Hasil untuk "Industrial relations"

Barry M. Staw, Sigal G. Barsade

P. Morrow

Zebei Tong, Hongchang Chen, Yujie Lei et al.

Image generation technology can synthesize condition-specific images to supplement real-world industrial anomaly data and enhance anomaly detection model performance. Existing generation techniques rarely account for the pose and orientation of industrial components in assembly, making the generated images difficult to utilize for downstream application. To solve this, we propose a novel image synthesis approach, called PostureObjectStitch, that achieves accurate generation to meet the requirement of industrial assembly. A condition decoupling approach is introduced to separate input multi-view images into high-frequency, texture, and RGB features. The feature temporal modulation mechanism adapts these features across diffusion model time-steps, enabling progressive generation from coarse to fine details while maintaining consistency. To ensure semantic accuracy, we introduce a conditional loss that enhances critical industrial elements and a geometric prior that guides component positioning for correct assembly relationships. Comprehensive experimental results on the MureCom dataset, our newly contributed DreamAssembly dataset, and the downstream application validate the outstanding performance of our method.

Sae Young Moon, Myeongjun Erik Jang, Haoyan Luo et al.

Topic modeling has extensive applications in text mining and data analysis across various industrial sectors. Although the concept of granularity holds significant value for business applications by providing deeper insights, the capability of topic modeling methods to produce granular topics has not been thoroughly explored. In this context, this paper introduces a framework called TIDE, which primarily provides a novel granular topic modeling method based on large language models (LLMs) as a core feature, along with other useful functionalities for business applications, such as summarizing long documents, topic parenting, and distillation. Through extensive experiments on a variety of public and real-world business datasets, we demonstrate that TIDE's topic modeling approach outperforms modern topic modeling methods, and our auxiliary components provide valuable support for dealing with industrial business scenarios. The TIDE framework is currently undergoing the process of being open sourced.

T. Melo, Álvaro Garrido-Morgado

W. Carlin, C. Mayer

Muhammad Aslam Jarwar, Jeremy Watson, Sajjad Ali

The significance of Industrial Internet of Things (IIoT) is undeniable, yet many critical industries remain hesitant to adopt it due to fundamental security, transparency and safety concerns. Developing a mechanism to address these concerns is challenging, as it involves a large number of heterogeneous devices, complex relations and human-machine contextual factors. This article presents a comprehensive analysis through a systematic review of ontologies and key security attributes essential for modelling the security of IIoT environments. Our review includes an extensive analysis of research articles, semantic security ontologies, and cybersecurity standards. Through this analysis, we identify critical security concepts and attributes, which can be leveraged to develop standardised security ontologies tailored for IIoT. Additionally, we explore the potential of integrating ontologies into the Industry 5.0 paradigm, which emphasises human-centricity, resilience, and sustainability. While ontologies offer structured modelling capabilities, their alignment with Industry 5.0’s unique collaborative and adaptive security needs remains limited. Our review suggests that existing security ontologies are not fully aligned with security goals, exposing many important research gaps. These gaps include areas such as semantic mapping techniques, security-by-design ontologies, holistic security standards, and ontologies that address the sociotechnical aspects of IIoT.

Juliana Londoño Polo

The challenges that present-day globalization poses in setting international labour standards are not uncharted. The conflict between the role of global considerations, on the one hand, and national and local dimensions, on the other, is one well-known by the International Labour Organization (hereinafter ILO) [1]. This issue resurfaces at this time when the ILO has expressed its commitment to adopting an international labour standard for decent work in the platform economy [2]. Against this legislative backdrop, it is particularly relevant to consider the wide range of existing institutional responses to platform work and their diverse content at national level. Due to the heterogeneous nature of the ILO’s member states, attempting a universal mandate on platform work adds an extra layer of complexity to regulating this phenomenon, compared to previous exercises conducted at a national level or even at a transnational level, as recently done by the EU’s directive. In this regard, identifying how diverse domestic institutional systems -i.e. judicial, industrial relations, and legislative systems- have responded to the presence of platform work so far and reflecting on the factors that (may) have impacted them through the lens of the widely diverse contexts of the Global North (GN) and Global South (GS) may provide key lessons and a valuable understanding of the challenges faced in different regions, in light of the commitment to adopt an international labour standard on this issue. This paper sets out to present a broad overview of precisely this by drawing on the data collected through a global mapping of jurisprudence, social dialogue, and legislative initiatives in the platform economy, which was carried out based on an extensive review of academic and grey literature, institutional and research databases, and media. This paper presents a portion of the results from this exercise, mainly from the perspective of the material scope and outcomes of the initiatives identified in the recollection. Research on this matter is essential, especially in the GS, due to it being heavily under-researched. [1] This paper seeks to contribute to bridging this gap by examining the global institutional responses, paying special attention to the GS. [1] ‘Universal Labor Standards and National Cultures by Jean-Michel Servais :: SSRN’ <https://papers.ssrn.com/sol3/papers.cfm?abstract_id=833266> accessed 7 October 2024. [2] Oxford Internet Institute, ‘ILO Includes an International Convention on Platform Workers on Its Agenda’ (Fairwork, 31 March 2023) <https://fair.work/en/fw/blog/ilo-international-convention-platform-workers-agenda/>. [3] ILO (ed), The Role of Digital Labour Platforms in Transforming the World of Work (ILO 2021). [1] Richard Heeks and others, Digital Labour Platforms in the Global South: Filling or Creating Institutional Voids? (2020) 1–2; Simon Joyce and Mark Stuart, ‘Trade Union Responses to Platform Work: An Evolving Tension between Mainstream and Grassroots Approaches’ [2021] A Modern Guide To Labour and the Platform Economy 177, 177.

Владислав БАЛІЙЧУК

The current state of Ukrainian society, which is defined as a set of systemic consequences of the Russian-Ukrainian war and rapid globalization changes, institutional and individual crisis of trust, growing structural fragmentation and polarization, actualizes the need to rethink the mechanisms of social interaction at all levels of socio-cultural reality. Traditional concepts that describe the idea of solidarity and were central to classical sociology and sociology of the 20th century (E.Durkheim, T.Parsons), turn out to be insufficient to explain new forms of social relations that arise in the post-industrial digital society, taking into account the current conditions of martial law and military aggression. In this context, the concept of “solidarity” acquires a new analytical content, since the system of social relations undergoes socio-cultural shifts and is defined as a “new sociality”. The systemic features of the “new sociality” – a flexible, situational and often hybrid form – are in fact a representative marker of instability, crisis, challenges, multiple identities and polyvariability of culture. The concept of “solidarity” goes beyond the normative traditional ideal of unity, offering alternative substantive meanings for comprehension. Discursive reflection on solidarity allows not only to identify transformations in the ways of social cohesion, but also to trace how new forms of solidarity are articulated not only in academic discourse, but also in the public and political field. This opens up prospects for a sociological rethinking of the concepts of solidarity, cohesion, interaction and social capital in the context of the latest socio-structural challenges of Ukrainian society. It is proven that the study of solidarity as a conceptual framework of the new sociality is not only theoretically significant, but also practically relevant for the analysis of contemporary processes of social cohesion, political mobilization and cultural integration. The results of the study can be used to develop strategies for social integration, form cohesion policies and rethink the role of solidarity in the conditions of wartime, digital transformation and cultural fragmentation.

Shayan Shokrgozar, Siddharth Sareen

Abstract Growing energy and material throughput, climate change targets and political economic evolution have spurred rapid deployment of lower‐carbon energy infrastructures. Many of these developments have relied on ‘cheap nature’, often covering agropastoral and indigenous lands, which raises questions about the implications of energy transitions for non‐industrial lifeways. This article explores the onto‐epistemological foundations that comprise the emergent energy transitions paradigm. Anchored in ethnographic findings from fieldwork in Rajasthan (India), we identify naturalism as the dominant ontological basis of knowledge production in global energy policies and examine its imaginaries and practices. We draw on Philippe Descola's ontological modes of identification to question universalism and demonstrate its perpetuation through energy transition practices. These approaches overlook socioecological complexity, a gap starkly showcased by the solar energy rollout in agropastoral Rajasthan, with Jaisalmer district as its epicentre. To overcome these limitations, we propose and empirically test the Situated Energy Ecologies principles, which combine (a) a post‐productivist approach based on a commitment to energy sufficiency; (b) a commitment to ontological and epistemic recognition, to better capture place‐based ways of knowing and being; and (c) autonomous practices based on prefigurative politics and agonism. By integrating a wider array of human experiences, this tripartite heuristic fosters a pluralistic understanding of energy‐society relations towards emancipatory engagement.

Stepanenko Ivan M. , Lyba Vasyl O.

The article explores the role of integrating Ukrainian machine building enterprises into value chains (VCs) as a decisive factor in their modernization and enhancing global competitiveness. The authors outline the theoretical foundations of VCs functioning and identify their impact on technological development, innovation activities, and the transformation of enterprise production and management models. The study systematizes the key integration barriers, including technological and infrastructural backwardness, investment shortages, personnel imbalances, and limited compliance with international standards. The study also analyzes current scientific approaches to studying integration processes in global production networks and highlights underdeveloped areas, including the assessment of management transformations, institutional support, and the risks associated with technological dependence. Based on logical-theoretical, systemic, structural-functional, and comparative analysis, the mechanisms and conditions under which integration into GVCs can accelerate the modernization of Ukrainian machine building have been identified. The practical significance of the study lies in formulating recommendations to enhance enterprise participation in global production networks: developing cluster structures, digitalization, improving logistics infrastructure, expanding innovation cooperation, and shifting to strategic planning focused on high-tech segments with high added value. The proposed approaches can be applied in the government industrial development policies, corporate strategies, and industrial modernization programs. Furthermore, the article emphasizes that integration into GVCs not only provides economic benefits for machine building enterprises but also introduces new requirements for production organization, quality management, and building partnership relations. The article shows that participation in global networks promotes the acceleration of technological upgrading, the development of engineering competencies, the enhancement of standardization levels, and the transition to «smart production» models. Special attention is given to the development of domestic value chains as a foundation for increasing localization, resilience, and the capacity of enterprises to act as full-fledged participants in international production systems.

Yao Song, Xiao Tan

This article examines how and why the Chinese central government has intensified its engagement with Shenzhen under Xi Jinping. It highlights new institutional mechanisms – comprehensive authorisation packages, inter-ministerial conference frameworks, and personnel secondment schemes – that enable Shenzhen to interact directly with central authorities, bypassing traditional bureaucratic intermediaries. These arrangements transform Shenzhen into a key site for aligning local policy experimentation with national priorities. Drawing on field interviews and policy documents, the article argues that these mechanisms reflect a targeted strategy to address three national imperatives: industrial upgrading, deeper integration with Hong Kong, and managing Sino–U.S. economic decoupling. The evolving relationship is underpinned by selective empowerment – a form of conditional delegation in which the centre entrusts select localities with expanded policy discretion under structured oversight. This model does not signify a shift towards decentralisation or recentralisation but reflects a recalibration of central–local relations, emphasising functional responsiveness over rigid hierarchy.

Kessia Nepomuceno, Fabio Petrillo

Context: Fairness in systems has emerged as a critical concern in software engineering, garnering increasing attention as the field has advanced in recent years. While several guidelines have been proposed to address fairness, achieving a comprehensive understanding of research solutions for ensuring fairness in software systems remains challenging. Objectives: This paper presents a systematic literature mapping to explore and categorize current advancements in fairness solutions within software engineering, focusing on three key dimensions: research trends, research focus, and viability in industrial contexts. Methods: We develop a classification framework to organize research on software fairness from a fresh perspective, applying it to 95 selected studies and analyzing their potential for industrial adoption. Results: Our findings reveal that software fairness research is expanding, yet it remains heavily focused on methods and algorithms. It primarily focuses on post-processing and group fairness, with less emphasis on early-stage interventions, individual fairness metrics, and understanding bias root causes. Additionally fairness research remains largely academic, with limited industry collaboration and low to medium Technology Readiness Level (TRL), indicating that industrial transferability remains distant. Conclusion: Our results underscore the need to incorporate fairness considerations across all stages of the software development life-cycle and to foster greater collaboration between academia and industry. This analysis provides a comprehensive overview of the field, offering a foundation to guide future research and practical applications of fairness in software systems.

Ruike Lyu, Anna Li, Jianxiao Wang et al.

In many countries, declining demand in energy-intensive industries such as cement, steel, and aluminum is leading to industrial overcapacity. Although industrial overcapacity is traditionally envisioned as problematic and resource-wasteful, it could unlock energy-intensive industries' flexibility in electricity use. Here, using China's aluminum smelting industry as a case study, we evaluate the system-level cost-benefit of retaining energy-intensive industries overcapacity for flexible electricity use in decarbonized energy systems. We find that overcapacity can enable aluminum smelters to adopt a seasonal operation paradigm, ceasing production during winter load peaks that are exacerbated by heating electrification and renewable seasonality. This seasonal operation paradigm could reduce the investment and operational costs of China's decarbonized electricity system by 23-32 billion CNY/year (11-15% of the aluminum smelting industry's product value), sufficient to offset the increased smelter maintenance and product storage costs associated with overcapacity. It may also provide an opportunity for seasonally complementary labor deployment across the aluminum smelting and thermal power generation sectors, offering a potential pathway for mitigating socio-economic disruptions caused by industrial restructuring and energy decarbonization.

Mari Ashiga, Vardan Voskanyan, Fateme Dinmohammadi et al.

Recent advancements in Large Language Models (LLMs) for code optimization have enabled industrial platforms to automate software performance engineering at unprecedented scale and speed. Yet, organizations in regulated industries face strict constraints on which LLMs they can use - many cannot utilize commercial models due to data privacy regulations and compliance requirements, creating a significant challenge for achieving high-quality code optimization while maintaining cost-effectiveness. We address this by implementing a Mixture-of-Agents (MoA) approach that directly synthesizes code from multiple specialized LLMs, comparing it against TurinTech AI's vanilla Genetic Algorithm (GA)-based ensemble system and individual LLM optimizers using real-world industrial codebases. Our key contributions include: (1) First MoA application to industrial code optimization using real-world codebases; (2) Empirical evidence that MoA excels with open-source models, achieving 14.3% to 22.2% cost savings and 28.6% to 32.2% faster optimization times for regulated environments; (3) Deployment guidelines demonstrating GA's advantage with commercial models while both ensembles outperform individual LLMs; and (4) Real-world validation across 50 code snippets and seven LLM combinations, generating over 8,700 variants, addresses gaps in industrial LLM ensemble evaluation. This provides actionable guidance for organizations balancing regulatory compliance with optimization performance in production environments.

Duygu Kabakci-Zorlu, Fabio Lorenzi, John Sheehan et al.

We propose an interactive system using foundation models and user-provided technical documents to generate Failure Mode and Effects Analyses (FMEA) for industrial equipment. Our system aggregates unstructured content across documents to generate an FMEA and stores it in a relational database. Leveraging this tool, the time required for creation of this knowledge-intensive content is reduced, outperforming traditional manual approaches. This demonstration showcases the potential of foundation models to facilitate the creation of specialized structured content for enterprise asset management systems.

Tianle Yang, Luyao Chang, Jiadong Yan et al.

As industrial products become abundant and sophisticated, visual industrial defect detection receives much attention, including two-dimensional and three-dimensional visual feature modeling. Traditional methods use statistical analysis, abnormal data synthesis modeling, and generation-based models to separate product defect features and complete defect detection. Recently, the emergence of foundation models has brought visual and textual semantic prior knowledge. Many methods are based on foundation models (FM) to improve the accuracy of detection, but at the same time, increase model complexity and slow down inference speed. Some FM-based methods have begun to explore lightweight modeling ways, which have gradually attracted attention and deserve to be systematically analyzed. In this paper, we conduct a systematic survey with comparisons and discussions of foundation model methods from different aspects and briefly review non-foundation model (NFM) methods recently published. Furthermore, we discuss the differences between FM and NFM methods from training objectives, model structure and scale, model performance, and potential directions for future exploration. Through comparison, we find FM methods are more suitable for few-shot and zero-shot learning, which are more in line with actual industrial application scenarios and worthy of in-depth research.

Bowen Zheng

To address the challenges of 3D modeling and structural simulation in industrial environment, such as the difficulty of equipment deployment, and the difficulty of balancing accuracy and real-time performance, this paper proposes an integrated workflow, which integrates high-fidelity 3D reconstruction based on monocular video, finite element simulation analysis, and mixed reality visual display, aiming to build an interactive digital twin system for industrial inspection, equipment maintenance and other scenes. Firstly, the Neuralangelo algorithm based on deep learning is used to reconstruct the 3D mesh model with rich details from the surround-shot video. Then, the QuadRemesh tool of Rhino is used to optimize the initial triangular mesh and generate a structured mesh suitable for finite element analysis. The optimized mesh is further discretized by HyperMesh, and the material parameter setting and stress simulation are carried out in Abaqus to obtain high-precision stress and deformation results. Finally, combined with Unity and Vuforia engine, the real-time superposition and interactive operation of simulation results in the augmented reality environment are realized, which improves users 'intuitive understanding of structural response. Experiments show that the method has good simulation efficiency and visualization effect while maintaining high geometric accuracy. It provides a practical solution for digital modeling, mechanical analysis and interactive display in complex industrial scenes, and lays a foundation for the deep integration of digital twin and mixed reality technology in industrial applications.

Francesco Aurelio Pironti, Angelo Furfaro, Francesco Blefari et al.

The security of Industrial Control Systems (ICSs) is critical to ensuring the safety of industrial processes and personnel. The rapid adoption of Industrial Internet of Things (IIoT) technologies has expanded system functionality but also increased the attack surface, exposing ICSs to a growing range of cyber threats. Honeypots provide a means to detect and analyze such threats by emulating target systems and capturing attacker behavior. However, traditional ICS honeypots, often limited to software-based simulations of a single Programmable Logic Controller (PLC), lack the realism required to engage sophisticated adversaries. In this work, we introduce a modular honeynet framework named ICSLure. The framework has been designed to emulate realistic ICS environments. Our approach integrates physical PLCs interacting with live data sources via industrial protocols such as Modbus and Profinet RTU, along with virtualized network components including routers, switches, and Remote Terminal Units (RTUs). The system incorporates comprehensive monitoring capabilities to collect detailed logs of attacker interactions. We demonstrate that our framework enables coherent and high-fidelity emulation of real-world industrial plants. This high-interaction environment significantly enhances the quality of threat data collected and supports advanced analysis of ICS-specific attack strategies, contributing to more effective detection and mitigation techniques.

P. Shrivastava