Mihai Andronie, George Lăzăroiu, Mariana Iatagan
et al.
With growing evidence of deep learning-assisted smart process planning, there is an essential demand for comprehending whether cyber-physical production systems (CPPSs) are adequate in managing complexity and flexibility, configuring the smart factory. In this research, prior findings were cumulated indicating that the interoperability between Internet of Things-based real-time production logistics and cyber-physical process monitoring systems can decide upon the progression of operations advancing a system to the intended state in CPPSs. We carried out a quantitative literature review of ProQuest, Scopus, and the Web of Science throughout March and August 2021, with search terms including “cyber-physical production systems”, “cyber-physical manufacturing systems”, “smart process manufacturing”, “smart industrial manufacturing processes”, “networked manufacturing systems”, “industrial cyber-physical systems,” “smart industrial production processes”, and “sustainable Internet of Things-based manufacturing systems”. As we analyzed research published between 2017 and 2021, only 489 papers met the eligibility criteria. By removing controversial or unclear findings (scanty/unimportant data), results unsupported by replication, undetailed content, or papers having quite similar titles, we decided on 164, chiefly empirical, sources. Subsequent analyses should develop on real-time sensor networks, so as to configure the importance of artificial intelligence-driven big data analytics by use of cyber-physical production networks.
Maryna V. Kovbatiuk, Ivanna I. Strilok, Viktoriya V. Shklyar
et al.
Modern realities indicate that improving the efficiency of management processes is impossible
without the use of information and software that should be integrated into the management system.
Therefore, the article explores the importance of this integration in the context of globalized markets,
emphasizing its role in increasing competitiveness, introducing innovations and making operational
and strategic decisions. It is noted that the main advantages of integration are: increased management
efficiency through automation of routine tasks, increased control over own operations; improved
coordination between departments through the use of a single database, simplification of information exchange and promotion of more effective cooperation; informed decision-making through access
to real-time data; reduction of costs for personnel, paper and other resources; gaining competitive
advantages in such areas as marketing, sales, production and logistics.
It is emphasized that the information support of international enterprises has moved to a new
level, where information has not only become an information resource, but also performs important
functions in management. By using advanced analytics and business intelligence tools, international
companies can gain strategic insights for further development, identify market trends, and make
informed operational decisions that meet their current and global goals.
The existing unified software of the leading ERP-systems vendors that can be used in the
management of an enterprise, in particular, an international company, is analyzed. Given that the
changing conditions of enterprise functioning require an individual approach and the creation of a
custom-made product, a comparative characterization of unified and individual software products is
carried out. An example of individual software products that take into account the specifics of certain
enterprises is the software developed with the participation of the authors for enterprises in the water
transport and insurance industries.
With a view to optimizing the process of using information and software in the management of an
international enterprise, the authors propose an appropriate mechanism. For its successful implementation,
it is necessary to take into account that the integration of information technology is a complex process
that requires careful planning and implementation, in particular, the factor of financing and staff training.
As modern international businesses continue to evolve and adapt to change, the use of information
and software is becoming a critical success factor. High-tech management solutions allow companies
to respond effectively to global market challenges and remain competitive in an ever-changing business
environment.
Background: Today, the digital transformation of business is one of the conditions for survival on the market. The development of digital technology is progressing rapidly, and only the business entities that keep pace with this development can expect good business results. Social entrepreneurship is an excellent way to solve the problems of social inequality and poverty and thus leads to economic growth and development. Purpose: The main goal of this research is to create a theoretical model of digital transformation of social entrepreneurship. This model can be a useful tool for deciding on the digital transformation of business. We investigated motivation of managers and employees as an influencing factor for the digital transformation of business. We declared other influencing factors as constants. Study design: We measured motivation by personal and professional use of the Internet, the acquisition of digital skills, the cost of labour of those who are involved in the digitisation process, and the application of data protection software. Ninety-seven social entrepreneurship entities from Bosnia and Herzegovina (B&H) participated in the research. The research was carried out using questionnaires, and we analysed the obtained data using correlation and regression methods. Findings: The results showed that motivation is a significant factor in the digital transformation of social entrepreneurship. Based on the results of the research, we have created a model of digital transformation of social entrepreneurship entities that can lead to economic and social development through steps applicable in practice. Limitations/future research: The most significant limitation of the research is the lack of an official register of social entrepreneurship entities from which we can collect data about the number of these entities. To future researchers, we leave open questions of other influencing factors for the development of social entrepreneurship, such as knowledge, sources of funding for initial business activities, etc.
Production management. Operations management, Personnel management. Employment management
Rodrigo Silva Sotolani, Isabella de Araújo Cionini Menezes, Napoleão Verardi Galegale
et al.
O progresso da Indústria 4.0 tem relevância cada vez maior, considerando o aumento das vulnerabilidades de segurança da informação e da complexidade em priorizá-las na tomada de decisões. Observou-se uma lacuna de pesquisa neste tema. O objetivo deste artigo é identificar critérios na literatura científica que possam ser utilizados em um método de análise multicritério, visando a priorização de tratamento de vulnerabilidades de segurança na Indústria 4.0. Um método como o Analytic Hierarchy Process (AHP) é uma proposta de solução. A metodologia utilizada foi a revisão exploratória da literatura encontrada nas bases SCOPUS e Web of Science. O resultado identificou oito critérios e 34 subcritérios relacionados ao tratamento das vulnerabilidades de segurança na Indústria 4.0. A contribuição teórica vai ao encontro do preenchimento da lacuna em relação a este tema. A contribuição prática permite que organizações da Industria 4.0 apliquem os critérios identificados na análise multicritério para o tratamento das suas vulnerabilidades de segurança e assim alcancem melhores decisões para a entrega de produtos e serviços contribuindo para sociedade. Pesquisas futuras podem ser conduzidas por meio de entrevistas ou questionários para validação com profissionais da área dos critérios encontrados, como também a aplicação prática do método AHP.
Production management. Operations management, Production capacity. Manufacturing capacity
Haar Cascade is a cost-effective and user-friendly machine learning-based algorithm for detecting objects in images and videos. Unlike Deep Learning algorithms, which typically require significant resources and expensive computing costs, it uses simple image processing techniques like edge detection and Haar features that are easy to comprehend and implement. By combining Haar Cascade with OpenCV2 on an embedded computer like the NVIDIA Jetson Nano, this system can accurately detect and match faces in a database for attendance tracking. This system aims to achieve several specific objectives that set it apart from existing solutions. It leverages Haar Cascade, enriched with carefully selected Haar features, such as Haar-like wavelets, and employs advanced edge detection techniques. These techniques enable precise face detection and matching in both images and videos, contributing to high accuracy and robust performance. By doing so, it minimizes manual intervention and reduces errors, thereby strengthening accountability. Additionally, the integration of OpenCV2 and the NVIDIA Jetson Nano optimizes processing efficiency, making it suitable for resource-constrained environments. This system caters to a diverse range of educational institutions, including schools, colleges, vocational training centers, and various workplace settings such as small businesses, offices, and factories. ... The system's affordability and efficiency democratize attendance management technology, making it accessible to a broader audience. Consequently, it has the potential to transform attendance tracking and management practices, ultimately leading to heightened productivity and accountability. In conclusion, this system represents a groundbreaking approach to attendance tracking and management...
Aleksandar Ivezić, Branislav Trudić, Zoran Stamenković
et al.
Modern agriculture necessitates the use of techniques and tools that pollute the environment less and improve the safety of food and feed production. In the field of plant protection, drones are attracting increasing attention due to their versatility and applicability in a variety of environmental and working conditions. Drone crop spraying techniques offer several advantages, including increased safety and cost effectiveness through autonomous and programmed operations based on specific schedules and routes. One of the main advantages of using drones for plant protection is their ability to monitor large areas of crops in a short amount of time. In addition to crop protection management, using drones for augmentative biocontrol facilitates the distribution of beneficial organisms to the exact locations where they are required, which can increase the effectiveness of biocontrol agents while reducing distribution costs. In this context, given the very limited commercial use of drones in the Western Balkans’ agri-food sector, the use of drones in the agri-food industry is a topic that needs to be elaborated on and highly promoted. Additionally, the specific legal regulations in Serbia that currently limit the use of drones in agriculture must be outlined. Conventional crop production is still significantly more prevalent in Serbia, but given the region’s continuous technological progress, there is no doubt that farmers’ education and future investments in precision agriculture will most likely increase the use of state-of-the-art technologies and drones in agriculture.
We review papers published in POM during its thirty‐year history that deal with retail operations issues with an empirical approach. The papers span a range of issues, from traditional ones like forecasting and inventory planning, to new technologies, like radio frequency identification (RFID) and e‐commerce, and strategic, like links between retailing and stock market performance.
Hanieh Shambayati, Mohsen Shafiei nikabadi, Seyed Mohammad Ali Khatami Firouzabadi
et al.
Purpose: Today, the manufacturing industry, with the expansion of the physical constraints of trade worldwide, has adopted modern information technologies to optimize the business process and achieve integration with geographically dispersed supply chain partners. Traditional supply chain models focus on optimizing physical flows. However, it is equally important to ensure that physical units can process appropriate information. This paper aims to propose a model for the optimization of information process performance in the IoT-based virtual supply chain. Design/methodology/approach: In this study, information processing performance in the closed-loop virtual supply chain has been optimized to maximize profit and information processing speed by considering costs of virtual, information security, and energy consumption. The final programming model has been optimized using meta-heuristic algorithms, the Non-Dominated Sorting Genetic Algorithm II (NSGA-II), and the Strength Pareto Evolutionary Algorithm (SPEA-II).Findings – The results indicated that there is an inverse relationship between virtual supply chain profit and information processing speed (delay). The results of model solving using NSGA-II and SPEA-II algorithms underlined the virtual supply chain profit of 9.93×106 and 4.23×106, and the data processing speed of 337.48 and 94.07, respectively. Thus, the NSGA-II algorithm contributes more to the supply chain profitability.Research limitations/implications - The proposed model can be used in manufacturing industries equipped with IoT. Unavailability of practical examples and insufficient data are the two main limitations of the study. Practical implications:- The proposed model improves the production process and helps managers to plan better for their supply chain management and make timely decisions by sharing information across the supply chain and being aware of the flows of products and associated parts.Social implications - The Internet of Things in the virtual supply chain provides an opportunity to manage logistics systems and results in efficient online delivery with minimal cost. The information flow integrates all links and participants in the virtual supply chain. It enables each member to obtain the accurate information needed for logistics capability, reduces resource wastage, and improves customer satisfaction. Originality/value: One of the innovative aspects of this research is the use of IoT in the virtual supply chain for the integration and transparency of information in the supply chain, considering the importance of information in the virtual supply chain and examining the impact of IoT usage on closed-loop virtual supply costs and target functions. In addition to considering the physical flow costs of the closed-loop, including production costs, separation costs, repair, disposal, recycling, etc., in the cost objective function, virtual flow costs included IoT usage costs and information security costs. Energy consumption was also included in the objective function. Also, due to the virtualization of the supply chain and the significant role of information, optimization of information processing speed was considered in modeling the supply chain performance, which is another innovative aspect of research.
Management. Industrial management, Production management. Operations management
Deepika Saxena, Ishu Gupta, Ashutosh Kumar Singh
et al.
Cloud computing has become inevitable for every digital service which has exponentially increased its usage. However, a tremendous surge in cloud resource demand stave off service availability resulting into outages, performance degradation, load imbalance, and excessive power-consumption. The existing approaches mainly attempt to address the problem by using multi-cloud and running multiple replicas of a virtual machine (VM) which accounts for high operational-cost. This paper proposes a Fault Tolerant Elastic Resource Management (FT-ERM) framework that addresses aforementioned problem from a different perspective by inducing high-availability in servers and VMs. Specifically, (1) an online failure predictor is developed to anticipate failure-prone VMs based on predicted resource contention; (2) the operational status of server is monitored with the help of power analyser, resource estimator and thermal analyser to identify any failure due to overloading and overheating of servers proactively; and (3) failure-prone VMs are assigned to proposed fault-tolerance unit composed of decision matrix and safe box to trigger VM migration and handle any outage beforehand while maintaining desired level of availability for cloud users. The proposed framework is evaluated and compared against state-of-the-arts by executing experiments using two real-world datasets. FT-ERM improved the availability of the services up to 34.47% and scales down VM-migration and power-consumption up to 88.6% and 62.4%, respectively over without FT-ERM approach.
This paper proposes optimal lockdown management policies based on short-term prediction of active COVID-19 confirmed cases to ensure the availability of critical medical resources. The optimal time to start the lockdown from the current time is obtained after maximizing a cost function considering economic value subject to constraints of availability of medical resources, and maximum allowable value of daily growth rate and Test Positive Ratio. The estimated value of required medical resources is calculated as a function of total active cases. The predicted value of active cases is calculated using an adaptive short-term prediction model. The proposed approach can be easily implementable by a local authority. An optimal lockdown case study for Delhi during the second wave in the month of April 2021 is presented using the proposed formulation.
Deoclécio Junior Cardoso da Silva, Denise Adriana Johann, Andrieli de Fátima Paz Nunes
et al.
Diante aos aspectos inerentes que permeiam a temática da sustentabilidade, bem como a importância desta na sociedade, torna-se relevante que estudos sejam realizados com a finalidade de auxiliar as organizações a estarem alinhadas a esse viés. Dessa forma objetivo do presente estudo é avaliar as alternativas de melhoria na qualidade no processo com ênfase nas práticas sustentáveis em um restaurante situado na região noroeste do Rio Grande do Sul. Através de uma pesquisa exploratória, descritiva, de abordagem qualitativa e quantitativa, este estudo de caso avaliou um restaurante, elencando alternativas de melhoria da qualidade, alinhadas a práticas sustentáveis, priorizando através do método de Análise hierárquica de processos (AHP) aquela que na visão do gestor é mais relevante. Dessa forma, os resultados demonstraram que alternativa voltada a treinamento do pessoal é a mais priorizada, visto sua influência direta nos processos, o que pode auxiliar na redução dos desperdícios no restaurante.
Production management. Operations management, Production capacity. Manufacturing capacity
This work proposes a novel portfolio management technique, the Meta Portfolio Method (MPM), inspired by the successes of meta approaches in the field of bioinformatics and elsewhere. The MPM uses XGBoost to learn how to switch between two risk-based portfolio allocation strategies, the Hierarchical Risk Parity (HRP) and more classical Naïve Risk Parity (NRP). It is demonstrated that the MPM is able to successfully take advantage of the best characteristics of each strategy (the NRP's fast growth during market uptrends, and the HRP's protection against drawdowns during market turmoil). As a result, the MPM is shown to possess an excellent out-of-sample risk-reward profile, as measured by the Sharpe ratio, and in addition offers a high degree of interpretability of its asset allocation decisions.