicht 1:1 mit den Bedarfen der IGF kompatibel. Somit war und ist die Umstellung nach wie vor eine große Herausforderung für alle. Das Team des FKT stellt sich fortlaufend und schnell auf die neue Situation ein, um die Administration der Industriellen Gemeinschaftsforschung für unsere Branche bestmöglich weiterzuführen. Bereits im Jahr 2023 wurden mit 51 Bewilligungen mehr Projekte bewilligt als im Jahr zuvor. Und auch im aktuellen Jahr 2024 scheint sich dieser Trend fortzusetzen
Method for determining material demands by combing deterministic and probabilistic information in flexible and changeable production systems
No full textIn today's dynamic manufacturing environment, flexible and resilient production systems are crucial for coping with constantly changing internal product and production requirements coupled with external market and customer demands. Conventional production systems often lack the capability to adapt to changing requirements due to their fixed structures and technical limitations. To address these challenges, various flexible and changeable production system approaches have been developed in the last years. However, material provision becomes challenging due to increasing degrees of freedom and uncertainty due to arising turbulences, making it difficult to match demand and material provision in terms of time, location, and quantity. This paper presents a method to determine material demands that considers both deterministic and probabilistic information regarding material demand location, quantity, and time. An experimental research approach based on a minimal system was pursued, incorporating simulation experiments covering parameter variation using the Monte Carlo method. The results demonstrate that the developed method successfully determines material demands, enabling flexible and target-size-optimized material provision with potentially arising turbulences
How successful is the marketing strategy of a social enterprise in the case of Patagonia? (Part 1)
No full textIn recent years, companies have become increasingly aware of the importance of social responsibility and sustainability in their operations. Social enterprises have emerged as a concept that aims to blend social objectives with profit-making characteristics. For social enterprises to succeed, a well-designed marketing strategy is essential. Ideally, this strategy should clearly communicate unique purposes and future visions, while justifying any high prices associated with their commitment. Patagonia is an example of a social enterprise that implements a purpose-driven marketing strategy