Industrial Problems Research Articles

Optimal control of mineral processing plants using constrained model predictive static programming

The model predictive static programming (MPSP) technique, which is extended recently to incorporate applicable state and control constraints, operates on the philosophy of nonlinear model predictive control (NMPC). However, it reduces the problem into a lower-dimensional problem of control variables alone, thereby enhancing computational efficiency significantly. Because of this, problems with larger dimensions and/or increased complexity can be solved using MPSP without changing the computational infrastructure. In this paper, the MPSP technique with applicable constraints is applied to two challenging control problems in the mineral processing industry: (i) a single-stage grinding mill circuit model, and (ii) a four-cell flotation circuit model. The results are compared with a conventional nonlinear MPC approach. Comparison studies show that constrained MPSP executes much faster than constrained MPC with similar/improved performance. Therefore, it can be considered a potential optimal control candidate for mineral processing plants.

REVIEW AND CRITICAL ANALYSIS OF THE CURRENT STATE AND WAYS OF DEVELOPING THE TECHNOLOGICAL PROCESS OF OIL PRODUCTION BY AN ELECTRIC DRIVE IN INTERMITTENT MODES OF OPERATION OF LOW- AND MEDIUM-RATE WELLS

Link for citation: Kladiev S.N. Review and critical analysis of the current state and ways of developing the technological process of oil production by an electric drive in intermittent modes of operation of low- and medium-rate wells. Bulletin of the Tomsk Polytechnic University. Geo Аssets Engineering, 2023, vol. 334, no. 8, рр. 220-231. In Rus. Relevance. The Russian Federation is one of the world leaders among oil-producing countries in terms of proven oil reserves. Historically, industrial oil production in the Russian Empire began in the area of the Caspian Sea on the territory of modern Azerbaijan. The energy strategy of the Russian Federation for the period up to 2035, as one of the measures to ensure the energy security of the country, provides for the introduction into economic circulation of hard-to-recover oil reserves (including from the Bazhenov formation) based on innovative domestic technologies and equipment. The main problem of the oil industry in Russia, as well as throughout the world, is the decline in the quality of the resource base. In oil-producing regions, there is a depletion of active oil reserves. Significant residual reserves of developed fields are expected to be brought into active exploitation using new oil production technologies. Ways of growth in oil production are possible in accordance with three different scenarios: innovative – it is supposed to increase the contribution to the total indicators of Russian oil production from new provinces, such as Eastern Siberia, the Republic of Sakha (Yakutia), as well as new fields in Western Siberia and the Krasnoyarsk Territory and the development of the shelf northern seas; forced scenario – in case of more active introduction of new technologies and incentive measures that reduce the cost of the production process, it is possible to increase the efficiency of oil production in offshore and hard-to-recover fields; extensive scenario of oil production is possible only at high market prices for oil. The main volume of production is carried out and will continue to be exclusively electrically driven. The purpose: a review and critical analysis of the current state and ways of developing the technological process of oil production by an electric drive in intermittent modes of operation of low- and medium-rate wells. Object: theoretical substantiation of the introduction of cyclic or short-term operation of electric centrifugal pump installations with an electric drive method of downhole oil production into practice. Methods: geophysical research to develop a concept for the operation of a marginal well stock, ways to increase the profitability of oil production, methods for optimizing the stock of medium and marginal wells, putting them into economic circulation. Results. Based on a critical analysis of literary sources and a feasibility study, it is shown that the most promising way to extract hard-to-recover oil reserves on the example of the Bazhenov formation is the electric drive of a submersible centrifugal pump according to the scheme «ground power converter – submersible cable – submersible electric motor – electric centrifugal pump». The technology of cyclic operation of wells in oil production shown that it is economically feasible for low- and medium-rate wells and is widely implemented in wells that cannot be operated in a continuous mode.

インシュアテック(Insurtech)の登場と保険産業の変化要因に関する考察

Purpose: This paper focuses on the impact of the emergence of InsurTech on the insurance industry. It is true that previous studies have been difficult to focus on the cutting-edge technology called Insurtech or to judge what kind of influence it has from a comprehensive perspective. Therefore, in this study, rather than introducing the technical aspects of Insurtech in detail, it is shown that the introduction of Insuretech is inevitable due to changes in the insurance industry and changes in the external environment, such as the consumer platform. In other words, since the introduction of Insurtech will inevitably happen in the future, the goal of this study is to suggest that sufficient preparation and research are necessary.
 Research design, data, and methodology: In order to find out how InsureTech is being used in the insurance industry, how to change the insurance business model for representative insurance startups such as Lemonade, Metromile, and Oscar Torv. It is a method of research to find out if there is.
 Results: The results of this study are as follows. First, the emergence of Insuretech is benefiting both insurance providers and beneficiaries in the insurance industry. Second, the emergence of Insuretech is changing the insurance business model, and although some changes are caused by the emergence of Insuretech, it is characterized by changes in external environmental factors such as existing consumer platforms.
 Implications: The implications of this study are as follows. The emergence of Insure Tech provides new opportunities to the insurance business as it provides the ability to identify and solve problems in the insurance industry. Insurtech is also changing the insurance business as a whole, which has a positive impact on the future insurance industry by creating new market products and consumers.

Optimal stochastic scheduling in residential micro energy grids considering pumped-storage unit and demand response

Improving energy efficiency, production costs, greenhouse gas emissions, and reliability are some of the most important problems in the energy industry. Energy storage systems and demand-side management (DSM) programs are among the existing solutions for removing such problems. This study presents an improved micro energy grid (MEG) to reduce operating costs as well as greenhouse gas emissions using combined cooling, heating, and power (CCHP) systems, wind turbines (WTs), photovoltaic (PV) units, pumped-storage units, and heating and cooling storage units. In this system, pumped-storage units are employed to store energy. Price- and incentive-based programs are employed to obtain better performance on the demand side. Uncertainties of wind speed, solar power, electricity price, and electrical load are considered to achieve more accurate results. In this paper, the Latin hypercube sampling (LHS) method is applied to generate various scenarios. Then, K-means clustering approach is employed to reduce the number of scenarios. By producing and reducing the proposed scenario, the inherent uncertainty in renewables can be covered, which will result in a more efficient model. Meta-heuristic whale optimization algorithm (WOA) and Pareto model are used to solve single- and multi-objective functions and to optimally design the proposed structure considering contradictory functions, respectively. The features of the proposed developed algorithm are simplicity in execution and absence of derivative operator, increase of local and global search capability and consideration of objective functions with different nature. Moreover, fuzzy decision-making mechanism is proposed to select the optimal solution from the Pareto set of solutions. Finally, the proposed approach in different scenarios on the microgrid with various sources is discussed. The results indicate the proposed method properly obtains the optimal solution.

Sustainable and Resilient Capacity Expansion Planning for Chemical Processing Industry: A Bi-Objective Approach

According to United Nations reports, the worldwide population is expected to reach around 9.6 billion by 2050. This forecast emphasizes the critical role of energy and raw materials that are needed to meet the tremendous demand for goods. Consequently, firms feel pressured to establish sustainable and resilient strategic plans to acquire new process technologies and expand their capacity on time. These decisions are made at the highest management level, supported by a set of capacity expansion portfolios, to improve their competitiveness, especially in capital-intensive industries such as chemical processing. This paper investigates the sustainable and resilient capacity expansion problem for such industries within a long-term horizon. The main objective is to develop a holistic capacity expansion planning framework that fits the chemical processing industries and can be used to generate resilient scenarios while enhancing their sustainability measures. To this end, a bi-objective mixed-integer programming model was developed to solve the sustainability–resilience–profitability dilemma. The results showed a controversial relationship between the profitability of capacity expansion investments and a company’s commitment to sustainability and resilience. Furthermore, capacity expansion decisions were shown to primarily depend on the importance assigned to maximize profit as a managerial choice. However, there is no clear trend in sustainability preferences based on the sustainability weighting choice.

Identification of seropositive wild boars in Eurasia as a sign of possible formation of African swine fever-endemic areas (review)

The continued spread of African swine fever (ASF) in Eurasia remains a global problem for the world pig industry. The disease is characterized by high mortality (up to 100 %) and acute course - domestic and wild animals die within the first two weeks after infection. However, active surveillance on ASF in Eastern Europe had been showing regular detection of seropositive susceptible animals, especially among wild boar populations which may indicate chronic, asymptomatic infection and even the survival of individual animals. At the same time, the persistence of the virus in the wild boar population creates constant risks of sporadic outbreaks of ASF in infected areas, and the infection can become endemic. The aim of the study was a systematic review of the available data on seroprevalence among wild boars in relation to the possible establishment of ASF endemicity in Eurasia. In these animals, there was a change in the dynamics of the disease, which is manifested by self-sustaining cycles of infection. Seropositive wild boars are being found in the Baltic countries, Hungary, Poland, Romania, Slovakia, and Russia. Seroprevalence rates among wild boars hunted in ASF-infected areas of European countries range from 0.3 to 3.8 %. In the Baltic countries, the number of seropositive samples from wild boars exceeds the number of samples positive for ASF virus in polymer chain reaction (PCR). A similar trend persists in those regions where the ASF virus has been present for a long time (Poland, Lithuania, Latvia, Estonia), which may indicate the endemic nature of ASF. In the Russian Federation, ASF-endemic territories in the wild have not yet been registered, although isolated cases of seropositive wild boars have been detected in some regions since 2013. In the future, in order to understand the dynamics of the disease in the wild, it is necessary to conduct a comprehensive diagnosis of the ASF virus genome and antibodies in wild boar samples, which eventually will allow choosing the right strategy to combat ASF.

CUSTOMER SATISFACTION TOWARDS FARM AT SAN BENITO BASED ONLINE REVIEWS FROM SELECTED TRAVEL WEBSITE

Service quality has been identified as a critical problem in the tourism industry. Despite several studies on service quality, the function of service quality and customer satisfaction in the tourism business, as well as their relationship, remains unsolved. The main focus of this paper is to assess the level of Customer Satisfaction in The Farm at San Benito Based on Online Reviews from Selected Travel Websites. This study also addresses the well-known SERVQUAL model and describes additional service quality and customer satisfaction models used in the tourism sector. The model focuses on the five variables namely, tangible, reliability, responsiveness, assurance, and empathy focusing on their core products as a Holistic Medical Wellness Resort. Based on the data gathered from five hundred reviews from the four travel websites, the study concludes that the respondents are overall satisfied with the Wellness Resort Services.

Analysis of the Effect of Various Potential Antimicrobial Agents on the Quality of the Unpasteurized Carrot Juice.

Short shelf-life and poor microbial quality of minimally processed foods of plant origin pose a serious problem for the food industry. Novel techniques of minimal treatment combined with disinfection are being researched, and, for fresh juice, the addition of antimicrobial agents appears to be a promising route. In this research, fresh, nonfiltered, unpasteurized carrot juice was mixed with four potential antimicrobials (bourbon vanilla extract, peppermint extract, cannabidiol oil, and grapefruit extract). All four variants and the reference pure carrot juice were analyzed for metapopulational changes, microbial changes, and physicochemical changes. The potential antimicrobials used in the research have improved the overall microbial quality of carrot juice across 4 days of storage. However, it is important to notice that each of the four agents had a different spectrum of effectiveness towards the groups identified in the microflora of carrot juice. Additionally, the antimicrobials have increased the diversity of the carrot juice microbiome but did not prevent the occurrence of pathogenic bacteria. In conclusion, the use of antimicrobial agents such as essential oils or their derivatives may be a promising way of improving the microbial quality and prolonging the shelf-life of minimally processed foods, such as fresh juices, but the technique requires further research.

Research on the Development Status of Smart and Healthy Pension Industry in Chongqing for 2035 based on TF-IDF Algorithm

The problem of population aging is crucial to social development, and the development of smart health care industry is one of the solutions to the problem of population aging. At present, the smart healthy aging industry in Chongqing is still dominated by governmental departments, and policies have a guiding role in the development of the industry, so policies are highly researchable. This paper collects 42 policy texts from March 2016-2023, extracts the keywords in the policy library using the TF-IDF algorithm, analyzes the development status and problems of the smart old-age health industry in Chongqing Municipality in the context of the actual situation, and puts forward relevant suggestions for the future development of the smart old-age health industry in Chongqing Municipality.

A way towards zero-waste campaign and sustainability in sugar industries; filter cake valorisation as energy pellets

A by-product known as filter cake has been a major problem for sugar industries. Despite its use as fertiliser, millions of tonnes of filter cake have been discarded as waste. Thus, the concept of wastevalorisation is highly essential to the production of useful energy. Filter cake consists of fine particulates with a high moisture content; consequently, crushing is not necessary for pelletisation. A preliminary investigation has demonstrated the tremendous potential of filter cake pellets with a higher heating value of 8–12 MJ/kg, depending on their moisture content. However, pelletisation must be properly optimised. In the present study, the initial moisture contents of filter cake werevaried between 10, 20, and 30%. The physical properties of pellets with these initial moisture levels were then determined and compared with EN 14961-1. Moreover, the relationship between particle and bulkdensities was determined and utilised for optimisation. The results indicated that an initial moisture content between 10 and 20% was suitable for pelletisation, with excellent conformance to the EN 14961-1 standard. The diameter, length, bulk density, particle density, fines, and durability values were 5.90–5.98 mm, 28.11–29.18 mm, 832.6–852.6 kg/m3,1517.3–1626.1 kg/m3, 0.22–0.30%, and 97.8–98.1%, respectively. In addition, a prototype system demonstrated the feasibility of the concept of waste valorisation for a zero-waste campaign. Furthermore, economic analysis indicated that if 2.04 million tonnes per year of filter cake pellets were utilised as fuels in steam power plants, they could generate 2.63x109 kWh of electricity per year, resulting in approximately 318 million US dollars.

Explainable subgradient tree boosting for prescriptive analytics in operations management

Motivated by the success of gradient boosting approaches in machine learning and driven by the need for explainable prescriptive analytics approaches in operations management (OM), we propose subgradient tree boosting (STB) as an explainable prescriptive analytics approach to solving convex stochastic optimization problems that frequently arise in OM. The STB approach combines the well-known method of subgradient descent in function space with sample average approximation, and prescribes decisions from a problem-specific loss function, historical demand observations, and prescriptive features. The approach provides a decision-maker with detailed explanations for the prescribed decisions, such as a breakdown of individual features’ impact. These explanations are particularly valuable in practice when the decision-maker has the discretion to adjust the recommendations made by a decision support system. We show how subgradients can be derived for common single-stage and two-stage stochastic optimization problems; demonstrate the STB approach’s applicability to two real-world, complex capacity-planning problems in the service industry; benchmark the STB approach’s performance against those of two prescriptive approaches—weighted sample average approximation (wSAA) and kernelized empirical risk minimization (kERM); and show how the STB approach’s prescriptions can be explained by estimating the impact of individual features. The results suggest that the quality of the STB approach’s prescriptions is comparable to that of wSAA’s and kERM’s prescriptions while also providing explanations.

An efficient simulation procedure for the expected opportunity cost using metamodels

Many decision problems in modern industries involve the performance optimization of discrete-event dynamic systems. Because of the stochasticity of these systems, performance usually is evaluated through simulation. Finding the optimal designs of these systems can be modeled as a ranking and selection problem. This research considers the problem of selecting the best design from among numerous designs. We minimized the expected opportunity cost (EOC) of incorrect selection with a limited computing budget. The entire domain of designs could be divided into several adjacent partitions, and the performances of designs in each partition were estimated using a regression metamodel. We assumed the underlying function in each partition to be quadratic. Using large deviations theory, we then derived an asymptotically optimal budget allocation rule and developed a sequential allocation algorithm to implement the allocation rule. The EOC measure was compared with the probability of correct selection measure in a set of large-scale simulation optimization problems. Numerical experiments verified the effectiveness of our proposed simulation procedure.

Независимый аудит как новое направление оценки промышленной безопасности на опасных производственных объектах горнодобывающего комплекса

The paper discusses a new key trend used to assess the state of industrial safety at mining operations as well as the cooperation efficiency. The experience GEOEXPERT LLC has gained in carrying out independent technical auditing and the relevance of this line of activity has been demonstrated. Taking into account current challenges and the experience of technical auditing, as well as the prospects for the development of this activity, the article and the data presented in it will help the top management to make their decisions, while the description of real auditing cases will provide the mining companies with an insight into the use of this new method of co-operation. Independent technical auditing is one of the tools to control the state of industrial safety at a mining operation, which provides a general picture of the company, classification of hazardous production facilities according to their hazard characteristics, independent verification of compliance of the production process organization and the production patterns with the regulatory requirements in order to improve the safety of operation, enhance the quality of products and reduce production risks. Three decades of experience gained by GEOEXPERT LLC and studying various aspects of challenges in the mining industry help to identify the method of independent technical auditing as one of the main tools for solving industrial safety problems and preventing emergencies at the operations.

Effectiveness of integrated bovine leukemia virus eradication strategies utilizing cattle carrying resistant and susceptible major histocompatibility complex class II DRB3 alleles

Bovine leukemia virus (BLV) has spread worldwide and causes serious problems in the cattle industry owing to the lack of effective treatments and vaccines. Bovine leukemia virus is transmitted via horizontal and vertical infection, and cattle with high BLV proviral load (PVL), which is a useful index for estimating disease progression and transmission risk, are considered major infectious sources within herds. The PVL strongly correlates with highly polymorphic bovine lymphocyte antigen (BoLA)-DRB3 alleles. The BoLA-DRB3*015:01 and *012:01 alleles are known susceptibility-associated markers related to high PVL, and cattle with susceptible alleles may be at a high risk of BLV transmission via direct contact with healthy cows. In contrast, the BoLA-DRB3*009:02 and *014:01:01 alleles comprise resistant markers associated with the development of low PVL, and cattle with resistant alleles may be low-risk spreaders for BLV transmission and disrupt the BLV transmission chain. However, whether polymorphisms in BoLA-DRB3 are useful for BLV eradication in farms remains unknown. Here, we conducted a validation trial of the integrated BLV eradication strategy to prevent new infection by resistant cattle and actively eliminate susceptible cattle in addition to conventional BLV eradication strategies to maximally reduce the BLV prevalence and PVL using a total of 342 cattle at 4 stall-barn farms in Japan from 2017 to 2019. First, we placed the resistant milking cattle between the BLV-positive and BLV-negative milking cattle in a stall barn for 3 yr. Interestingly, the resistant cattle proved to be an effective biological barrier to successfully block the new BLV infections in the stall-barn system among all 4 farms. Concomitantly, we actively eliminated cattle with high PVL, especially susceptible cattle. Indeed, 39 of the 60 susceptible cattle (65%), 76 of the 140 neutral cattle (54%), and 20 of the 41 resistant cattle (48.8%) were culled on 4 farms for 3 years. Consequently, BLV prevalence and mean PVL decreased in all 4 farms. In particular, one farm achieved BLV-free status in May 2020. By decreasing the number of BLV-positive animals, the revenue-enhancing effect was estimated to be ¥5,839,262 ($39,292.39) for the 4 farms over 3 yr. Our results suggest that an integrated BLV eradication program utilization of resistant cattle as a biological barrier and the preferential elimination of susceptible cattle are useful for BLV infection control.

Integration of chemical engineering skills in the curriculum of a master course in industrial engineering

Promoting new teaching methodologies is essential to improve the participation, motivation, interest, and results of students in all educational stages. In this sense, flipped classroom and problem-based learning have emerged in the last years as fascinating options to be implemented in high education levels thanks to the students’ maturity and previously acquired background. Working with motivating case studies based on real processes with their restrictions appears as an opportunity to bring future professionals closer to the industrial problems; this will capacitate engineers to solve and understand complex procedures getting tangible results. In this context, the main goal of this work is to combine flipped classroom and problem-based learning methodologies to gain the interest of students of a Master course in Industrial Engineering in the subject of Chemical Processes using real data of local companies. A survey, designed by the academics involved, will help collecting the opinion of students as well as the acquired skills in the frame of the specific subject. Results demonstrated the satisfaction of the students with the course, highlighting mainly the acquisition or improvement of self-learning skills (survey 4.0/5.0), capacity for organization and planning (survey 4.0/5.0), analytical ability (survey 4.2/5.0), and teamwork (survey 4.3/5.0). In addition, the grades accomplished during the year of implementation show that although the success rate is quite similar to preceding years, the marks achieved are considerably higher.

Factors influencing construction workers’ intention to transfer occupational health and safety training

The effectiveness of occupational health and safety (OHS) training programs is dependent on the extent to which workers transfer OHS knowledge, skills and abilities acquired from OHS training into post-training workplace performance. However, the lack of training transfer has long been a critical problem in the construction industry. As an attempt to gain a better understanding of the transfer of training, this research investigated factors affecting construction workers’ OHS training transfer intention. A questionnaire survey was used to collect data from Australian construction workers, and 295 valid responses were obtained. Partial least squares structural equation modelling was used to test the model of transfer intention adapted from the Theory of Planned Behaviour (TPB). Multigroup analysis was conducted to identify the similarities and differences in terms of factors affecting transfer intention among managerial/professional and non-managerial/manual construction workers. The research found that the TPB can be used to explain the transfer intention of OHS training among construction workers. Perceived behavioural control was found to be an antecedent of the intention to transfer among both groups of workers. However, attitudes only predicted transfer intention among managerial/professional workers, while subjective norms only predicted transfer intention among non-managerial/manual construction workers. The study provided a good understanding of the formation of transfer intention among managerial/professional and non-managerial/manual construction workers and identified critical factors influencing the transfer intention of these two groups. This new knowledge is useful for training providers and construction organisations to develop targeted strategies to increase the transfer of OHS skills and knowledge among construction workers and improve the effectiveness of OHS training.

Reduced order modelling using neural networks for predictive modelling of 3d-magneto-mechanical problems with application to magnetic resonance imaging scanners

The design of magnets for magnetic resonance imaging (MRI) scanners requires the numerical simulation of a coupled magneto-mechanical system where the effects that different material parameters and in-service loading conditions have on both imaging and MRI performance are key to aid with the design and the manufacturing process. To correctly capture the complex physics, and to obtain accurate solutions, finite element simulations with dense meshes and high order elements are needed. Reduced order model approaches, based on the established proper orthogonal decomposition (POD) approach, are attractive as they can rapidly predict the numerical simulations needed under changing parameters or conditions. However, the projected (PODP) approach has an invasive computational implementation, whilst the interpolated (PODI) approach presents challenges when the dimension of the space of parameters to be investigated becomes large. As an alternative, we investigate a POD technique based on using a neural network regression, which is not as invasive as PODP, but has superior approximation properties compared to PODI. We apply this to the coupled magneto-mechanical system to understand three pressing industrial problems: firstly, the accurate and rapid computation of the resonant frequencies associated with this coupled magneto-mechanical system, secondly, the effects of magnet motion on the Ohmic power and kinetic energy curves, and, thirdly, the prediction of the uncertainty in Ohmic power and kinetic energy curves as a function of exciting frequency for uncertain material parameters.

DEVELOPMENT AND APPLICATION OF NEW COMPOSITIONS TO IMPROVE THE EFFICIENCY OF OIL FIELD EQUIPMENT OPERATION

One of the urgent problems in the oil industry is the reliable protection of oil field equipment from corrosion. With this in mind, as a result of laboratory studies, three compositions were developed based on phospholipids, fatty acids, phosphoric acid, nitrogen compounds, asidol, naphthenic acids and light gas oil. The complexity of the composition gives the resulting compositions multifunctionality and allows them to be used in various aggressive conditions.
 In laboratory conditions, the effect of these compositions on the corrosion rate of metals and on the vital activity of sulfate reducing bacteria (SVB) was studied. Based on the obtained results, the concentration of the compositions (500 mg/l) was established, providing a protective effect against corrosion, which was 94–95 %, and the degree of suppression of SVB was 97–99 %.
 Field tests of corrosion inhibitors also yielded positive results: the protective effect against corrosion was 89–90 %, and the degree of SVB suppression was 92–97 %.

Integration of hybrid score functions to design new adaptive EWMA control chart to monitor the process mean shift

Small-to-moderate shifts in the process parameters can be detected using the traditional Exponentially Weighted Moving Average (EWMA) control chart. The classical EWMA control chart's parameter helps only to identify the specific size of the shift. However, various shifts occur in real-world processes, so the conventional EWMA control chart performs inefficiently for off-target shifts. This problem has been confronted by applying an adaptive EWMA (AEWMA) control chart, an advanced version of the classical EWMA control chart. The score functions are utilized to design the AEWMA control chart. Generally, the Huber and Bi-square (score) functions have unique characteristics, such as monotone and redescended, respectively.There has not been any investigation into the simultaneous and/or joint deployment of score functions. So, by taking this point as motivation, this study aims to propose a new score function by blending the Huber and Bi-square characteristics into one hybrid formulation and then utilize it to design a new AEWMA control chart to monitor different sizes of the shift in the process location parameter. To evaluate the proposed control chart performance against other control charts, Monte Carlo simulation is applied to obtain the run length properties under zero-state and steady-state environments. Performance measures, such as average run length, standard deviation of run length, and median of run length, are considered to evaluate the performance at a single shift. In contrast, extra quadratic loss, relative average run length, and performance comparison index are utilized to evaluate effectiveness for a specific range of shifts. The comparison based on performance measures and visual presentation reveals the superiority of the proposed control chart. Besides, the proposed control chart is employed in the real-world chemical engineering process industry problem, demonstrating excellent detection ability of anomalies in air pollutant data. The comparison based on performance measures and visual presentation reveals the good performance of the proposed control chart.

Implementation of BIM-technologies for the design of mining and metallurgical industry facilities of the Republic of Uzbekistan

The article is devoted to the functionality and role of the application of BIM technologies in design at the present stage of development of information structures in Uzbekistan. The authors noted that a typical problem in the design industry around the world is the use of outdated methodologies and software complexes, which require a lot of labor and human resource coasts. Therefore, it is reasonable to use BIM technology in design as a key effective concept for improving all design processes.