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2022 ◽  
Vol 12 (2) ◽  
pp. 667
Author(s):  
Mehrzad Lavassani ◽  
Johan Åkerberg ◽  
Mats Björkman

The industrial network infrastructures are transforming to a horizontal architecture to enable data availability for advanced applications and enhance flexibility for integrating new technologies. The uninterrupted operation of the legacy systems needs to be ensured by safeguarding their requirements in network configuration and resource management. Network traffic modeling is essential in understanding the ongoing communication for resource estimation and configuration management. The presented work proposes a two-step approach for modeling aggregated traffic classes of brownfield installation. It first detects the repeated work-cycles and then aims to identify the operational states to profile their characteristics. The performance and influence of the approach are evaluated and validated in two experimental setups with data collected from an industrial plant in operation. The comparative results show that the proposed method successfully captures the temporal and spatial dynamics of the network traffic for characterization of various communication states in the operational work-cycles.


2022 ◽  
Vol 131 ◽  
pp. 03005
Author(s):  
Aurelija Stelmokiene ◽  
Giedre Geneviciute-Janone ◽  
Loreta Gustainiene ◽  
Kristina Kovalcikiene

Burnout can negatively affect both workers’ health and safety in an organization [1]. The current study was oriented to identify the main risk and protective factors, which might predict professional burnout among workers in an industrial plant in Lithuania using the Job demands-resources model [2, 3]. 249 industrial and 74 administrative workers from one organization filled out a self-administered questionnaire. Scales from COPSOQ II (Copenhagen Psychosocial Questionnaire) were used in a cross-sectional survey. With reference to the research results, there were no significant differences in professional burnout between industrial and administrative workers. However, scores of work pace, safety climate, possibilities for development, influence at work, recognition and organizational justice were higher in a group of administrative employees as compared to their colleagues from the industrial departments. Moreover, different factors were found to predict employees’ physical, emotional and mental exhaustion: emotional demands predicted burnout in administrative workers’ group, while quantitative demands, work-family conflict, possibilities for development- among industrial workers. Organizational justice was the only protective factor to predict lower burnout in both groups of employees.


2021 ◽  
Vol 6 (7) ◽  
pp. 160-163
Author(s):  
Haruna A. Ogweda ◽  
Joseph E. Okhaifoh

This paper presents the design and implementation of a remotely mounted Anti-surge Control Valve (ASCV) for a mixed refrigerant gas compressor deployed in an industrial plant. The traditional ASCV model which is usually self-mounted is plagued by component failures due to stress fatigue from excessive vibrations leading to unreliability of the system. A new system with a remote-mount actuation control system was developed, tested, installed and commissioned in place of the initial self-mount system. Test results showed that average percentage of trips caused by failure of the ASCV dropped from 70% with the initial set-up to 0% with the modified set-up. Hence, a lasting solution to the issue of component fatigue failure from vibrations has been resolved using the highly reliable developed remote-mount actuation control.


2021 ◽  
Vol 31 (2) ◽  
pp. 25-35
Author(s):  
Guilherme Balduino Lopes ◽  
Renato Ferreira Fernandes Junior.

The concept of the new industry seeks not only to improve production processes, but also to bring solutions to environmental problems, in addition to reducing resource consumption, while maintaining high yields. This constant search for process optimization has been the main agent in the development of new technologies aimed at improving the performance of industrial production lines. Thus, this article proposes to raise some important concepts of Industry 4.0, and present the development of a remote IoT-based system that, through MQTT and Modbus protocols, will be responsible for monitoring the entire electrical network of an industrial plant, sending its data to the cloud, where it can be monitored and analyzed by the industry management sector or even by an artificial intelligence system, in a simple and effective way, in real time and from anywhere, in order to assist in decision-making focused on energy efficiency.


Energies ◽  
2021 ◽  
Vol 14 (24) ◽  
pp. 8456
Author(s):  
Icaro Figueiredo Vilasboas ◽  
Victor Gabriel Sousa Fagundes dos Santos ◽  
Armando Sá Ribeiro Júnior ◽  
Julio Augusto Mendes da Silva

Global optimization of industrial plant configurations using organic Rankine cycles (ORC) to recover heat is becoming attractive nowadays. This kind of optimization requires structural and parametric decisions to be made; the number of variables is usually high, and some of them generate disruptive responses. Surrogate models can be developed to replace the main components of the complex models reducing the computational requirements. This paper aims to create, evaluate, and compare surrogates built to replace a complex thermodynamic-economic code used to indicate the specific cost (US$/kWe) and efficiency of optimized ORCs. The ORCs are optimized under different heat sources conditions in respect to their operational state, configuration, working fluid and thermal fluid, aiming at a minimal specific cost. The costs of 1449.05, 1045.24, and 638.80 US$/kWe and energy efficiencies of 11.1%, 10.9%, and 10.4% were found for 100, 1000, and 50,000 kWt of heat transfer rate at average temperature of 345 °C. The R-square varied from 0.96 to 0.99 while the number of results with error lower than 5% varied from 88% to 75% depending on the surrogate model (random forest or polynomial regression) and output (specific cost or efficiency). The computational time was reduced in more than 99.9% for all surrogates indicated.


2021 ◽  
Author(s):  
Salem All Dhanhani ◽  
Ivan Novendri

Abstract The control room acts as a central nervous system facility. This is where important decisions, using complex systems, are made every day. The actions of control room operators have a direct impact on uptime, production yields, quality, and industrial plant safety. In addition, long working hours per shift result in fatigue, irregularity of circadian rhythms and sleep cycles, and decreased cognitive performance at the end of day and night shifts. Fatigue causes decreased alertness, attention span, poor memory, and concentration and affect other mental factors. ADNOC Gas Processing established Fatigue Risk Management Taskforce (FRMT) to adapt practices to the specific conditions and create a safer working environment, leading to happier and healthier employees and an overall community. In industries that run continuous and heavy-duty plants such as Oil, gas, and petrochemical, shift work ensures production flow. After the outbreak of Covid-19, business needs to adapt quickly so that their activities can run. The finding suggests that the workers' cognitive performance is reduced, shown by the increase of triggered alarm by the average of 14.39% higher than before the outbreak of Covid-19. However, with the ability to adapt and implement control and monitoring measures, the number of alarm rate gradually decreased. The study framework was proven to be a valuable tool that decision-makers can use, especially to measure the performance of control room workers and their psychological fatigue affected by the Covid-19 pandemic.


2021 ◽  
Vol 2 (2) ◽  
pp. 87-96
Author(s):  
Marulam MT Simarmata

Londut protected forest contains mixed forest vegetation in the form of natural forest vegetation and there is forest vegetation of former industrial plant forest management, as well as natural tusam vegetation (Pinusmerkusii), also has the privilege of existing conditions that still have natural biodiversity in the form of natural tropical forest vegetation. The research aims to find out the variation and dominance of the type of forest vegetation contained in the area, so that initial information will be obtained in the framework of planning and management of the area. The implementation of research is carried out by the determination of plot methods, and the creation of inventory plots, the creation of inventory plots according to growth rate, inventory path, measurement of vegetation dimensions, and identification. The inventory plot method is carried out with a net system (nested sampling) with an inventory path length of 500 m with a repeat of 5 lanes whose placement is evenly spread over the Londut forest area to get representation. The results showed 31 types of vegetation growing in the region. Based on the diversity of types included in the moderate category as well as the value of the level of the type in the low class. The dominance of vegetation types at the level of seedlings, stake, and poles is occupied by hosting vegetation types (Quercus sp) with magnitudes of 25.90%, 33.94%, and 37.61% respectively. For the level of trees dominated by the type of Tusam (Pinusmerkussii) 57.71%.


2021 ◽  
Vol 11 (12) ◽  
pp. 3090-3095
Author(s):  
Ramesh Chandran ◽  
N. Gayathri ◽  
S. Rakeshkumar

The medical data integrating system allows the hospital’s resource constraints to be more effectively utilized. Moreover, by improving the resource management and allocation method, the hospital’s operations may be more organized, and the effectiveness of healthcare can be improved without breaking the medical agreements. Significant catastrophes frequently result in a scarcity of important medical resources, hence resource allocation must be optimized to enhance the performance of relief operations. The two main requirements for healthcare industrial applications are timeliness and reliability. Therefore, in the architecture of a smart healthcare industry these two criteria should be thought carefully. A well-known approach for the security and timeliness in the intelligent healthcare industry is to utilize hybrid IoT and Cloud technologies. Yet it is not enough to protect their hard deadlines for tight time-sensitive applications utilizing cloud. A potential way to cope with efficiency and latency criteria for strict time-sensitive applications is the deployment of intermediate processing layer IoT that can be linked between healthcare industrial plant and cloud. The purpose of this article is to develop a healthcare Industrial IoT system that include a medical resource allocation scheme for dividing a certain amount of workload between those multiple computing layers which are dependable and time consuming. IOT is integration of microprocessors and controller Workload partitioning can give us important design decisions to specify how many computing resources are needed in cooperation with IoT to develop a local private cloud. Ant lion optimization (ALO) and TABU Look for the right route. The simplest method of deciding the distance to a destination is to choose an OLSR routing protocol depending on the meaning or measure it requires. The method proposed in the distribution and data storage of medical resources is very efficient.


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