Hasil untuk "Management. Industrial management"

H. Jouhara, N. Khordehgah, Sulaiman Almahmoud et al.

Horizon 2020 Project “Design for Resource and Energy efficiency in CerAMic Kilns- DREAM Project (Grant No: 723641), Horizon 2020 Industrial THERMal energy recovery conversion and management (Grant No:680599) and ESPRC (Grant No: EP/P004636/1)

L. Suganthi, A. A. Samuel

A. Nardone, B. Ronchi, N. Lacetera et al.

A. Monthly, Sr. No, S. Basha et al.

Mehrdokht Pournader, Yangyan Shi, S. Seuring et al.

This paper presents current academic and industrial frontiers on blockchain application in supply chain, logistics and transport management. We conduct a systematic review of the literature and find four main clusters in the co-citation analysis, namely Technology, Trust, Trade, and Traceability/Transparency. For each cluster, and based on the pool of articles included in it, we apply an inductive method of reasoning and discuss the emerging themes and applications of blockchains for supply chains, logistics and transport. We conclude by discussing the main themes for future research on blockchain technology and its application in industry and services.

D. Gupta, B. Denton

Ke Feng, J. Ji, Yongchao Zhang et al.

Gearbox has a compact structure, a stable transmission capability, and a high transmission efficiency. Thus, it is widely applied as a power transmission system in various applications, such as wind turbines, industrial machinery, aircraft, space vehicles, and land vehicles. The gearbox usually operates in harsh and non-stationary working environments, expediting the degradation process of the gear surface. The degradation process may lead to severe gear failures, such as tooth breakage and root crack, which could damage the gear transmission system. Therefore, it is essential to assess the progression of gear surface degradation in order to ensure a reliable operation. The digital twin is an emerging technology for machine health management. A high-fidelity digital twin model can help reflect the operation status of the gearbox and reveal the corresponding degradation mechanism, which could benefit the remaining useful life (RUL) prediction and the predictive maintenance-based decision-making framework. This paper develops a digital twin-driven intelligent health management method to monitor and assess the gear surface degradation progression. The developed method can effectively reveal the gear wear propagation characteristics and predict the RUL accurately. Furthermore, the knowledge learned from digital twin models can be well transferred to the

D. Miracle

M. Guerin, M. Huntley, M. Olaizola

Hajar Fatorachian, Hadi Kazemi

Abstract Considering the crucial role Information Technology (IT) plays in achieving performance improvements in business processes, this paper aims to explore the potential impact of the fourth industrial revolution – Industry 4.0 and its associated technological advances on Supply Chain (SC) performance. This study is exploratory research, conducted based on inductive reasoning, which aims to bring new insights into the topic, and to provide forward-thinking for future research. Hence, through conducting a systematic literature review, the paper attempts to explore the impact of Industry 4.0 on SC performance and to conceptualise and develop findings into an operational framework underpinned by Systems Theory. Based on this research, the application of Industry 4.0-enabling-technologies is expected to bring about significant performance improvements in SCM by enabling a holistic approach towards supply chain management resulting from extensive supply chain integration as well as information sharing and transparency throughout the supply chain. Moreover, these technologies allow for huge performance improvements within individual supply chain processes such as procurement, production, inventory management and retailing through enabling process integration, digitisation and automation, and bringing about novel analytical capabilities.

H. Stadtler, Christoph Kilger

P. Boxall, J. Purcell, P. Wright

O. V. Shcherbakova

The subject. Economic, technological and geopolitical changes are leading to the digitalization of virtually all structures of the labor market: from the process of production and human resources management to the organization of the workplace. The use of new digital technologies makes it possible to give up routine human labor, contribute to improving the quality of working life of employees and employers, and increase industrial production, which means economic growth of the state. Thus, in accordance with the National Security Strategy, approved by the Decree of the President of the Russian Federation dated July 2, 2021 No. 400, the situation in the production industry is one of the key criteria of Russia's competitiveness and contributes to the strengthening of the state's defense capability. Ensuring Russia's independence  and competitiveness was also announced to be the main goal of the Strategy for Scientific and Technological Development of the Russian Federation, approved by Presidential Decree No. 642 dated December 1, 2016. On the other hand, the use of new technologies may have time-delayed risks. The most important risk today is the increasing release of labor force and mass cuts of jobs requiring average qualifications, as well as dismissal of employees due to failure to pass tests because of the lack of skills in digital tools.The purpose of the study was to substantiate the urgent character of the implementation of digital profile programs as a part of the employer's personnel policy to achieve the objectives set in the National Security Strategy of the Russian Federation dated 2021.The methodology of comprehensive research, including methods of document analysis, comparative analysis, secondary use of sociological and economic data were used.Main results. The study shows that the use of the employee digital profile programs will allow the employer to identify weaknesses in any of the employee’s skills well in advance, and to pave individual learning pathway, based on his/her preferences, hobbies  and intentions, in order to upgrade the skills. It is deemed that the competence of employees is a factor for transfer of any business to digitalization. This policy of the employer will allow to cover for low-quality job cut and give personnel the minimum knowledge that makes it possible to acquire information on modern information technologies, be able to use it to solve the set problems and have necessary skills and technology, which will facilitate solution of the problems. Ultimately, these are tools to achieve the tasks set by the state in the framework of the state's defensive capability and competitiveness. At the same time, the lack of normative methodologies for the creation and operation of employee digital profiles and comprehensive scientific research predetermine increasing risks of violation of personal data of employees, privacy of employees, as well as discrimination in making legally significant decisions. Today there are no normative standards of data processing and system interaction, which leads to the diminution of guarantees of employees' rights in terms of respect for personal data and other data in terms of classified information.

Florina DEIAC, Felix Horațiu ARION

The cluster of excellence in the agri-food sector could function as a significant driver for promoting innovation and advanced technologies throughout all aspects of the supply chain. This collaboration can facilitate the exchange of knowledge and experiences, promoting innovation and the development of efficient solutions. Innovative clusters have an impact on regional growth because they enable new technology applications, cost savings, and research. Romania's North West area is well-known for having the highest number of gold-certified clusters in a variety of disciplines, including the lone gold-certified cluster in the agro-industrial sector. For the gold clusters in the North West region, the study finds less meaningful indicators for the agro-industrial sector using the ESCA standard technique for management excellence indicator evaluation.

Patrick Prieur, Aline Belloni

With the evolution of process approaches within organizations, the increasing importance of quality management systems (like ISO 9001) and the recent introduction of ISO 30401 for knowledge management, we examine how these different elements converge within the framework of an Integrated Management System. The article specifically demonstrates how an ISO30401-compliant knowledge management system can be implemented by deploying the mechanisms of the SECI model through the steps of the PDCA cycle as applied in the processes of the integrated management system.

J. Morillo, J. Usero, D. Rosado et al.

Jasman Pardede, Desita Nurrohmah

Background: Hepatitis is a contagious inflammatory disease of the liver and is a public health problem because it is easily transmitted. The main factors causing hepatitis are viral infections, disease complications, alcohol, autoimmune diseases, and drug effects. Some hepatitis variants such as B, C, and D can also cause liver cancer if left untreated. Objective: This research aims to determine the effect of Backward Elimination feature selection on the performance of hepatitis disease identification compared to cases where Backward Elimination is not applied. Methods: XGBoost classification, capable of handling machine learning problems, was utilized. Additionally, Backward Elimination was used as a featured selection to increase accuracy by reducing the number of less important features in the data classification process. Results: The results for training XGBoost model with Backward Elimination, and applying Random Search for hyperparameter optimization, achieved an accuracy of 98.958% at 0.64 seconds. This performance was better than using Bayesian search, which produced the same accuracy of 98.958% but required a longer training time of 0.70 seconds. Conclusion: The use of features obtained from Backward Elimination process as well as the use of feature average values for missing value treatment, produced an accuracy of 98.958%.the precision in training XGBoost model with hyperparameter Bayesian search achieved accuracy, recall, and F1 score of 98.934%, 98.934%, and 98.934%, respectively. Consequently, the use of Backward Elimination in XGBoost model led to faster training, improved accuracy, and decreased overfitting.   Keywords: Hepatitis, Backward Elimination, XGBoost, Bayesian Search, Random Search

Awang Herjunie Nurdy, Abdul Rahim, Arbansyah

Perkembangan teknologi yang pesat mempermudah akses ke berbagai hiburan digital, termasuk game online seperti Stumble Guys, yang telah diunduh lebih dari 163 juta kali dan mendapatkan ulasan beragam di Google Play Store. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna Stumble Guys menggunakan algoritma Naïve Bayes. Metode penelitian melibatkan tahapan Knowledge Discovery in Databases (KDD), meliputi pemilihan data, preprocessing, transformasi dengan CountVectorizer dan TF-IDF, serta pengklasifikasian dengan Naïve Bayes. Dengan menggunakan 1.500 ulasan dari Google Play Store, model Naïve Bayes mencapai akurasi 86%, dengan precision, recall, dan f1 score masing-masing sebesar 86%. Hasil penelitian menunjukkan bahwa Naïve Bayes efektif dalam mengklasifikasikan sentimen ulasan game Stumble Guys.

Ravi Kashyap

We develop several innovations to bring the best practices of traditional investment funds to the blockchain landscape. Specifically, we illustrate how: 1) fund prices can be updated regularly like mutual funds; 2) performance fees can be charged like hedge funds; 3) mutually hedged blockchain investment funds can operate with investor protection schemes, such as high water marks; and 4) measures to offset trading related slippage costs when redemptions happen. Using our concepts - and blockchain technology - traditional funds can calculate performance fees in a simplified manner and alleviate several operational issues. Blockchain can solve many problems for traditional finance, while tried and tested wealth management techniques can benefit decentralization, speeding its adoption. We provide detailed steps - including mathematical formulations and instructive pointers - to implement these ideas and discuss how our designs overcome several blockchain bottlenecks, making smart contracts smarter. We provide numerical illustrations of several scenarios related to our mechanisms.

Wanchao Liu, Xiangqing Chen, Wang-xing Li et al.