Hasil untuk "Industrial relations"

Puyu Zeng, Zhaoxi Wang, Zhixu Duan et al.

Code generation and comprehension by Large Language Models (LLMs) have emerged as core drivers of industrial intelligence and decision optimization, finding widespread application in fields such as finance, automation, and aerospace. Although recent advancements have demonstrated the remarkable potential of LLMs in general code generation, existing benchmarks are mainly confined to single domains and languages. Consequently, they fail to effectively evaluate the generalization capabilities required for real-world industrial applications or to reflect the coding proficiency demanded by complex industrial scenarios. To bridge this gap, we introduce IndustryCode, the first comprehensive benchmark designed to span multiple industrial domains and programming languages. IndustryCode comprises 579 sub-problems derived from 125 primary industrial challenges, accompanied by rigorous problem descriptions and test cases. It covers a wide range of fields, including finance, automation, aerospace, and remote sensing-and incorporates diverse programming languages such as MATLAB, Python, C++, and Stata. In our evaluation, the top-performing model, Claude 4.5 Opus, achieved an overall accuracy of 68.1% on sub-problems and 42.5% main problems. The benchmark dataset and automated evaluation code will be made publicly available upon acceptance.

Rifki Maulana Iqbal Taufik, Tri Kurnia Revul Andina

This research aims to examine the impact of automation on future work in Indonesia's agriculture sector. Internet and digital platforms have altered many aspects of life and resulted in automation in several fields, including agriculture. The emergence of new technologies is often perceived as a threat and a challenge for this sector and its workers. Using a desk study method, however, the result shows that the automation of agriculture is beneficial to Indonesia’s economy. This is not only in terms of gross domestic product (GDP) but also in terms of enhancing the quality of smallholder employment and the interest of youth in working in this sector. Farmers' use of the internet and smartphones have become catalysts in adopting automation in the present and emerging. Digital technology has become an important intermediate factor that helps farmers improve their productivity. This has become the mainstream of the adoption of the technology in agriculture rather than mechanization. Job replacement due to automation will possibly not happen in Indonesia due to labour market conditions, disparity of land ownership, and the high cost of implementing automation. Furthermore, this research addresses aspects that deserve attention, including job quality, social protection, industrial relations, inequality, gender, and participation.

Abdelrahman Alzarooni, Ehtesham Iqbal, Samee Ullah Khan et al.

Anomaly detection from images captured using camera sensors is one of the mainstream applications at the industrial level. Particularly, it maintains the quality and optimizes the efficiency in production processes across diverse industrial tasks, including advanced manufacturing and aerospace engineering. Traditional anomaly detection workflow is based on a manual inspection by human operators, which is a tedious task. Advances in intelligent automated inspection systems have revolutionized the Industrial Anomaly Detection (IAD) process. Recent vision-based approaches can automatically extract, process, and interpret features using computer vision and align with the goals of automation in industrial operations. In light of the shift in inspection methodologies, this survey reviews studies published since 2019, with a specific focus on vision-based anomaly detection. The components of an IAD pipeline that are overlooked in existing surveys are presented, including areas related to data acquisition, preprocessing, learning mechanisms, and evaluation. In addition to the collected publications, several scientific and industry-related challenges and their perspective solutions are highlighted. Popular and relevant industrial datasets are also summarized, providing further insight into inspection applications. Finally, future directions of vision-based IAD are discussed, offering researchers insight into the state-of-the-art of industrial inspection.

Shinichi Mae, Ryousuke Yamada, Hirokatsu Kataoka

Pre-training on real-image datasets has been widely proven effective for improving instance segmentation. However, industrial applications face two key challenges: (1) legal and ethical restrictions, such as ImageNet's prohibition of commercial use, and (2) limited transferability due to the domain gap between web images and industrial imagery. Even recent vision foundation models, including the segment anything model (SAM), show notable performance degradation in industrial settings. These challenges raise critical questions: Can we build a vision foundation model for industrial applications without relying on real images or manual annotations? And can such models outperform even fine-tuned SAM on industrial datasets? To address these questions, we propose the Instance Core Segmentation Dataset (InsCore), a synthetic pre-training dataset based on formula-driven supervised learning (FDSL). InsCore generates fully annotated instance segmentation images that reflect key characteristics of industrial data, including complex occlusions, dense hierarchical masks, and diverse non-rigid shapes, distinct from typical web imagery. Unlike previous methods, InsCore requires neither real images nor human annotations. Experiments on five industrial datasets show that models pre-trained with InsCore outperform those trained on COCO and ImageNet-21k, as well as fine-tuned SAM, achieving an average improvement of 6.2 points in instance segmentation performance. This result is achieved using only 100k synthetic images, more than 100 times fewer than the 11 million images in SAM's SA-1B dataset, demonstrating the data efficiency of our approach. These findings position InsCore as a practical and license-free vision foundation model for industrial applications.

Jay Lee, Hanqi Su

Recent advancements in industrial artificial intelligence (AI) are reshaping the industry by driving smarter manufacturing, predictive maintenance, and intelligent decision-making. However, existing approaches often focus primarily on algorithms and models while overlooking the importance of systematically integrating domain knowledge, data, and models to develop more comprehensive and effective AI solutions. Therefore, the effective development and deployment of industrial AI require a more comprehensive and systematic approach. To address this gap, this paper reviews previous research, rethinks the role of industrial AI, and proposes a unified industrial AI foundation framework comprising three core modules: the knowledge module, data module, and model module. These modules help to extend and enhance the industrial AI methodology platform, supporting various industrial applications. In addition, a case study on rotating machinery diagnosis is presented to demonstrate the effectiveness of the proposed framework, and several future directions are highlighted for the development of the industrial AI foundation framework.

Hang Yu, Yuzhou Lai, Li Zhang et al.

The rapid advancement of large language models (LLMs) is fundamentally reshaping software engineering (SE), driving a paradigm shift in both academic research and industrial practice. While top-tier SE venues continue to show sustained or emerging focus on areas like automated testing and program repair, with researchers worldwide reporting continuous performance gains, the alignment of these academic advances with real industrial needs remains unclear. To bridge this gap, we first conduct a systematic analysis of 1,367 papers published in FSE, ASE, and ICSE between 2022 and 2025, identifying key research topics, commonly used benchmarks, industrial relevance, and open-source availability. We then carry out an empirical survey across 17 organizations, collecting 282 responses on six prominent topics, i.e., program analysis, automated testing, code generation/completion, issue resolution, pre-trained code models, and dependency management, through structured questionnaires. By contrasting academic capabilities with industrial feedback, we derive seven critical implications, highlighting under-addressed challenges in software requirements and architecture, the reliability and explainability of intelligent SE approaches, input assumptions in academic research, practical evaluation tensions, and ethical considerations. This study aims to refocus academic attention on these important yet under-explored problems and to guide future SE research toward greater industrial impact.

Christian Bergqvist, Camilla Ringeling, Mariana Camacho

Objetivo: o artigo discute a colusão de Inteligência Artificial (IA) e o potencial da tomada de decisão impulsionada por IA para permitir que entidades se coordenem de maneiras anticompetitivas que podem escapar dos mecanismos de fiscalização atuais. Método: por meio de pesquisa bibliográfica e documental, o estudo examina as implicações da tomada de decisão apoiada por IA na coordenação de mercado e colusão. Analisa casos de enforcement na União Europeia (UE), nos EUA e na América Latina e identifica lacunas na aplicação da lei. Além disso, explora as diferenças entre o direito da concorrência da UE,a lei antitruste dos EUA e a abordagem adotada por algumas jurisdições latino-americanas no contexto da colusão orientada por IA. Conclusões: a principal preocupação com as decisões de preços baseadas em IA, do ponto de vista do antitruste, é que elas podem facilitar resultados colusivos fora do alcance da fiscalização antitruste. Dada a probabilidade de que as IAs de precificação tornem mais fácil para as empresas adotarem comportamentos paralelos, há um temor bem justificado de que isso amplie essa área cinzenta, onde o comportamento paralelo legal e a colusão tácita se tornam cada vez mais indistinguíveis. Seria prudente que os fiscais na América Latina seguissem os exemplos europeu e estadunidense e considerassem o risco da colusão orientada por IA.

Pierre Thévenin, Emmanuel Ducourneau, Anthony Stavrianakis

This article presents an interlinked series of inquiries concerning the material inscription of language. This inscription is explored in its poetic and symptomatic aspects, as well as by way of a “machined” cartography. Sound and concrete poems isolate the acoustic component of oral language and the visual dimension of writing. A figure in the domain of art brut invents alphabets to grasp the being of words. A designer seeks to apply his “onto-cartographic” method beyond an original application to industrial design objects. Integrating these three investigations into the same experimental set, we endeavoured to meta-model the way in which investment in the plastic and sonic values of language expands, and disrupts the field of signification. Our experimental method involves building a machine, based on the upcycling of a video game terminal. We describe its genesis and show how its design reflects, in turn, four “material planes” of a poem by Bernard Heidsieck, and a dual topological series of images by Francis Palanc, pertaining to the possible and impossible relations between signifiers.

İbrahim Yılmaz

This study is about civil servants’ union rights in Türkiye during the Cold War. The article will also discuss trade union rights the right to organize a union, the right to collective bargaining, and the right to strike. The aim of this study is to compare the developments regarding civil servants’ union rights in Türkiye during the Cold War with the developments in the Western Bloc. The article uses the document analysis method to examine the developments regarding civil servants’ union rights in Türkiye and the Western Bloc and evaluates the changes that occurred in Türkiye primarily through the Turkish Constitution and laws of the period, as well as through the discussions that occurred in the Grand National Assembly of Türkiye as these legislations were being formed. The article uses the international documents created by the United Nations, the International Labour Organization, and the Council of Europe to examine the developments in the Western Bloc. Türkiye, which was trying to integrate into the Western Bloc that was led by United States both militarily and ideologically during the Cold War, can be said to have differed from its allies in terms of its civil servants’ union rights, except for the period between 1961-1971. In a broad sense, Türkiye can be argued to have fallen far behind its Western allies during the Cold War in terms of recognizing and securing its civil servants’ union rights at the constitutional and legal levels.

Felipe Leitão Valadares Roquete

Contexto: diagnósticos recentes, realizados por organismos internacionais e por pesquisadores, identificam possível arrefecimento na atratividade de Programas de Leniência Antitruste. A determinação das possíveis causas é desafiadora, uma vez que existem diferenças institucionais significativas entre as diversas jurisdições, bem como o acesso a dados detalhados sobre os programas é restrito devido à sua natureza sigilosa, o que dificulta não apenas o diagnóstico preciso, mas também o desenho de propostas de aperfeiçoamento que sejam aderentes às especificidades de cada programa. Objetivo: o trabalho pretende analisar resultados de pesquisas empíricas, realizadas por outros pesquisadores e/ou organismos internacionais, sobre Programas de Leniência Antitruste, a fim de avaliar criticamente os diagnósticos recentes, bem como apresentar estatísticas descritivas sobre o Programa de Leniência brasileiro. Método: revisão de literatura e análise exploratória de estatísticas descritivas. Conclusões: diagnósticos e cenários sobre Programas de Leniência Antitruste precisam ser avaliados à luz das especificidades institucionais de cada jurisdição e, para tanto, é necessário que sejam analisados dados não apenas sobre os resultados dos programas, mas também sobre a dinâmica do processo de negociação.

Siqi Wang, Chao Liang, Yunfan Gao et al.

Industrial parks are critical to urban economic growth. Yet, their development often encounters challenges stemming from imbalances between industrial requirements and urban services, underscoring the need for strategic planning and operations. This paper introduces IndustryScopeKG, a pioneering large-scale multi-modal, multi-level industrial park knowledge graph, which integrates diverse urban data including street views, corporate, socio-economic, and geospatial information, capturing the complex relationships and semantics within industrial parks. Alongside this, we present the IndustryScopeGPT framework, which leverages Large Language Models (LLMs) with Monte Carlo Tree Search to enhance tool-augmented reasoning and decision-making in Industrial Park Planning and Operation (IPPO). Our work significantly improves site recommendation and functional planning, demonstrating the potential of combining LLMs with structured datasets to advance industrial park management. This approach sets a new benchmark for intelligent IPPO research and lays a robust foundation for advancing urban industrial development. The dataset and related code are available at https://github.com/Tongji-KGLLM/IndustryScope.

Xiao Wang, Yutong Wang, Jing Yang et al.

As the concept of Industries 5.0 develops, industrial metaverses are expected to operate in parallel with the actual industrial processes to offer ``Human-Centric" Safe, Secure, Sustainable, Sensitive, Service, and Smartness ``6S" manufacturing solutions. Industrial metaverses not only visualize the process of productivity in a dynamic and evolutional way, but also provide an immersive laboratory experimental environment for optimizing and remodeling the process. Besides, the customized user needs that are hidden in social media data can be discovered by social computing technologies, which introduces an input channel for building the whole social manufacturing process including industrial metaverses. This makes the fusion of multi-source data cross Cyber-Physical-Social Systems (CPSS) the foundational and key challenge. This work firstly proposes a multi-source-data-fusion-driven operational architecture for industrial metaverses on the basis of conducting a comprehensive literature review on the state-of-the-art multi-source data fusion methods. The advantages and disadvantages of each type of method are analyzed by considering the fusion mechanisms and application scenarios. Especially, we combine the strengths of deep learning and knowledge graphs in scalability and parallel computation to enable our proposed framework the ability of prescriptive optimization and evolution. This integration can address the shortcomings of deep learning in terms of explainability and fact fabrication, as well as overcoming the incompleteness and the challenges of construction and maintenance inherent in knowledge graphs. The effectiveness of the proposed architecture is validated through a parallel weaving case study. In the end, we discuss the challenges and future directions of multi-source data fusion cross CPSS for industrial metaverses and social manufacturing in Industries 5.0.

Ahmed Gailani, Peter Taylor

Decarbonising the industrial sector is vital to reach net zero targets. The deployment of industrial decarbonisation technologies is expected to increase industrial electricity demand in many countries and this may require upgrades to the existing electricity network or new network investment. While the infrastructure requirements to support the introduction of new fuels and technologies in industry, such as hydrogen and carbon capture, utilisation and storage are often discussed, the need for investment to increase the capacity of the electricity network to meet increasing industrial electricity demands is often overlooked in the literature. This paper addresses this gap by quantifying the requirements for additional electricity network capacity to support the decarbonisation of industrial sectors across Great Britain (GB). The Net Zero Industrial Pathways model is used to predict the future electricity demand from industrial sites to 2050 which is then compared spatially to the available headroom across the distribution network in GB. The results show that network headroom is sufficient to meet extra capacity demands from industrial sites over the period to 2030 in nearly all GB regions and network scenarios. However, as electricity demand rises due to increased electrification across all sectors and industrial decarbonisation accelerates towards 2050, the network will need significant new capacity (71 GW + by 2050) particularly in the central, south, and north-west regions of England, and Wales. Without solving these network constraints, around 65% of industrial sites that are large point sources of emissions would be constrained in terms of electric capacity by 2040. These sites are responsible for 69% of industrial point source emissions.

Simon Liebl, Leah Lathrop, Ulrich Raithel et al.

As part of the Internet of Things, industrial devices are now also connected to cloud services. However, the connection to the Internet increases the risks for Industrial Control Systems. Therefore, a threat analysis is essential for these devices. In this paper, we examine Industrial Internet of Things devices, identify and rank different sources of threats and describe common threats and vulnerabilities. Finally, we recommend a procedure to carry out a threat analysis on these devices.

Viktoriia Patsiuk, Volodymyr Kazakov

Formulation of the problem. The world is constantly moving towards the post-industrial phase of development of society, and if the majority of civilized Western countries have decided on their place and role, the cities of Ukraine are just beginning to outline their future landmarks. This is especially true for the future of single-industry cities, the number of which in Ukraine is quite large. Kryvyi Rih is the largest city with exclusively industrial specialization, performing administrative functions only at the local level and having a scientific sector almost completely focused on the needs of the industrial complex. For the last 10 years, managers and scientists have been actively thinking about the problem of diversifying the city's economy and changing its image, and this is reflected in the Marketing Strategy for the city development. Industrial tourism is one of the key tasks of the Strategy. The promising character of the chosen direction of activities is confirmed by the practice of European countries, which are guidelines for development for us. This is due to the fact that not only individual cities, but also entire regions of Great Britain, Germany, France, Poland, the Czech Republic have a wide experience in regeneration of former industrial territories and further popularization of successful practices through industrial tourism. Methods. The research is based on the system approach and the dialectical method of cognition. The key scientific results are obtained using a complex of general scientific methods, namely: analysis and synthesis, abstraction, theoretical generalization. The historical method enables determining significant moments for development of this tourist destination. With the help of these methods, industrial tourism is considered in its internal and external relations entirety. The simulation method enables presenting the organizational model of this tourist destination at the local level. Comparative-geographical and statistical analysis methods allow assessment of the state and dynamics of tourism development in Kryvorizhzhia (Kryvyi Rih region). Based on the method of observation and analysis, the most visited objects of industrial tourism in Kryvyi Rih are systematized and their base map is created. The study aims to analyze best practices of implementing theoretical developments concerning establishment of industrial tourism in Kryvorizhzhia so that Ukrainian cities with similar resources can factor in all positive areas and minimize shortcomings. Results. The theoretical foundations of industrial tourism establishment are analyzed and this definition is outlined. The practice of Kryvyi Rih concerning integrated development of industrial tourism as a direction of further regeneration of the city, which is pioneering for our country, is revealed, the results obtained are analyzed and available shortcomings are identified. Scientific novelty and practical significance. An organizational model of industrial tourism has been developed, which demonstrates the relationship between the resource of the territory and the management mechanism for introducing tourist activities in order to create a tourist product and bring it to the tourist.

Fouad Oubari, Raphael Meunier, Rodrigue Décatoire et al.

Generative design is an increasingly important tool in the industrial world. It allows the designers and engineers to easily explore vast ranges of design options, providing a cheaper and faster alternative to the trial and failure approaches. Thanks to the flexibility they offer, Deep Generative Models are gaining popularity amongst Generative Design technologies. However, developing and evaluating these models can be challenging. The field lacks accessible benchmarks, in order to evaluate and compare objectively different Deep Generative Models architectures. Moreover, vanilla Deep Generative Models appear to be unable to accurately generate multi-components industrial systems that are controlled by latent design constraints. To address these challenges, we propose an industry-inspired use case that incorporates actual industrial system characteristics. This use case can be quickly generated and used as a benchmark. We propose a Meta-VAE capable of producing multi-component industrial systems and showcase its application on the proposed use case.

Stein Tore Johansen, Bjørn Tore Løvfall, Tamara Rodriguez Duran et al.

A methodology for building pragmatic physics based models (Zoric et al., 2015b) is here adapted to a use-case in the steel industry. The challenge is to predict the erosion of steel ladle linings, such that the model can support operators to decide if the lade lining can be used one more time or not. If the ladle has too thin lining 140 tons of hot liquid steel may escape out of the ladle, with huge consequences for workers and plant. The development was done with a very small core team (two developers), which is typical for many industrial developments. The adopted workflow for the development, challenges that were faced, and some model results are presented. One key learning is that development of models should allow time for maturing the process understanding, and time should be given for many iterations by "questions-responses and actions" at the various levels in the model development. The good interactions between development team and industry case owner is an important success factor. In this case the results of using the PPBM (Pragmatism in physics-based modelling) were good thanks to very successful interaction between development team and industry case owner. Combining or extending the model with use of ML methods and cognition-related methods, such as knowledge graphs and self-adaptive algorithms is discussed.

Hanife Candır Şimşek

The aim of the study is to discover which concepts explain the views of women who receive education from a continuing education center and to give meaning to the subject. In line with this, Istanbul University Continuing Education Center has taken place within the scope of the study. The study uses embedded theory design with the aim of examining the participants’ opinions in depth. The study group consists of 26 female participants. The interviews were coded using the program NVivo 10, after which the codes were gathered under categories and made meaningful. The study includes examples the participants’ expressions under the categories within the scope of the descriptive analysis. According to the research findings, the emphasis on vocational education is at the forefront in terms of the participants’ perceptions regarding the role that continuing education centers have in society. Similarly, the purpose of vocational education is understood to have been determinant regarding participating in trainings; however, this was due not to having acquired a new profession but to reasons such as being better in the current profession, relieving deficiencies, following the developments in their profession, and rising in the profession.

Kazhan Othman Mohammed Salih, Tarik A. Rashid, Dalibor Radovanovic et al.

There is no doubt that new technology has become one of the crucial parts of most people's lives around the world. By and large, in this era, the Internet and the Internet of Things (IoT) have become the most indispensable parts of our lives. Recently, IoT technologies have been regarded as the most broadly used tools among other technologies. The tools and the facilities of IoT tech-nologies within the marketplace are part of Industry 4.0. The marketplace is too regarded as a new area that can be used with IoT technologies. One of the main purposes of this paper is to highlight using IoT technologies in Industry 4.0, and the Industrial Internet of Things (IIoT) is another feature revised. This paper focuses on the value of the IoT in the industrial domain in general; it reviews the IoT and focuses on its benefits and drawbacks, and presents some of the IoT applications, such as in transportation and healthcare. In addition, the trends and facts that are related to the IoT technologies on the marketplace are reviewed. Finally, the role of IoT in telemedicine and healthcare and the benefits of IoT technologies for COVID-19 are presented as well.

O. S. Pugacheva

The relations between South Korea and North Korea were improved in 2018 on the basis of the Sunshine policy ideational platform and the inter-Korean agreements reached between the two countries under the progressive administrations of Kim Dae-jung in 2000 and Roh Moohyun in 2007. However, inter-Korean relations had been at a lull since the US-North Korea summit in Hanoi in February 2019 despite the intentions of the parties to develop diverse forms of cooperation. After that, the month of June saw a severe deterioration in the Inter-Korean relations. The aim of this article is to analyze the inter-Korean relations and the North Korean policies of the South Korean governments from 1998 to 2020 as well as explain the reasons behind Seoul’s inability to make progress in dialogue with Pyongyang. South Korea’s prioritizing of its ties with the United States as well as its increased dependence on the United States were the main reason behind the stagnation of inter-Korean relations. Under the international regime of sanctions against the DPRK, Moon Jae-In has failed to put the Sunshine policy into practice, for instance, re-open Kaesong Industrial Complex and Mount Kumgang tourism zone. The fact that inter-Korean economic cooperation was actually still linked to the denuclearization of the DPRK also had a negative impact on the prospects for maintaining the positive dynamics of inter-Korean relations. The exacerbation of inter-Korean relations in June 2020 showed that in the absence of practical inter-Korean cooperation and with the continuing deadlock in the US-North Korean negotiations on the nuclear issue, Pyongyang is not interested in normalizing relations with Seoul and it can concentrate on relations with the United States. At the same time, the intensifying confrontation between China and the United States in the Asia-Pacific region is not conducive to a political settlement of the Korean Peninsula nuclear issue and it can potentially lead to an aggravation of inter-Korean relations.