Plant Personnel Research Articles

Avances recientes en el estudio de factores de estrés prefaenado sobre la calidad de la carne bovina, aviar y porcina

Stress in the pre-slaughter stage is a critical period in the production chain because it causes losses in animal live weight, affects carcass yield and quality, and leads to a loss of animal welfare due to an alteration in the homeostasis of the organism as a result of exposure to stressful situations. This review identifies and describes the stressors that have been reported in the last 5 years as the main causes of meat quality deterioration, including animal handling activities by farm or plant personnel (transport, loading and unloading, in the slaughter plant), environmental conditions (temperature, vibrations), waiting time prior to slaughter and mixing of lots, water and food fasting period, and fatigue states, as well as the biomarkers routinely used for the study of conditions associated with stress. Although research on the subject is abundant, the biochemical mechanisms involved in obtaining certain organoleptic characteristics of meat with respect to stress levels and the individual variations observable in different groups of animals are still not completely clear, and more research is needed on stress biomarkers that allow a more specific, effective and non-invasive identification and measurement.

Coping with chaos at Fukushima Daiichi: Bricolage in and through a space

When the Fukushima Daiichi nuclear plant was hit with unexpected force by an earthquake and a tsunami, its safety protocol did not include instructions for what to do in case of a complete loss of power. Plant personnel were forced to practice bricolage, making do with what they had, to come up with their own solutions. Existing literature on bricolage activities has until now largely focused on organizational perspective. This article uses the case of the catastrophe at Fukushima to shed light on the role played by managers and workers when doing bricolage according to their hierarchical position as it is distributed within a space.This article claims that bricolage is made possible in and through space through movement, distance and boundaries; by creating rules for choosing not to escape, expanding the bricolage repertoire's within a space, defining objectives which are simultaneously clear and gaseous, pushing back the boundaries of a repertoire to increase the possible surface area available for bricolage, and using hierarchical power to expand resources.Finally, our article suggests that paying closer attention to the mechanisms actors use to appropriate and create spaces might provide a new framework for analyzing crises and their management, as well as helping to identify ways to promote bricolage practices in crisis situations.

Economics of Dairy Products in a Experimental Dairy Plant

In order to ensure sustainable and economic dairy-based value-added production, it is essential to analyze the costs and Break-Even points. The study was undertaken in the Experimental Dairy Plant, National Dairy Research Institute, Karnal (Haryana) with handling capacity of ten thousand liter per day, to optimize the cost of Dairy products manufactured in the dairy plant. Burfi and Ice-cream are among the most crucial Indian dairy products processed in a dairy plant and widely consumed. Primary and Secondary data were both used to conduct this study. Primary data is supplemented by actual observation and interviewing plant personnel, and Secondary data, i.e., milk inflow, its utilization pattern, and product output, was taken from different plant ledgers. Economic analysis of this dairy product in a dairy plant is necessary to optimize the cost of each component used in manufacturing Burfi and ice cream. The dairy product will keep its presence in the competitive market, and as a result, the consumer will benefit from this optimum price. Therefore, calculated the product cost was in a dairy plant, and the fixed and variable cost was 24.56 and 75.44 percent for Burfi and 34.01 and 65.99 percent for ice cream, respectively. This study shows that the dairy plant has surplus production of 3721.69 kg and 1,02,082.33 cups of 100 ml of output Burfi and Ice-cream respectively, after the break-even point. The study has suggested that the quantity of Burfi and Icecream should be manufactured above recommended Break-Even Point to avoid losses. As a seasonal product, if there is a fluctuation in market demand, products could be shifted to other profitable products.

Control of Acoustic Energy Input for Cleaning of Industrial Boilers

A non-intrusive cleaning method for boiler tubes at Sasol Synfuels power station at Secunda, in the Mpumalanga province of South Africa, is preferred over conventional methods that require boiler shutdown. The elected non-intrusive cleaning method utilizes sound energy waves, produced by an acoustic horn. Due to the nature of sound propagation and the effectiveness required, there is a requisite to control and operate the sonic horn. If the acoustic horn’s sound frequency is too low, it will produce higher sound energy waves that will resonate with the plant’s harmonious frequency and cause structural damage. Conversely, if the sonic horn’s sound frequency is too high, excessive noise levels may be reached and annoy plant personnel. To prevent these undesirable outcomes posed by adopting acoustic cleaning, there needs to be a regulatory system incorporated into the configuration to mitigate vibrations and limit noise. The regulatory system comprises a control system that drives the acoustic horn’s sound frequency as intended through a set point. The designed control system meets the anticipated requirements, such that it has an ideal transient response of 0.562 s, a steady-state error achieved in 1.05 s, with 0.201% overshoot, and most importantly the closed-loop system is stable.

Simulation-Based VR Training for the Nuclear Sector—A Pilot Study

Simulation-based training has seen an increased use of extended reality, that is, augmented reality (AR), virtual reality (VR) and mixed reality (MR) displays. The health professions have been using VR for simulation-based training more extensively than others. This method can offer the possibility of immediate feedback, which promotes more accurate training to self-correct mistakes in environments that are otherwise risky or provide unsafe conditions. The nuclear industry has attempted to seize the same digital and educational transformation to train their personnel to handle dangerous scenarios. We ran a pilot study with the aim of evaluating the VR training scenario developed for the specific target group and the acceptance of the VR technology itself for this kind of training. We used the Kirkpatrick framework to evaluate the training and the VR-HAM acceptance model to evaluate the acceptance of VR. A VR scenario was developed to test specific technical skills of nuclear power plant personnel. The 13 participants showed results within the basic level of the Kirkpatrick framework and held both positive reactions and concerns, that is, they enjoyed the training with VR and expressed concerns regarding the stability of the VR technology. The participants also showed positive attitudes towards the perceived ease of use and usefulness of the VR-HAM and its various constructs. Even though the COVID-19 pandemic limited our testing, we could show valuable data and positive attitudes and perceived ease by the participants. Simulation-based VR training could be an important complement to traditional training methods, especially where safety is a priority, but we still need to provide solid evidence.

Verification of human error traps in NPP procedures utilizing syntactic and semantic information extraction

ABSTRACT Procedures must be provided in an easy-to-follow manner to ensure human performance quality especially in complex process industries. Principles and practices to enhance human performance of plant personnel are described in a procedure writing manual. However, a coherent review of a large volume of procedures concerning various human performance issues is a challenging task. This paper introduces a novel application of natural language processing for the verification of human error traps in procedures in two stages. First, all the significant syntactic and semantic information are extracted from the input procedure documents, and then the stepwise drilled-down verification results for each human error trap are provided. Case study results of the proposed approach to selected procedures obtained from a U.S. commercial nuclear power plant are introduced showing the various summary analysis data produced by the software tool implemented. Although the number of analyzed procedures was limited, it is shown that the proposed approach could make the process of verifying human-factored procedures systematic and coherent. Increasingly advanced management of procedures could be implemented by integrating more intelligent features into the proposed approach.

Process intensification and digital twin – the potential for the energy transition in process industries

Abstract The work defines and discusses process intensification (PI) and digital twin (DT) as potential tools to accelerate the energy transition through their applications in the process industries. The PI technologies take advantage of innovative principles in equipment design and control to improve the physical process, while the DT offers the virtual model of the plant as an environment for production optimization. The effects of both tools on the energy transition are evaluated not only from the point of applications but also from the possibility of implementation and barriers in process industries. Although they are beneficial, the deployment of PI and DT requires not only infrastructure and capital investment but the knowledge and cooperation of different levels of plant personnel. Besides review of individual implementation, this work explores the concept of combining PI and DT which can make them the enabler of each other and bring a breakthrough in optimization of process design and control.

Wastewater treatment plant operators report high capacity to support wastewater surveillance for COVID-19 across New York State, USA.

Wastewater surveillance for infectious disease expanded greatly during the COVID-19 pandemic. As a collaboration between sanitation engineers and scientists, the most cost-effective deployment of wastewater surveillance routinely tests wastewater samples from wastewater treatment plants. To evaluate the capacity of treatment plants of different sizes and characteristics to participate in surveillance efforts, we developed and distributed a survey to New York State municipal treatment plant supervisors in the summer and fall of 2021. The goal of the survey was to assess the knowledge, capacity, and attitudes toward wastewater surveillance as a public health tool. Our objectives were to: (1) determine what treatment plant operators know about wastewater surveillance for public health; (2) assess how plant operators feel about the affordability and benefits of wastewater surveillance; and (3) determine how frequently plant personnel can take and ship samples using existing resources. Results show that 62% of respondents report capacity to take grab samples twice weekly. Knowledge about wastewater surveillance was mixed with most supervisors knowing that COVID-19 can be tracked via wastewater but having less knowledge about surveillance for other public health issues such as opioids. We found that attitudes toward wastewater testing for public health were directly associated with differences in self-reported capacity of the plant to take samples. Further, findings suggest a diverse capacity for sampling across sewer systems with larger treatment plants reporting greater capacity for more frequent sampling. Findings provide guidance for outreach activities as well as important insight into treatment plant sampling capacity as it is connected to internal factors such as size and resource availability. These may help public health departments understand the limitations and ability of wastewater surveillance for public health benefit.

Study on the training, retraining and further training of industrial plant personnel

Study on the training, retraining and further training of industrial plant personnel

Framatome ANP GmbH Concept of Plant Life Management (PLIM)

Abstract The deregulation of the power generation industry has resulted in increased competitive pressure and is forcing operators to improve plant operating economy while maintaining high levels of plant safety. A key factor to meeting this challenge is to apply a comprehensive plant life management (PLIM) approach which addresses all relevant ageing and degradation mechanisms regarding the safety concept, plant component structures and documentation, plant personnel, consumables, operations management system and administrative controls. For this reason, Framatome ANP GmbH has developed an integrated PLIM concept applicable for both new and operating plants and focusing on the safety concept, plant component structures and documentation.

Intelligent Integrated Model for Improving Performance in Power Plants

Industry 4.0 is expected to play a crucial role in improving energy management and personnel performance in power plants. Poor performance problem in maintaining power plants is the result of both human errors, human factors and the poor implementation of automation in energy management. This problem can potentially be solved using artificial intelligence (AI) and an integrated management system (IMS). This article investigates the current challenges to improving personnel and energy management performance in power plants, identifies the critical success factors (CSFs) for an integrated intelligent framework, and develops an intelligent framework that enables power plants to improve performance. The theoretical basis is founded on a systematic literature review to locate 110 out of 3108 papers studied carefully to examine the performance architecture that best enables effective maintenance. The findings from this literature review are combined with expert judgment and the big data advantages of AI applications to develop an intelligent model. Data are collected from a power plant in Iraq. To ensure the reliability of the proposed model, various hypotheses are tested using structural equation modeling. The results confirm that the measurement model is acceptable, and that the hypotheses are supported and significant. A case study demonstrates the strong relationship and significance between big data of performance and the CSFs. It is hoped that this model will be adopted to enable performance improvement in power plants.

Süt İşletmeleri Çalışanlarının El ve Gaita Örneklerinde Astrovirüs, Norovirüs ve Rotavirüs Antijenlerinin Belirlenmesi

In this study, swab and stool samples were obtained from employees (n=47) working in five dairy processing plants located in Burdur province (Turkey) and the district of Bucak to determine the prevalence of norovirus (NoV), rotavirus (RoV) and astrovirus (AsV) antigens by the enzyme-linked immunosorbent assay (ELISA) technique. Swab samples were obtained from both hands (palm, upper part, sides of fingers and fingernail tips) of employees. In a questionnaire, participants were asked to provide information regarding their gender, age, education level, smoking status, hygiene education status, habits of glove use during working as well as whether they had had digestive problems such as diarrhea, vomiting and abdominal pain in the period of study. Results of the stool analyses indicated that NoV antigen was present in an employee of a dairy processing plant, which was not participated in any hygiene education. AsV and RoV antigens were absent in swap and stool samples of employees. According to results of the questionnaire, 42 of the 47 employees frequently used gloves while 4 employees used gloves rarely. It was determined that 7 of 47 staff was not in participated any hygiene education, and one of those 7 staff did not use gloves during working. It can be concluded that hygiene in the working environment and personnel in these dairy processing plants were sufficient and appropriate from viral perspective. However, detection of NoV antigen in stool sample of a staff of a dairy processing plant shows that there is high viral contamination potential for employees of dairy processing plants. Thus, hygiene education in food processing plants including dairy plants to prevent possible viral infections and outbreaks and prevent to loss of workforce is extremely important.

СРАВНИТЕЛЬНЫЙ АНАЛИЗ СТРУКТУРЫ ПАРНЫХ КОРРЕЛЯЦИЙ МЕЖДУ ПСИХОЛОГИЧЕСКИМИ ПОКАЗАТЕЛЯМИ В РАЗНОВЕЛИКИХ ВЫБОРКАХ

Purpose: To propose a procedure for comparative analysis of correlation relationships structure between psychological scales in samples of different sizes.
 Material and methods: A procedure of comparative analysis of correlation relationships structure between psychological indicators in groups of different sizes based on the «zet» method of R. Fisher is proposed. To illustrate the method, data from psychodiagnostic surveys of the nuclear power plant (NPP) personnel who worked in normal conditions and the personnel of the Chernobyl NPP at four different stages of aftermath activities in 1986–1987 were used. All the subjects performed the Minnesota Multiphasic Personality Inventory (MMPI); the results of each of the groups were subjected to a correlation analysis using the Pearson method. The analysis took into account average (0.5 ≤ r < 0.7) and strong (r ≥ 0.7) correlations.
 Results: Using the example of a number of psychodiagnostic examinations of the Chernobyl NPP personnel at various stages of aftermath activities, it is shown that the structure of correlation relationships between the MMPI scales can reflect the peculiarities of mental adaptation of professional teams working in regular and extreme conditions.
 It was shown that in the aftermath process by March–April 1987, the number of medium and strong pairwise Pearson correlations between the clinical MMPI scales increased. This fact apparently indicates that during this period, the NPP personnel were characterized by the simultaneous activation of various mechanisms of intrapsychic adaptation. The core of the correlation pleiad consisted of scales 1, 2, 7, and 8. Such a multidirectional reaction to the aftermath stressors was accompanied by a statistically significant increase in almost all clinical scales (except scale 6) of the average MMPI profile in comparison with the control group. The absence of stable correlations of clinical scales with the F scale indicates that the marked increase in the MMPI profile was not associated with a tendency to aggravation.
 By the period of November–December 1987, the hypochondria scale occupied a leading place in the correlation pleiad of the MMPI indicators of the Chernobyl NPP personnel, the number of its significant connections with other clinical scales (2, 3, 7 and 8) reached four. Apparently, the mechanism of anxiety somatization at that time could be considered as a syndrome-forming factor and taken into account when planning rehabilitation and health measures.
 Conclusion: The use of the proposed method of the strength standardization of pairwise correlation relationships between the MMPI scales allowed us to legitimately compare these indicators in groups that differ significantly in number. The chosen representation form of correlations facilitates the analysis of their structure.

Bayesian network-based root cause analysis and fault pathway identification in complex industrial processes

Real-time root cause identification (RCI) of faults or abnormal events in industries gives plant personnel the opportunity to address the faults before they progress and lead to failure. RCI in industrial systems must deal with their complex behavior, variable interactions, corrective actions of control systems and variability in faulty behavior. Bayesian networks (BNs) is a data-driven graph-based method that utilizes multivariate sensor data generated during industrial operations for RCI. Bayesian networks, however, require data discretization if data contains both discrete and continuous variables. Traditional discretization techniques such as equal width (EW) or equal frequency (EF) discretization result in loss of dynamic information and often lead to erroneous RCI. To deal with this limitation, we propose the use of a dynamic discretization technique called Bayesian Blocks (BB) which adapts the bin sizes based on the properties of data itself. In this work, we compare the effectiveness of three discretization techniques, namely EW, EF and BB coupled with Bayesian Networks on generation of fault propagation (causal) maps and root cause identification in complex industrial systems. We demonstrate the performance of the three methods on the industrial benchmark Tennessee-Eastman (TE) process. For two complex faults in the TE process, the BB with BN method successfully diagnosed correct root causes of the faults, and reduced redundancy (up to 50%) and improved the propagation paths in causal maps compared to other two techniques.

Assessment of Environmental and Occupational Risk Factors for the Mitigation and Containment of a COVID-19 Outbreak in a Meat Processing Plant.

Throughout the COVID-19 pandemic, meat processing plants have been vulnerable to outbreaks of SARS-CoV-2 infection. Transmission of the virus is difficult to control in these settings because of a combination of factors including environmental conditions and the specific nature of the work. This paper describes a retrospective outbreak investigation in a meat processing plant, a description of the measures taken to prevent or contain further outbreaks, and insights on how those with specific knowledge of the working environment of these plants can collaborate with public health authorities to ensure optimal outbreak control. The plant experienced 111 confirmed positive asymptomatic cases in total with an estimated attack rate of 38% during a five-week period. 4 weeks after the first case, mass screening of all workers was conducted by the public health authorities. Thirty-two workers tested positive, of which 16 (50%) worked in one particular area of the plant, the boning hall (n = 60). The research team prepared and carried out semi-structured interviews with the plant personnel who were charged with COVID control within the plant. They carried out assessments of operational risk factors and also undertook air quality monitoring in the boning hall and abattoir. The air quality measurements in the boning hall showed a gradual build-up of carbon dioxide and aerosol particles over the course of a work shift, confirming that this poorly ventilated area of the plant had an environment that was highly favorable for aerosol transmission of SARS-CoV-2. Assessment of operational conditions incorporated visual surveys of the plant during the working day. Prior to and during the first 2 weeks of the outbreak, multiple measures were introduced into the plant by management, including physical distancing, provision of educational material to workers, visitor restrictions, and environmental monitoring. After the implementation of these measures and their progressive refinement by plant management, the factory had no further linked cases (clusters) or outbreaks for the following 198 days. The tailored approach to risk mitigation adopted in this meat processing plant shows that generic risk mitigation measures, as recommended by public health authorities, can be successfully adapted and optimized by designated plant emergency response teams.

Variability in Ferroalloy Furnace Tapping – Insights from Modelling

During tapping of pyrometallurgical smelters, molten products from the furnace operation are periodically removed from the vessel. Variations in the quantities of alloy and slag obtained from each tap are undesirable and can cause disruption to upstream and downstream operations, resulting in economic losses and safety risks to plant personnel. In the present work an integrated reduced-order model of a ferroalloy furnace tapping system was used to assess the sensitivity of the process to various operating parameters, and describe the statistical impact of random changes in the system over a large number of tapping cycles. The effect of implementing simple control measures to determine the best point to stop a tap is also presented.

Second wave of COVID-19 pandemic and the surge of mucormycosis: Lessons learnt and future preparedness: Indian Society of Anaesthesiologists (ISA National) Advisory and Position Statement.

Second wave of COVID-19 pandemic and the surge of mucormycosis: Lessons learnt and future preparedness: Indian Society of Anaesthesiologists (ISA National) Advisory and Position Statement.

INTELLIGENT PRODUCTION PLANNING AND OPTIMISATION TOOL FOR GAS PROCESSING COMPLEX

Structured production planning is very important to achieve good financial performance in the oil and gas industry. This is especially crucial in an integrated oil and gas supply chain which encompasses feed gas supply, gas processing plants, and petrochemical plants. In the current offshore production climate, the nature of feed gas qualities has evolved. Gas from offshore fields has progressed from having minimal to much higher CO2 content, exceeding the CO2 limits of existing gas processing plants. It is generally impossible to curtail productions from high CO2 gas fields, leading to a loss of revenue. Optimised blending of the feed gas sources is therefore vital to adjust to this changing environment. An intelligent production planning tool was designed to meet the multiple objectives of a gas plant and optimise production. The sales gas demand must first be met based on available feed gas supply and individual plant availability and reliability. Economic factors such as maximising profit from by-products were also factored in by ranking the loading of each processing plant and prioritising plants with higher recovery. Planning strategies were also tailored to each plant’s unique operational limits and turndowns, modes, and challenges. Combining these complex objectives and constraints into a powerful optimisation tool allows a new level of connected intelligence in the production planning of the gas processing complex. The innovative optimisation tool was officially released in 2019 and is currently utilised by production planners in different modes: long-term (5-year duration), medium-term (90 days), and daily operational planning. The planning tool was also designed to be digital-ready and equipped with much improved automation and robustness to embrace the digital transformation agenda. These optimised workflows would improve efficiency and ultimately result in better production planning and decision-making by plant personnel.
 Keywords: Production planning

Application of Cable Condition Monitoring Technologies to Assess Age-Related Degradation of Industrial Cables Installed in Harsh Environments

The aging of electrical cables has been the subject of substantial research and development (R&D) projects performed by national and international laboratories, universities, and private organizations for many years. This R&D was conducted to develop guidance, equipment, and techniques to support aging management of in-service cables in industrial facilities such as nuclear power plants, research reactors, waste facilities, and fuel fabrication plants. Through these research efforts, condition monitoring technologies have been developed that can determine the severity of age-related degradation that occurs in industrial cables and insulation polymers during service. This paper summarizes the results of aging assessments that were performed for cables installed in two U.S. nuclear power plants, one a pressurized water reactor and one a boiling water reactor. These cables had been in service for over 40 years and during plant operation were exposed to harsh environmental conditions including elevated temperatures and radiation. For these assessments, a comprehensive series of measurements was performed to assess the aged condition of the cables. These cables came from different manufacturers, were manufactured in different years, and were constructed with a variety of jacket and insulation polymers including chloro-sulfonated polyethylene (CSPE), cross-linked polyethylene (XLPE)/cross-linked polyolefin (XLPO), neoprene, and ethylene propylene rubber (EPR). The goal of these assessments was to determine the current aged condition of the cable polymers and provide an estimate of how long the cable insulation materials could remain exposed to their in-service environmental conditions before reaching their end-of-life condition. Both nuclear power plants have received license renewals to extend their operation from 40 to 60 years, and the utilities need objective evidence to show that critical components such as cables will be able to function safely and reliably during the extended operating period. The results of these assessments showed that the cables exhibited different aged conditions depending on the type of polymers they were constructed with and the environment they were exposed to during service. Some of the cables and insulation polymers showed signs of significant age-related degradation and were estimated to have approximately 5 years of remaining service life. Other cables exhibited no signs of significant age-related degradation and were estimated to have 50 years or more of remaining service life. Using the results of these cable aging assessments, plant personnel were able to (1) determine the overall aged condition of cables and insulation polymers using objective test results, (2) identify aged or degraded cables before they caused operability issues, and (3) avoid unnecessary and costly replacement of cables that can continue to operate safely and reliably.

Prevalence of SARS-CoV-2 Contamination on Food Plant Surfaces as Determined by Environmental Monitoring

The SARS-CoV-2 pandemic has presented new challenges to food manufacturers. During the early phase of the pandemic, several large outbreaks of coronavirus disease 2019 (COVID-19) occurred in food manufacturing plants resulting in deaths and economic loss, with approximately 15% of personnel diagnosed as asymptomatic for COVID-19. Spread by asymptomatic and presymptomatic individuals has been implicated in large outbreaks of COVID-19. In March 2020, we assisted in implementation of environmental monitoring programs for SARS-CoV-2 in zones 3 and 4 of 116 food production facilities. All participating facilities had already implemented measures to prevent symptomatic personnel from coming to work. During the study period, from 17 March to 3 September 2020, 1.23% of the 22,643 environmental samples tested positive for SARS-CoV-2, suggesting that infected individuals were actively shedding virus. Virus contamination was commonly found on frequently touched surfaces such as doorknobs, handles, table surfaces, and sanitizer dispensers. Most processing plants managed to control their environmental contamination when they became aware of the positive findings. Comparisons of positive test results for plant personnel and environmental surfaces in one plant revealed a close correlation. Our work illustrates that environmental monitoring for SARS-CoV-2 can be used as a surrogate for identifying the presence of asymptomatic and presymptomatic personnel in workplaces and may aid in controlling infection spread.