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The usage of language models for human assistance in production failure root cause analysis
No full textDowntimes (outages) are unfavorable and costly events in production. Although approaches exist, they have to be implemented mainly manually and with a huge effort. Language models could be useful to support the production root cause failure analysis and help to get production up and running again more quickly. However, sparse research focused on this point so far. Therefore, it is still unclear how the usage of language models for human assistance in production failure root case analysis should be implemented. A qualitative expert study was conducted to reveal the potentials of such an approach and to find suitable use cases for language models. Based on the insights triggering factors, use cases as well as benefits and risks were identified and summarized within a model
How can international business-to-business partnerships in Africa contribute to achieving the sustainable development goals?
Get PDFFollowing calls by international business scholars to pay attention to how multinational enterprises contribute to the Sustainable Development Goals, we make implementable recommendations for international B2B partnerships in Africa. We postulate that international businesses can alleviate extreme poverty and eradicate child labor by selecting ethical African suppliers. Furthermore, partners must exercise transparency in how they adopt clean and environmentally sound technologies. We also highlight that partners should demonstrate flexibility and open-mindedness to African indigenous know-how and sustainable practices to facilitate knowledge-sharing. International B2B partners may consider our recommendations to guide the building of ethical and responsible businesses in Africa
A framework for explainable root cause analysis in manufacturing systems – combining machine learning, explainable artificial intelligence and the Ishikawa model for industrial manufacturing
Get PDFThis paper proposes a novel framework – “Transparent Reasoning in Artificial intelligence Cause Explanation” (TRACE) – that combines root cause analysis, explainable artificial intelligence, and machine learning in an understandable way for the worker. The goal is to enhance transparency, interpretability, and explainability in AI-driven decision-making processes as well as to increase the acceptance of AI within an industrial manufacturing area. The paper outlines the need of such a framework, describes the design process, and shows a preliminary mockup, a possible underlying software architecture as well as an evaluation and integration plan in an industrial environment
Kleine Ausführungen zur Vertriebsethik
No full textVertriebsmitarbeiter werden häufig unethischen Verhaltens beschuldigt. Laut Jung (2019) sind Bluffen, Lügen, Täuschung und Falschdarstellung in Verhandlungen zwischen Unternehmen gängige Praktiken. Eine internationale Studie zu Lügen in Vertragsverhandlungen ergab, dass zwar Falschdarstellungen über den Inhalt eines Vertrags allgemein als inakzeptabel angesehen wurden, die Mehrheit der Befragten jedoch Bluffen über Fristen und Budgetbeschränkungen als moralisch akzeptabel betrachtete (Jung, 2019)
A low-cost setup and procedure for measuring losses in inductors
No full textInductors are critical components in power electronic converters, determining their efficiency and size. A converter's performance is limited by the losses associated with inductors. In lower power applications, commercially available off-the-shelf inductors are usually used, but their losses are often difficult to predict solely based on datasheet values. Therefore, a direct measurement is typically required; here, a separate measurement of the dc and an ac loss is proposed to simplify the measurement process. This paper presents a low-cost setup based on affordable equipment, such as a self-built current probe, and uses simple compensation methods that allow developers to efficiently and cost-effectively measure losses in inductors. The setup is designed to emulate conditions comparable to real-world applications. The proposed procedure and setup are validated through experimental results, and potential sources of error and methods for compensation are discussed
Overcoming data shortage in critical domains with data augmentation for natural language software requirements
Get PDFNatural language processing (NLP) offers the potential to automate quality assurance of software requirement specifications. In particular, large‐scale projects involving numerous suppliers can benefit from this improvement. However, due to privacy restrictions especially in highly restrictive industries, the availability of software requirements specification documents for training NLP tools is severely limited. Also, domain‐ and project‐specific vocabulary, as such in the aerospace domain, require specialized models for processing effectively. To provide a sufficient amount of data to train such models, we studied algorithms for the augmentation of textual data. Four algorithms have been investigated by expanding a given set of requirements from the European Space projects generating correct and incorrect requirements. The initial study yielded data of poor quality due to the particularities of the domain‐specific vocabulary, yet laid the foundation for the algorithms' improvement, which, eventually, resulted in an increased set of requirements, which is 20 times the size of the seed set. A complementing experiment demonstrated the usability of augmented requirements to support AI‐based quality assurance of software requirements. Furthermore, a selected improvement of the augmentation algorithms demonstrated notable quality improvements by doubling the number of correctly augmented requirements
Das chinesische Afrika-Engagement – und die Folgen für die deutsche Wirtschaft und Politik
Get PDFChina hat durch das Forum on China-Africa Cooperation (FOCAC) und die Belt and Road Initiative (BRI) seine wirtschaftlichen und politischen Beziehungen zu Afrika in den vergangenen 25 Jahren erheblich ausgeweitet. Unternehmen spielen in Chinas Afrika-Engagement eine zentrale Rolle zur Verwirklichung der geopolitischen Ziele. Für den deutschen und europäischen Privatsektor verschärft sich dadurch die Wettbewerbssituation in afrikanischen Märkten, wobei sich durchaus auch Geschäftschancen als Kooperationspartner chinesischer Unternehmen bieten. Die Bundesregierung und die Europäische Kommission sollten diese Potenziale fördern, zum Beispiel durch institutionalisierte Kooperationen und das Erstellen von Kriterien für die Finanzierung von Projekten in Afrika
Third‐party market cooperation and non‐Chinese multinational enterprises' participation in the Belt and Road Initiative in Sub‐Saharan Africa
Get PDFChinese multinational enterprises (MNE) are wondering whether China's Belt and Road Initiative (BRI) in Sub‐Saharan Africa (SSA) creates challenges or opportunities for them. The fuzzy term “third‐party market cooperation” was coined to involve non‐Chinese MNEs in BRI‐related business opportunities. Our contribution is threefold: First, we explore the role of non‐Chinese firms in the BRI. Second, we locate “third‐party market cooperation” in the international business literature and examine its originality. Third, we assess how non‐Chinese MNEs can seize business potentials associated with third‐party market cooperation in SSA. We conduct a qualitative analysis of official documents and substantiate our analysis by evaluating other media sources on third‐party market cooperation projects in SSA. We find that firms play a decisive role in substantiating the BRI. The core novelty of third‐party market cooperation is its strong political dimension, as governments may initiate and flank the participation of their MNEs in the BRI
Exploring the impact of siloxane networks on the thermal behavior of P/N-enriched flame-retardant finishes for cotton fabric
Get PDFOur aim was to decipher potential synergy between phosphorus‑nitrogen (PN) and silicon (Si) in flame-retardant (FR) coatings for cotton textiles using a novel TRIAMO-based phosphoramidate-FR (TD) as a benchmark. For that we chose a comparative approach, employing a silica-free diethylenetriamine based derivative (DD), a dual-layer coating of tetraethyl orthosilicate (TEOS) and DD (DD/T). Standardized flame tests revealed that TD exhibited reduced performance at low add-on compared to DD, while DD/T consistently showed improved performance across loadings. TG-IR studies demonstrated that phosphoramidate species degrade via the release of triethyl phosphate (TEP) into the gas phase while forming PN networks on the substrate, independent of silica presence. However, functionalized silane networks accelerate the condensed phase mechanism of TEP by limiting gas diffusion. This was evidenced by XPS as TD yields a dense network of aliphatic PNO species such as phosphoramides and phosphor oxynitrides, while DD predominantly forms phosphazenes. These findings align with isoconversional kinetic studies showing higher activation energies for TD-treated cotton, attributed to diffusion limitations induced by the sol-gel network. This barrier effect also inhibits cotton pyrolysis, and enhances the structural integrity of char, as evidenced by SEM, DSC, and DTG data. While TEOS in DD/T alone does not alter the FR mechanism, it synergistically enhances char formation without impeding dehydration activity. In contrast, functionalized silanes demonstrate synergy only at critical add-ons; at lower loadings, the barrier effect disrupts the interaction between the FR moiety and the substrate. These findings suggest that the passivation and barrier effects of silica networks, though beneficial, may be overestimated in functionalized silane coatings for reactive substrates like cotton, emphasizing the need for increased loading levels to achieve desired FR performance. The same conclusion was found for functionalized phosphonate (DPTS) and amine-based silanes (TRIAMO), demonstrating that our findings are applicable for systems beyond phosphoramidate
Strategies to overcome the liability of outsidership in geopolitical projects: the case of German firms in the Chinese belt and road initiative in Africa
Get PDFPurpose
Building on the revised Uppsala model’s perspective on firm internationalization, which has been extended by network theory, we explore how firms overcome their liability of outsidership in the multi-stakeholder networks of geopolitical projects. We apply our theoretical assumptions in the context of the Belt and Road Initiative (BRI) in Sub-Saharan Africa (SSA).
Design/methodology/approach
We conducted a qualitative analysis of 20 semi-structured interviews with managers of German firms along the value chain of infrastructure projects in SSA.
Findings
Our findings show that Chinese firms are regarded not only as competitors but also as customers, particularly after network entry. We propose a four-tiered approach of entry nodes and processes showing how non-Chinese firms build enduring network relationships to overcome their liability of outsidership, thereby benefiting from BRI-related networks in SSA.
Originality/value
This is a pioneering study applying the revised Uppsala model to business networks in the multi-stakeholder and multi-country setting of geopolitical projects. Contrary to public opinion, we posit that in these geopolitical projects, it is not only firms from the sponsor government that benefit. Based on our “outside-in” perspective, we make clear that outsider firms may find business opportunities in geopolitical projects if they successfully build network relationships with insiders