production management
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Abstract By enabling the merging of the virtual and real worlds, DT (Digital Twin) technology has considerably aided the development of businesses at both levels of digitization and networking in recent years. As an outcome, industrial research has shifted its attention to this new technology in the manufacturing business. However, there are still technical issues with DT technology, such as real-time data interaction, high integration of constituent elements, and high simulation. This paper proposes to solve these issues by presenting a framework that blends DT with 3D visualization technologies. A case study of an intelligent logistics management 3D scheduling system for a factory in Shandong verifies the applicability of digital twins to flexible production management. The example demonstrates that the framework can be synchronizing the virtual and real systems. Moreover, the framework can effectively cover the whole manufacturing life cycle, enhance production efficiency and product quality, and achieve flexible production management, helping the manufacturing industry's digital and intelligent transition.

Green citrus detection in citrus orchards provides reliable support for production management chains, such as fruit thinning, sunburn prevention and yield estimation. In this paper, we proposed a lightweight object detection YOLOv5-CS (Citrus Sort) model to realize object detection and the accurate counting of green citrus in the natural environment. First, we employ image rotation codes to improve the generalization ability of the model. Second, in the backbone, a convolutional layer is replaced by a convolutional block attention module, and a detection layer is embedded to improve the detection accuracy of the little citrus. Third, both the loss function CIoU (Complete Intersection over Union) and cosine annealing algorithm are used to get the better training effect of the model. Finally, our model is migrated and deployed to the AI (Artificial Intelligence) edge system. Furthermore, we apply the scene segmentation method using the “virtual region” to achieve accurate counting of the green citrus, thereby forming an embedded system of green citrus counting by edge computing. The results show that the [email protected] of the YOLOv5-CS model for green citrus was 98.23%, and the recall is 97.66%. The inference speed of YOLOv5-CS detecting a picture on the server is 0.017 s, and the inference speed on Nvidia Jetson Xavier NX is 0.037 s. The detection and counting frame rate of the AI edge system-side counting system is 28 FPS, which meets the counting requirements of green citrus.

The processing of food products during the pandemic is growing rapidly, resulting in processed products that are increasingly diverse and widespread in the market. To empower rural communities by improving knowledge, attitudes, skills, and behaviors, activities and mentoring programs are needed in accordance with the needs of the community.  This community service activity was held in the Group of Women's Farmers “Dharma Santi”, Baru Village,  Marga Sub district, Tabanan Regency, Bali Province. Taro is an untapped commodity in  Baru  Village. Processing taro into various products such as bread, jam, and noodles have been produced and marketed by Women Farmers Group,  but marketing is still limited around the village.  Farmers Group does not have adequate entrepreneurship skill, production management, and marketing. The solution to address partner problems is to provide the right technology for processing bread, jam, and taro noodles, equipment assistance, knowledge of packaging and product labeling, marketing, and entrepreneurship. The implementation of community service activities has been running smoothly. The number of participants who participated in the activity was 10 people. Based on the results of the evaluation, this group mastered the technology of making bread, jam, and taro noodles up to 75%. Further help is needed to the group so that more quality bread products,  jams, and taro noodles produced have a longer shelf life as well as wider marketing.

CO2-based fracturing is widely introduced to stimulate shale oil reservoirs for its multiple advantages. However, the range of CO2 entering the matrix around fractures and CO2-oil replacement capacity between matrix and fractures cannot be fully explained. To address this issue, a radial constant volume diffusion experiment on shale cores was designed in this study, and the pressure drop curve history was matched through numerical model to determine the composition effective diffusion coefficient. A field-scale numerical model was established, in which a series of certain grids were used to explicitly characterize fracture and quantify the prosess of CO2 mass transfer and oil replacement. Based on the field-scale numerical model, the process of shut-in, flow back, and oil production was simulated. The distribution of CO2 in fractured shale oil formation and its impact on crude oil during shut-in stage and flow back stage were investigated. This study concludes that CO2 gradually exchanges the oil in matrix into fractures and improve the fluidity of oil in matrix until the component concentrations of the whole reservoir reaches equilibrium during the shut-in process. Finally, about 30∼35 mole % of CO2 in fractures exchanges for oil in matrix. The range of CO2 entering the matrix around fractures is only 1.5 m, and oil in matrix beyond this distance will not be affected by CO2. During the process of flow back and production, the CO2 in fracture flows back quickly, but the CO2 in matrix is keeping dissolved in oil and will not be quickly produced. It is conclued that the longest possible shut-in time is conducive to making full use of the CO2-EOR mechanism in fractured shale oil reservoirs. However, due to the pursuit of economic value, a shut-in time of 10 days is the more suitable choice. This work can provide a better understanding of CO2 mass transfer mechanism in fractured shale oil reservoirs. It also provides a reference for the evaluation of the shut-in time and production management after CO2 fracturing.

Abstract Fungi are important in several aspects of human life. In particular, to agriculture, pathogenic fungi are of great importance, as they are responsible for production losses of the most diverse types. Because of this, knowledge about pathogenic fungus is of extreme importance for farmers and professionals working in agricultural areas. Among farmers who use specific agroecological practices, this knowledge is even more valuable, since by not adopting conventional methods of production, they resort to non-invasive alternatives that are less or not harmful at all to the environment in consideration of production management methods. This study aimed to assess farmer perception in the Cerrado biome in the city of Goiás (GO), Brazil, in order to understand their ethnomycological perceptions to verify historical management practices, their knowledge about phytopathogenic fungi, and how these producers perceive fungi. We used the theoretical reference method “From peasant to peasant” formulated by ANPA - National Association of Small Farmers. Some aspects of farmers’ ethnomycological knowledge are discussed. These ease identification the representatives of the Fungi Kingdom is associated with organisms that present easily recognizable characteristics, such as wood-ears or disease-causing fungi. In general, farmers are able to identify representatives of the Fungi Kingdom that are found in their daily lives. The perception of farmers about fungi, a group still much unknown by society, is very relevant for future actions of ethnomycology.

The article substantiates the directions of increasing production and exports in the East Zangezur region on the basis of a green economy model, shows the ways of introducing new resources into the economy, examines ways to provide various sectors of the domestic market with food and other goods. The purpose of the article is to characterize the use of production and export resources of the region. The subject of the research is the process of managing the production and export resources of the region. Research hypothesis. Agriculture plays a leading role in the employment of the population of this region. In accordance with this tradition, agriculture is being created in the regions on the basis of a modern material and technical base and new production management technologies based on the new structure of the green economy model. Presentation of the main material. Effective use of the country's export potential plays an important role in strengthening Azerbaijan's integration into the world economy. From this point of view, the effective use of the economic potential of the territories opens up new horizons in increasing the production and export potential of the republic and creating an alternative export sector. Originality and practical significance of the research. On the basis of the proposed model, special attention is paid to the production of environmentally friendly products in developing regions. This approach is due to the fact that Azerbaijan ranks 10th in the world for the production of environmentally friendly products. Conclusions of the study. The rich natural resources of the Republic of Azerbaijan in some areas should be re-evaluated, and the results of the assessment should be promoted in international advertising channels, posting them on the website of the World Tourism Organization. It is advisable to assess, first of all, the mineral and natural landscape resources of the republic.