Hasil untuk "Management. Industrial management"

K. Govindan, Mathiyazhagan Kaliyan, Devika Kannan et al.

Fadi Shrouf, Joaquín B. Ordieres Meré, G. Miragliotta

Keerththanan Vickneswaran, Mariangel Garcia Andarcia, Hugo Retief et al.

Sustainable water resource management in transboundary river basins is challenged by fragmented data, limited real-time access, and the complexity of integrating diverse information sources. This paper presents WaterCopilot-an AI-driven virtual assistant developed through collaboration between the International Water Management Institute (IWMI) and Microsoft Research for the Limpopo River Basin (LRB) to bridge these gaps through a unified, interactive platform. Built on Retrieval-Augmented Generation (RAG) and tool-calling architectures, WaterCopilot integrates static policy documents and real-time hydrological data via two custom plugins: the iwmi-doc-plugin, which enables semantic search over indexed documents using Azure AI Search, and the iwmi-api-plugin, which queries live databases to deliver dynamic insights such as environmental-flow alerts, rainfall trends, reservoir levels, water accounting, and irrigation data. The system features guided multilingual interactions (English, Portuguese, French), transparent source referencing, automated calculations, and visualization capabilities. Evaluated using the RAGAS framework, WaterCopilot achieves an overall score of 0.8043, with high answer relevancy (0.8571) and context precision (0.8009). Key innovations include automated threshold-based alerts, integration with the LRB Digital Twin, and a scalable deployment pipeline hosted on AWS. While limitations in processing non-English technical documents and API latency remain, WaterCopilot establishes a replicable AI-augmented framework for enhancing water governance in data-scarce, transboundary contexts. The study demonstrates the potential of this AI assistant to support informed, timely decision-making and strengthen water security in complex river basins.

H. Andersson, Arild Hoff, Marielle Christiansen et al.

Michael Sony

ABSTRACT Lean Management (LM) is one of the most widely used business strategies for the last three decades. Industry 4.0 shows all the promise of the fourth industrial revolution using automation technologies like cyber-physical systems, internet of things and cloud computing. The purpose of this paper is to propose an integration model of Industry 4.0 and LM. A summary literature review of Industry 4.0 and LM is carried out to construct a theoretical model of integration. The previous literature is used to develop and propose an integration model of Industry 4.0 and LM. The horizontal, vertical and end-to-end engineering integration model are integrated with LM methodology. Testable research propositions are proposed between Industry 4.0 and LM. The model proposed is novel and it raises the important issue of integration of LM with Industry 4.0. This is the first paper which proposes the integration framework of LM with Industry 4.0.

Jun Wang, Peng Wu, Xiangyu Wang et al.

Jacob Lohmer, R. Lasch

Abstract Transparency, visibility, and disintermediation are some of the prospects of the aspiring blockchain technology in the business-to-business context. The digital transformation and Industry 4.0 trends also facilitate blockchain applications in operations management (OM) and manufacturing. However, scientific contributions and successful industrial applications in this area are still scarce and mainly at a proof-of-concept stage. The empirical research in this article is based on an expert interview study to uncover and analyse the potential and barriers to the adoption of blockchain technology in OM and manufacturing from within the industry. Semi-structured interviews with industry experts are employed to elaborate on promising practices for the industry to efficiently promote blockchain adoption and meaningful research directions for scholars. Findings include unexplored potential regarding distributed production networks and collaboration, expected evolutionary steps of IoT, disintermediation leading to new business models like tokenisation, and short-term rather than long-term relationships. Current barriers include staff difficulties, legal uncertainties, missing infrastructure and standardisation, and unclear governance structures. Improving smart contract security and interoperability of private and public protocols will enable further dissemination of the technology. Managers and academic scholars can address these findings and new propositions of this study in future application development and implementation.

Z. Whysall, M. Owtram, S. Brittain

Purpose The transformational changes to business environments brought about by the fourth industrial revolution create a perfect storm for strategic human resource management, prompting a need to explore the implications of this context for talent management theory and practice. The paper aims to discuss these issues. Design/methodology/approach In-depth interviews were conducted with HR directors and senior leaders within engineering-led organisations to explore current challenges experienced across each stage of the talent pipeline: attraction and recruitment, training and development, career development, talent mobility and succession planning. Findings The speed of technological change brought about by Industry 4.0 had created a significant gap between current capability of employees and the rapidly evolving requirements of their roles, prompting a need to consider new and more effective approaches to talent development. Middle managers are increasingly recognised as overlooked critical talent within this context of unprecedented change, given their essential role in change management. In addition, whilst lateral hiring remains a common talent management practice, in the case of Industry 4.0 this equates to fighting a war for talent that does not exist. Practical implications This study suggests that there is a need for evolution of talent management theory and practice towards a more dynamic, systems-thinking orientation, acknowledging the interrelated nature of different talent management activities. Originality/value This paper provides an in-depth insight into the impact of the unprecedented change brought about by Industry 4.0 on contemporary talent management practice, considering how theory and practice might need to evolve to enable individuals and organisations to keep up with the rate of technological change.

Ali Abbasi Godarzi, Khadijeh Abdi Rokni

Energy intensity is one of the most important energy feature that has a dramatic value in energy system of Iran. Indeed, Iran is one of the most energy intensive countries in the world and its main reason is related to high energy consumption in household section. In this article, we present a non-linear model that considers three scenarios in management of household energy demand reducing. Therefore, a rational percentage of energy consumption reduction in the household sector, which firstly eliminates the imbalance between energy production and consumption, and secondly, derives a rational amount of profit from various reduction scenarios, will be presented. The mentioned rational profits in this article are obtained from three scenarios. In the first scenario, it is assumed that the percentage reduction in household energy consumption will be allocated to reducing energy demand in the industrial sector, resulting in profits from value-added creation in this sector. In the second scenario, all benefits from reducing energy consumption in the household sector will be devoted to energy exports, yielding profits from this source. Finally, in the third scenario, the reduction in energy consumption will lead to a decrease in energy supply and consequently a reduction in energy supply costs. To conduct a comprehensive study, a combination of the mentioned scenarios has also been modeled and investigated. The model results indicate that with a 25% reduction in household energy consumption in the 2024-2034 timeframe, the energy imbalance will be eliminated, and allocating 5% of this reduction entirely to the industrial sector will result in profits equivalent to $164.18 billion. However, it should be noted that in the considered combined scenarios, the greater the share of the first scenario, the higher the resulting profit, and the optimal point is achieved in the first scenario.

Д. Луцак, М. Ткач

У статті розглянуто актуальність проблеми впровадження віртуальних голосових асистентів зі штучним інтелектом у сучасне життя. Аналізуються особливості їх застосування у різних сферах, від персонального використання до інтеграції в бізнес- процеси, з метою підвищення ефективності роботи та покращення якості обслугову- вання. Віртуальні асистенти допомагають оптимізувати взаємодію з цифровими пристроями, виконують різноманітні завдання на основі голосових або текстових команд, що робить їх універсальними інструментами для автоматизації повсякденних функцій. Окремо досліджується здатність цих систем до навчання та адаптації до індивідуальних потреб користувачів завдяки застосуванню технологій штучного інтелекту. Проаналізовано останні дослідження науковців у цій сфері та наведено приклади ефективного застосування віртуальних асистентів у різних галузях. Бібл. 14, іл. 2, табл. 2

Angga Yesaya, Vivi Arisandhy, David Try Liputra

Penelitian mengenai pemilihan atau penentuan supplier dengan menggunakan metode AHP maupun kombinasinya dengan metode TOPSIS dalam penentuan supplier di industri penghasil kasur pegas belum banyak dilakukan. Penelitian ini akan membahas penerapan gabungan metode AHP dan TOPSIS dalam penentuan supplier di industri penghasil kasur pegas sehingga diharapkan hasil yang diperoleh lebih akurat dibandingkan jika hanya menggunakan salah satu metode. PT XYZ melakukan pemesanan bahan baku kawat kepada 4 supplier dan mengalokasikan pesanan dengan jumlah yang sama rata. Langkah pertama yang dilakukan adalah penentuan kriteria dan subkriteria untuk pemilihan supplier dan penyusunan hierarki. Selanjutnya dilakukan penyusunan kuesioner perbandingan berpasangan untuk menentukan tingkat kepentingan kriteria dan subkriteria. Setelah dilakukan perhitungan dengan metode AHP, diperoleh bobot kriteria dan subkriteria yang menjadi input untuk metode TOPSIS. TOPSIS digunakan untuk mengetahui supplier yang memiliki kinerja terbaik. Hasil yang diperoleh adalah kriteria Price dan subkriteria Harga Bahan Baku mempunyai tingkat kepentingan tertinggi dalam penilaian kinerja supplier kawat karena memiliki bobot tertinggi. Perusahaan dapat tetap menggunakan kebijakan multi-supplier dengan memprioritaskan supplier 1, namun ada beberapa kriteria dari kinerja supplier 1 yang perlu ditingkatkan jika dibandingkan dengan supplier lainnya. Kata Kunci: AHP, Bahan Baku Utama, Kasur Pegas, Supplier, TOPSIS.

Shunzhi Pang

With the rise of emerging risks, model uncertainty poses a fundamental challenge in the insurance industry, making robust pricing a first-order question. This paper investigates how insurers' robustness preferences shape competitive equilibrium in a dynamic insurance market. Insurers optimize their underwriting and liquidity management strategies to maximize shareholder value, leading to equilibrium outcomes that can be analytically derived and numerically solved. Compared to a benchmark without model uncertainty, robust insurance pricing results in significantly higher premiums and equity valuations. Notably, our model yields three novel insights: (1) The minimum, maximum, and admissible range of aggregate capacity all expand, indicating that insurers' liquidity management becomes more conservative. (2) The expected length of the underwriting cycle increases substantially, far exceeding the range commonly reported in earlier empirical studies. (3) While the capacity process remains ergodic in the long run, the stationary density becomes more concentrated in low-capacity states, implying that liquidity-constrained insurers require longer to recover. Together, these findings provide a potential explanation for recent skepticism regarding the empirical evidence of underwriting cycles, suggesting that such cycles may indeed exist but are considerably longer than previously assumed.

Aurel Mihail Titu, Alina Bianca Pop, Camelia Oprean-Stan et al.

This paper addresses the issue of intellectual property management in the knowledge-based economy. The starting point in carrying out the study is the presentation of some concepts regarding in the first phase, the intellectual capital. Arguments are made that the knowledge-based economy is a challenge for the current century. The subject of intellectual property is approached through the prism of a topical concept operationalized in the current global economic context. The main institutions that are directly related to this concept are mentioned. The topic of patents related to WOS indexed scientific papers is also debated, along with a series of statistics and studies on the state of patent protection worldwide in the top fields. The last part of the paper contains the conclusions and own points of view on the debated topic.

G. Santos, J. C. Sá, M. J. Félix et al.

Digitalization is rushing throughout the world, namely, in industrial and societal infrastructures. Hence, digital transformation becomes a pillar of industrial policy, known in Europe as “Industry 4.0,” in China as “made in China 2025,” in Asia as “Smart Cities,” in Japan as “Society 5.0,” and in North America as “Industrial Internet.” These transformations will change the industrial landscape, toward Quality 4.0 and therefore, our lives. The presented research was conducted on quality management employees in Portugal and it aims to analyze if such employees have the perception of the impact of Industry 4.0 in the quality management profession and the required and needed skills. After analyzing the answered questionnaires, 90 results were considered valid. This is the sample of our study. Simultaneously, the goal of this research is also to review and analyze the main topics in progress related to quality management for the fourth industrial revolution and how quality emerges of this change. The professionals that work on quality management must have creative thinking, be leaders, know how to communicate and work as a team, as well as, to have knowledge and understanding of ICT (Information and Communications Technology), and main pillars of Industry 4.0. These are the main findings. Besides that, they must know how to motivate their work teams, be open to change, know how to use Big Data to make decisions and above all, they must know how to manage conflicts. In addition, quality professionals must promote the design and production of first class products, be the defenders of their customers within the organization, and finally, they must create value for the stakeholders.

Sijia Liu, Xuedong Wang, G. Guo et al.

The harm from mercury pollution to human health and the environment has long been known. In recent years, the combination of industrial activities and long-term atmospheric transport has resulted in a sustained increase in mercury concentrations in soils. However, soil remediation and mercury-contaminated soil management in China are still in its infancy, and there is ample space for the development of related research. We systematically reviewed several pertinent topics and found that soil mercury pollution around mines and industrial soil in China is the most serious. The highest mercury content is found in the soil around the Tongren mercury mine in Guizhou Province and the thermometer factories. The average content of soil mercury is similar to that of atmospheric mercury emission in China. Mercury content in soil gradually decreases from the southeast to the northwest. In order to repair the mercury-contaminated soil, solidification and stabilization technology have been developed in China and applied in the engineering of restoration. In the future, we will study more effective stabilizer materials and select plants highly rich in mercury, to develop low-cost and high-repair-rate remediation technology. China has also developed a series of policies, regulations, and regulatory documents to manage mercury pollution, such as the Agricultural Land Standard and the Construction Land Standard. Compared with other countries, the screening values for soil mercury in China are relatively low. China has also established control standards for methylmercury in soils of residential and industrial land. In addition, China has issued emission standards and control notices related to the mercury industry. However, there are still shortcomings in soil remediation technology and environmental management systems for mercury pollution in China. In the future, China will formulate standards according to local conditions and improve the responsibility mechanism, financial mechanism, and level of public participation.

Bassirou Diène, J. Rodrigues, O. Diallo et al.

Abstract Internet of Things (IoT) is a network paradigm in which physical, digital, and virtual objects are equipped with identification, detection, networking, and processing functions to communicate with each other and with other devices and services on the Internet in order to perform the users’ required tasks. Many IoT applications are provided to bring comfort and facilitate the human life. In addition, the application of IoT technologies in the automotive industry has given rise to the concept of Industrial Internet of Things (IIoT) which facilitated using of Cyber Physic Systems, in which machines and humans interact. Due to the diversity, heterogeneity, and large volume of data generated by these entities, the use of traditional database management systems is not suitable in general. In the design of IoT data management systems, many distinctive principles should be considered. These different principles allowed the proposal of several approaches for IoT data management. Some middleware or architecture-oriented solutions facilitate the integration of generated data. Other available solutions provide efficient storage and indexing structured and unstructured data as well as the support to the NoSQL language. Thus, this paper identifies the most relevant concepts of data management in IoT, surveys the current solutions proposed for IoT data management, discusses the most promising solutions, and identifies relevant open research issues on the topic providing guidelines for further contributions.

Theofanis P. Raptis, A. Passarella, M. Conti

Information and communication technologies are permeating all aspects of industrial and manufacturing systems, expediting the generation of large volumes of industrial data. This paper surveys the recent literature on data management as it applies to networked industrial environments and identifies several open research challenges for the future. As a first step, we extract important data properties (volume, variety, traffic, and criticality) and identify the corresponding data enabling technologies of diverse fundamental industrial use cases, based on practical applications. Second, we provide a detailed outline of recent industrial architectural designs with respect to their data management philosophy (data presence, data coordination, and data computation) and the extent of their distributiveness. Then, we conduct a holistic survey of the recent literature from which we derive a taxonomy of the latest advances in industrial data enabling technologies and data centric services, spanning all the way from the field level deep in the physical deployments, up to the cloud and applications level. Finally, motivated by the rich conclusions of this critical analysis, we identify interesting open challenges for future research. The concepts presented in this paper thematically cover the largest part of the industrial automation pyramid layers. Our approach is multidisciplinary, as the selected publications were drawn from two fields; the communications, networking and computation field, and the industrial, manufacturing, and automation field. This paper can help the readers to deeply understand how data management is currently applied in networked industrial environments, and select interesting open research opportunities to pursue.

Gang Qiao, Xizhu Qiang, Lei Wan et al.

In this paper, in order to reduce the energy leakage caused by the discretized representation in sparse channel estimation for Orthogonal Frequency Division Multiplexing (OFDM) systems, we systematically have analyzed the optimal locations of atoms with discrete delays for each path reconstruction from the perspective of linear fitting theory. Then, we have investigated the adverse effects of the non-ideal inner product function on the iteration in one of the most widely used channel estimation method, Orthogonal Matching Pursuit (OMP). The study shows that the distance between the selected atoms for each path in OMP can be larger than the sampling interval, which prevents OMP-based methods from achieving better performance. To overcome this drawback, the image deblurring-based channel estimation method, in which the channel estimation problem is analogized to one-dimensional image deblurring, was proposed to improve the large compensation distance of traditional OMP. The advantage of the proposed method was validated by the results of numerical simulation and sea trial data decoding.

Ashish Anil Pawar, Vishnureddy Prashant Muskawar, Ritesh Tiku

Algorithmic trading or Financial robots have been conquering the stock markets with their ability to fathom complex statistical trading strategies. But with the recent development of deep learning technologies, these strategies are becoming impotent. The DQN and A2C models have previously outperformed eminent humans in game-playing and robotics. In our work, we propose a reinforced portfolio manager offering assistance in the allocation of weights to assets. The environment proffers the manager the freedom to go long and even short on the assets. The weight allocation advisements are restricted to the choice of portfolio assets and tested empirically to knock benchmark indices. The manager performs financial transactions in a postulated liquid market without any transaction charges. This work provides the conclusion that the proposed portfolio manager with actions centered on weight allocations can surpass the risk-adjusted returns of conventional portfolio managers.

Weizhen Bian, Siyan Liu, Yubo Zhou et al.

Faced with the burgeoning volume of academic literature, researchers often need help with uncertain article quality and mismatches in term searches using traditional academic engines. We introduce IntellectSeeker, an innovative and personalized intelligent academic literature management platform to address these challenges. This platform integrates a Large Language Model (LLM)--based semantic enhancement bot with a sophisticated probability model to personalize and streamline literature searches. We adopted the GPT-3.5-turbo model to transform everyday language into professional academic terms across various scenarios using multiple rounds of few-shot learning. This adaptation mainly benefits academic newcomers, effectively bridging the gap between general inquiries and academic terminology. The probabilistic model intelligently filters academic articles to align closely with the specific interests of users, which are derived from explicit needs and behavioral patterns. Moreover, IntellectSeeker incorporates an advanced recommendation system and text compression tools. These features enable intelligent article recommendations based on user interactions and present search results through concise one-line summaries and innovative word cloud visualizations, significantly enhancing research efficiency and user experience. IntellectSeeker offers academic researchers a highly customizable literature management solution with exceptional search precision and matching capabilities. The code can be found here: https://github.com/LuckyBian/ISY5001