Methodological foundations for substantiating safe levels of exposure to artificial nanomaterials (for example, carbon nanotubes) (literature review)

Introduction. The unique physicochemical properties of carbon nanotubes allow them to be used in many fields. The global nanomaterials market is growing every year. An important step in introducing products to the domestic and world markets is to determine the safe exposure levels of CNTs. Establishing a corporate standard can serve as a preliminary stage before the approval of a state hygiene standard. Material and methods. The material for the analysis was the sources of information on the available standards for the content of CNTs in the air of the working area using information from regulatory agencies, research centers, CNT manufacturers, bibliographic and abstract databases Web of Science, Scopus, PubMed, RSCI. Results. A scheme for justifying safe levels of exposure to CNTs (corporate standard) has been developed, consisting of several stages: characterization of CNTs in the air at workplaces, selection of experimental doses of CNTs, preparation of CNT dispersions, and conducting toxicological and hygienic experiments. Justification of the corporate standard is carried out in in vitro and in vivo experiments. The planning of experiments should be carried out taking into account the target organ under the influence of CNT - the respiratory system. The recommended dose / concentration range for experiments should include doses / concentrations derived from calculated and literature data. A necessary step is to obtain homogeneous dispersions in which CNTs become bioavailable for biological systems. In vitro and in vivo experiments determine the level of exposure at which no harmful effect is observed and / or the lowest level of exposure at which there is a harmful effect on the cell culture / respiratory tract of animals. After the stage of substantiating the corporate standard, the enterprise should take measures for several years to adjust the corporate standard based on data from clinical and hygienic studies, during which the working conditions and health status of workers are monitored, and extended toxicological and hygienic studies. Conclusion. The presence of a corporate standard will allow the manufacturer of CNTs to carry out activities for the development and implementation of a production control program with the introduction of monitoring the air condition in the working area. The development of a corporate regulation can be seen as a preparatory stage before the establishment of a government regulation.

Hygienic analysis of violations of sanitary and epidemiological requirements for working conditions in the field of "Mining" before and after the introduction of a risk-oriented model of control and supervisory activities (on the example of the Perm Region)

In the Russian Federation, "Mining" is a priority activity in the group "Activities in the field of industry and agriculture" for the potential risk of harm to health. The study aims to perform a hygienic analysis of violations of sanitary and epidemiological requirements for working conditions in the field of "Mining" (on the example of the Perm Region) before and after the introduction of a risk-oriented model of control and supervisory activities to manage risks to the health of the working population. Scientists performed a study according to the data of 49 inspection acts by the Rospotrebnadzor Department in the Perm Region to facilities operating in the field of "Mining," before and after the introduction of a risk-based approach (for the periods 2013-2016 and 2017-2019), using standard analysis methods. Implemented in practice in 2016, the risk-oriented approach to the control and supervision of working conditions provides for the attribution of the activities of a legal entity, an individual entrepreneur, and (or) production facilities used by them in the implementation of this activity to a particular risk category under MP 5.1.0116-17. The study used data from the Federal Register of economic entities (legal entities/sole proprietors) subject to sanitary and epidemiological supervision as of 2020; data from Rosstat and Permstat on the number of employees engaged in work with harmful and(or) dangerous working conditions, data from Rospotrebnadzor and the Department of Rospotrebnadzor in the Perm Region on occupational morbidity for 2019. The average number of violations of sanitary and epidemiological requirements to working conditions per year per economic entity in the field of Mining in the Perm Region since 2017 (since the introduction of the risk-based model of sanitary and epidemiological surveillance) has significantly decreased (p<0.05) from 62 violations (in 2013-2016) to 31 (in 2017-2019), mainly due to a significant 2.5-fold decrease in the number of breaches of the requirements of Federal Law No. 52-FZ per entity - from 30 violations to 12. In 2017-2019, the average number of violations of the requirements for working conditions per year per subject significantly decreased compared to 2013-2016 (p<0.05) due to a reduction in violations of the requirements for the maintenance of industrial and household premises (by 11.9 times). In the period 2017-2019, regarding 2013-2016, the contribution of violations under requirements for the maintenance of industrial and household premises, ventilation decreased by an average of 5.37 and 6.07 times, respectively, increased to overalls and PPE, production control by 3.16 and 1.67 times. The results obtained indicate that introducing a risk-based approach has led to a decrease in the number of violations of sanitary and epidemiological requirements for working conditions in the field of Mining in the Perm Region since 2017. As well as an increase in the overall structure of violations of the proportion of violations of requirements, non-compliance with which can lead to severe consequences for human health (increased the proportion of violations of requirements for overalls, PPE, working conditions with a PC, production control).

Evaluation of Pull Production Control Mechanisms by Simulation

Today, companies need to continuously improve their production processes, which is a complex task. Lean manufacturing is one of the methodologies for production improvement, and one of the basic goals of any lean implementation is to reduce work-in-process (WIP) and shorten the production lead time. One of the basic lean principles for achieving these goals is pull principle. The adoption of this principle is quite challenging, as it requires a long-term commitment in the application and adoption of various lean techniques and tools that are prerequisites for the successful introduction of the pull principle. Kanban is the most well-known pull production control mechanism, and the first one developed within Toyota production system, but later, other pull control mechanisms were developed. Some of them include Conwip, Hybrid Kanban/Conwip, and Drum Buffer Rope (DBR), and those three, together with Kanban, were the research topic of this study. These four mechanisms were not explored and compared all together not for these specific production configurations considered in this research but also with regard to optimal parameters of control mechanisms. The goal was to analyze and compare how these pull control mechanisms affect lead time in different production conditions. For this purpose, simulation experiments were performed. The results showed that for different production conditions, different pull control mechanisms are optimal in terms of shortening lead time. This finding could help companies as a guideline for making a decision in terms of which pull control mechanism to choose.

A comparative study of different pull control strategies in multi-product manufacturing systems using discrete event simulation

Pull production control strategies coordinate manufacturing operations based on actual demand. Up to now, relevant publications mostly examine manufacturing systems that produce a single type of a product. In this research, we examine the CONWIP, Base Stock, and CONWIP/Kanban Hybrid pull strategies in multi-product manufacturing systems. In a multi-product manufacturing system, several types of products are manufactured by utilizing the same resources. We develop queueing network models of multi-stage, multi-product manufacturing systems operating under the three aforementioned pull control strategies. Simulation models of the alternative production systems are implemented using an open-source software. A comparative evaluation of CONWIP, Base Stock and CONWIP/Kanban Hybrid in multi-product manufacturing is carried out in a series of simulation experiments with varying demand arrival rates, setup times and control parameters. The control strategies are compared based on average wait time of backordered demand, average finished products inventories, and average length of backorders queues. The Base Stock strategy excels when the manufacturing system is subjected to high demand arrival rates. The CONWIP strategy produced consistently the highest level of finished goods inventories. The CONWIP/Kanban Hybrid strategy is significantly affected by the workload that is imposed on the system.

Production and maintenance in industries: impact of industry 4.0

Purpose Production industries are undergoing a digital transition, referred to as the fourth industrial revolution or Industry 4.0, as a result of rapidly expanding advances in information and communication technology. The purpose of this research is to provide a conceptual insight into the impact of unique capabilities from the fourth industrial revolution on production and maintenance tasks in terms of providing the existing production companies a boost by making recommendations on areas and tasks of great potential. Design/methodology/approach A survey and a literature review are among the research methods used in the research. The survey collected empirical data using a semi-structured questionnaire, which provided a broad overview of the company's present condition in terms of production and maintenance, resulting in more comprehensive and specific information regarding the study topics. Findings The study points out that, the implementation of I4.0-technology leads to an increase in production, asset utilization, quality, reduced machine down time in industries, and maintenance. Sensor technology, big data analysis, cloud technologies, mobile end devices, and real-time location systems are now being implemented to improve production processes and boost organizational competitiveness. Moreover, the study highlights that data acquired throughout the production process is utilized for quality control, predictive maintenance, and automatic production control. Furthermore, I4.0 solutions help companies to be more efficient with assets at each stage of the process, allowing them to have a stronger control on inventories and operational-optimization potential. Originality/value The findings of the study was supported by empirical data collected through survey that provides an intangible understanding of the importance of distinctive capabilities from the I4.0 revolution on production and maintenance tasks. In this study, some recommendations and guidelines to enhance these tasks are provided that are vital for existing production companies.

Artificial Intelligence and Data Analytics for Virtual Flow Metering

Modern challenges in reservoir management have recently faced new opportunities in production control and optimization strategies. These strategies in turn rely on the availability of monitoring equipment, which is used to obtain production rates in real-time with sufficient accuracy. In particular, a multiphase flow meter is a device for measuring the individual rates of oil, gas and water from a well in real-time without separating fluid phases. Currently, there are several technologies available on the market but multiphase flow meters generally incapable to handle all ranges of operating conditions with satisfactory accuracy in addition to being expensive to maintain. Virtual Flow Metering (VFM) is a mathematical technique for the indirect estimation of oil, gas and water flowrates produced from a well. This method uses more readily available data from conventional sensors, such as downhole pressure and temperature gauges, and calculates the multiphase rates by combining physical multiphase models, various measurement data and an optimization algorithm. In this work, a brief overview of the virtual metering methods is presented, which is followed by the application of several advanced machine-learning techniques for a specific case of multiphase production monitoring in a highly dynamic wellbore. The predictive capabilities of different types of machine learning instruments are explored using a model simulated production data. Also, the effect of measurement noise on the quality of estimates is considered. The presented results demonstrate that the data-driven methods are very capable to predict multiphase flow rates with sufficient accuracy and can be considered as a back-up solution for a conventional multiphase meter.

Agile Smart Completion Application for Effective Water Production Control in Heterogeneous Carbonate Reservoir in Abu Dhabi Offshore Reservoir

This paper provides the learnings from a successful application of a smart completion in a complex heterogeneous carbonate reservoir. It details the study, planning, coordination, and implementation process of two pilot wells by a multidisciplinary team, and pilot production performance results, illustrating the success. First, to select an optimum completion design for the field, multi-segment well option and local grid refinement option were applied to the reservoir simulation model including calibration of faults/fractures. Second, based on the modified model, sensitivity analysis was conducted; 1) by selecting different types of completion including Open-hole, blank pipes (BP), compartmentalized slotted liners (SL), inflow control device (ICD) and hydraulic flow control valve (FCV); 2) by optimizing the number of compartments (packer and blank pipe placements for all cases), and ICD / FCV numbers and nozzle sizes. Using the data from the modeled cases, economic analysis was conducted, which indicated that the ICD in conjunction with sliding sleeves (SSD) was the best option. Two candidate wells were selected to cover the variation of reservoir characteristics: one well representing the heterogeneous part of the reservoir with high-density of faults, fractures and kurst, and another one representing the relatively homogenous part of the reservoir suffering from heel to toe effect. A multidisciplinary implementation team was set up to align all stakeholders on subsurface requirements, following up the completion design, coordinating material procurement and logistics for mobilizations, daily drilling operations follow-up, real-time logging data interpretations and completion design adjustment. Evaluation of the two pilots’ results based on predefined KPIs during the study, exceeded overall expectations.

Vine architecture and production control measures to improve the quality of the wine from Shiraz variety (Vitis vinifera L.)

Aim of study: Ssix thinning treatments were studied to improve the chemical composition and quality of grapes of cv. ‘Shiraz’ under two vine architectures (vase and trellis). Area of study: Spain (from 2015 to 2016). Material and methods: The following thinning treatments were applied during four consecutive crop seasons: T0, control; T1, removal of 33% of the clusters (75 BBCH stage); T2, removal of 33% of the clusters (85 BBCH stage); T3, removal of the leaves at the base of the branches; T4, removal of the leaves at base of the branches together with removal of 33% of the clusters; T5, grouping of green branches; and T6, grouping of green branches and removal of 33% of the clusters. Main results: All the treatments increased the luminosity and degree of polymerization, improving the color intensity and stability in the wines. In the musts, the levels of phenolic compounds (from 48.0 and 46.7 mg L-1 in T0 trellis and vase, respectively, to 66.8 and 68.9 mg L-1 in T6 trellis and vase, respectively), anthocyanins and sugars (from 22.0 and 22.1 mg L-1 in T0 trellis and vase, respectively, to 24.3 mg L-1 in T6 trellis and vase), were considerably improved. Research highlights: Treatments T6 and T4 reported the best results. Branch grouping was more efficient than leaf removal regarding the contents of phenolic compounds. With respect to vine architecture, the results point out small differences, but we recommend the application of the treatments, mainly T4 and T6, under vase architecture. The season effect was mainly observed in the fourth year, probably due to the climatic conditions.