Spare Components Research Articles

Reliability and performance evaluation of weighted [formula omitted]-out-of-[formula omitted]:G system consisting of components with discrete lifetimes

For the k-out-of-n system consisting of components that have different weights, the system is in a good state if the total weight of working components is at least k. Such a system is known to be weighted k-out-of- n:G system. Although the weighted k-out-of-n system that has continuously distributed components’ lifetimes has been extensively studied, the discrete weighted k-out-of-n:G system has not been considered yet. The present paper fills this gap by modeling and analyzing the weighted k -out-of-n:G system that consists of discretely distributed components’ lifetimes. In particular, the behavior of the total capacity/weight of the system with respect to the component failures is evaluated. An optimization problem that is concerned with the determination of optimal number of spare components is also formulated by utilizing the mean lost capacity of the system.

Mixed-integer programming models for a multi-period integrated reverse logistics network with multiple recovery options and different quality levels of returns

This paper addresses an integrated reverse logistics (RL) model with a production route and multiple recovery options, including repair, refurbishing, remanufacturing, recycling, and selling spare components. We aim to use the quality grading system method to analyse returns comprehensively. In this regard, quality levels are used to classify returns and quality thresholds are utilised to categorise them into certain quality groups. The proposed model deals with different activities such as locating, purchasing, transporting, processing, inventory holding, recovering, and production in a planning horizon with multiple periods. A two-stage optimisation model is proposed to facilitate the decision-making process. In Stage 1, a mixed integer linear programming (MILP) model is proposed to minimise the costs and determine the number of returned products directed into different recovery routes. In Stage 2, another MILP is proposed to maximise the network’s profit. Furthermore, 350 scenarios are defined to examine the network’s performance and decide the optimal quality thresholds. Finally, the proposed models are applied to a real dataset and solved by the CPLEX solver through Pyhton. According to the results, scenarios that use multiple recovery options earn higher profits and lower costs as most demands are satisfied and the stock level of inventories decreases.

The Frechet Reliability for (2+2) Cascade Model

In this paper, a reliability function for one of the cascade models was found; the model consists of two basic components (B_1 and B_2 ) and two spare components (B_3 and B_4 ), and it is sufficient for the model to be in a working state with the presence of two active components and, in case of failure of one of the two basic components, it is compensated with one of the two standby components to keep the model running. It was assumed that the strength-stress factors traced the Frechet, the parameters of the Frechet were estimated by three different estimation methods (Moments, Least Squares and Weighted Least Square,), after which the reliability of the model was estimated. Monte Carlo simulations were also conducted to compare the results and find out which estimation methods are the best to estimate the reliability of the model using two statistical criteria: MSE and MAPE, where it was presented that least square estimation is the preferred for estimating the function of reliability.

Scheduling the repair and replacement of individual components in operating systems: a bi-objective mathematical optimization model

Preventive maintenance (PM) is performed so that failure is avoided while corrective maintenance is performed after a failure has occurred in order to restore the system back to an operational state. This research aims at scheduling PM activities for a multi-component system within a finite time horizon. We consider a setting with two stakeholders, being the system operator and the maintenance workshop, and two different contract types governing their joint activities, namely an availability contract and a turn-around time contract. Components in the systems that are to be maintained are sent to the maintenance workshop, which needs to schedule and perform all maintenance activities while at the same time satisfying the contract and not exceeding the workshop capacity. Our modelling is based on a mixed-binary linear optimization model of a PM scheduling problem with so-called interval costs over a finite and discretized time horizon. We enhance this scheduling model with the flow of individual components through the maintenance workshop, including stocks of spare components, both those components that need repair and the repaired ones. The resulting scheduling model is then utilized in the optimization of two main contracts, namely maximizing the availability of repaired (or new) components and minimizing the deviation from the contracted turn-around times for the components in the maintenance loop. Each of these objectives is combined with the objective to minimize the costs for maintenance of the operating system, leading to two bi-objective optimization problems. We analyse the two contracting forms between the stakeholders by studying and comparing the Pareto fronts resulting from different parameter settings, regarding minimum allowed stock levels and investments in repair capacity of the workshop. Our bi-objective mixed-binary linear optimization model is able to capture important properties of the results from the contracting forms as well as to show that, in our setting, an availability contract performs better than a turn-around time contract in terms of tractability.

Implementation Of Information And Communication Technology In Improving Intellectual Competence Of Reserved Components Through Integrated Training And Monitoring System Of Reserve Components (SPMT Komcad) In Inactive Periods. (Qualitative Analytical Descriptive Study on MAN 1 and MAN 2 Tasikmalaya Regency)

Reserve Component as a national resource that is prepared to be deployed through mobilization to enlarge and strengthen the strength and capability of the main components, TNI and POLRI. The existence of an active period and an inactive period of Komcad on the other hand becomes a question whether Komcad can maintain its intellectual competence during an inactive period. This study aims to determine the use of information and communication technology in increasing the intellectual competence of reserve components through the Reserved Components Integrated Training and Monitoring System (SPMT Komcad) during inactivity. The method used in this research is a quantitative approach. The data collection technique in this research is using literature study, the authors develop a system with the waterfall model, namely sequentially starting from the analysis, design, coding, testing and support stages. The results of this study are the increase in intellectual competence of reserve components can be done through an integrated training and monitoring system for Reserve Components (SPMT Komcad). SPMT Komcad can be a solution to the concerns of spare components in maintaining their competence in inactive periods.

Deep reinforce learning for joint optimization of condition-based maintenance and spare ordering

Condition-based maintenance (CBM) policy can avoid premature or late maintenance and reduce system failures and maintenance costs. Most existing CBM studies cannot solve the dimensional disaster problem in multi-component complex systems. Only some studies consider the constraint of maintenance resources when searching for the optimal maintenance policy, which is hard to apply to practical maintenance. This paper studies the joint optimization of the CBM policy and spare components inventory for the multi-component system in large state and action spaces. We use Markov Decision Process to model it and propose an improved deep reinforcement learning algorithm based on the stochastic policy and actor-critic framework. In this algorithm, factorization decomposes the system action into the linear combination of each component's action. The experimental results show that the algorithm proposed in this paper has better time performance and lower system cost compared with other benchmark algorithms. The training time of the former is only 28.5% and 9.12% of that of PPO and DQN algorithms, and the corresponding system cost is decreased by 17.39% and 27.95%, respectively. At the same time, our algorithm has good scalability and is suitable for solving Markov decision-making problems in large-scale state and action space.

Failure Rate Assessment for Onshore and Floating Offshore Wind Turbines

A detailed analysis is performed on a dataset of failure and maintenance records from various onshore wind farms located in different geographical areas for the safety, risk, reliability, availability, and maintainability characterization of wind turbines. Specifically, characteristics related to failures, including the criticality of failure modes, failure frequencies, failure rates, and lifetime distributions of components, are analyzed to support the failure identification and failure prevention of wind turbines. Additionally, characteristics of maintenance, including typical maintenance measures of failures, policies for spare components, delayed maintenance, as well as related times such as reaction time, travelling time, and mean time to repair, are provided to support the maintenance management of wind farms. Based on the operational data analysis results, a reliability influence factor-based failure data correction approach is presented to transfer the onshore data to floating offshore turbines by modeling the differences in failure occurrences based on experts’ judgment. A comprehensive comparison with existing studies validates the performance of the proposed approach.

Development of a Procedure for Risk-Based Qualification of Additively Manufactured Components: Adopting to Oil and Gas Industrial Applications

Recent advances in additive manufacturing (AM) technology provide the potential for on-demand and rapid production of spare parts during urgent repair times. Recently, big oil and gas companies have shown early progress in using additive technology in manufacturing specific heat exchangers, downhole cleanout tool nozzles, offshore risers, gas turbine nozzles, and subsea chemical stick injection tools. Despite the mentioned progress, the current adoption level of additive technology for the offshore oil and gas industry is very limited. Non-destructive and destructive evaluation methods of additively manufactured metallic components have been studied extensively. However, the technique selection procedure and scope of the required test methods have not been studied sufficiently. This paper discusses various elements related to the qualification of additively manufactured components for application in the oil and gas industry. A risk-based qualification method for identifying the scopes of required non-destructive and destructive tests and the resulting qualification procedure for additively manufactured spare components in offshore oil and gas applications is suggested.

Optimization Methods for Redundancy Allocation in Hybrid Structure Large Binary Systems

This paper addresses the issue of optimal redundancy allocation in hybrid structure large binary systems. Two aspects of optimization are considered: (1) maximizing the reliability of the system under the cost constraint, and (2) obtaining the necessary reliability at a minimum cost. The complex binary system considered in this work is composed of many subsystems with redundant structure. To cover most of the cases encountered in practice, the following kinds of redundancy are considered: active redundancy, passive redundancy, hybrid standby redundancy with a hot or warm reserve and possibly other cold ones, triple modular redundancy (TMR) structure with control facilities and cold spare components, static redundancy: triple modular redundancy or 5-modular redundancy (5MR), TMR/Simplex with cold standby redundancy, and TMR/Duplex with cold standby redundancy. A classic evolutionary algorithm highlights the complexity of this optimization problem. To master the complexity of this problem, two fundamentally different optimization methods are proposed: an improved evolutionary algorithm and a zero-one integer programming formulation. To speed up the search process, a lower bound is determined first. The paper highlights the difficulty of these optimization problems for large systems and, based on numerical results, shows the effectiveness of zero-one integer programming.

Simultaneous scheduling of replacement and repair of common components in operating systems

In order for a system to stay operational, its components need maintenance. We consider two stakeholders—a system operator and a maintenance workshop—and a contract governing their joint activities. Components in the operating systems that are to be maintained are sent to the maintenance workshop, which should perform all maintenance activities on time in order to satisfy the contract. The maintained components are then sent back to be used in the operating systems. Our modeling of this system-of-systems includes stocks of damaged and repaired components, the workshop scheduling, and the planning of preventive maintenance for the operating systems. Our modeling is based on a mixed-binary linear optimization (MBLP) model of a preventive maintenance scheduling problem with so-called interval costs over a finite and discretized time horizon. We generalize and extend this model with the flow of components through the workshop, including the stocks of spare components. The resulting scheduling model—a mixed-integer optimization (MILP) model—is then utilized to optimize the main contract in a bi-objective setting: maximizing the availability of repaired (or new) components and minimizing the costs of maintaining the operating systems over the time horizon. We analyze the main contract and briefly discuss a turn-around time contract. Our results concern the effect of our modeling on the levels of the stocks of components over time, in particular minimizing the risk for lack of spare components.

A Bayesian Regularization Approach to Predict the Quality of Injection-Moulded Components by statistical SVM for Online Monitoring system

To evaluate the quality of injection-molded components, conventional approaches are costly, time-consuming, or based on statistical process control characteristics that are not always accurate. Machine learning might be used to categorise components based on their quality. In order to accurately estimate the quality of injection moulded components, this study uses a SVM classifier. In addition, the form of the spare components after the working method product in simulation is classified as "qualified" or "unqualified". The quality indicators have an excellent association with data recordings from the original database of various sensors such as pressure and temperature used in the proposed network model for online prediction. The outliers are removed from the input original data to minimize the deviation of precision or prediction accuracy of the model performance metrics. Data points in the "to-be-confirmed" region (which is in the fit line area) may be misjudged by this statistical SVM model since it is placed between the "qualified" and "unqualified" areas. This statistical procedure in the proposed SVM model also uses Bayesian regularisation to classify final components into distinct quality levels.

An Optimized Complex Fuzzy Hypersoft Set System Based Approach for the Evaluation of Strategic Procurement Techniques for Fuel Cell and Hydrogen Components

While fuel-cell conjunction with hydrogen (FCH) innovation is still in its infancy, the existing market progression towards corporatization is straddled by prevailing research, development, and advancement. The availability of spare components and auxiliary equipment for the FCH process is vital to the component’s improvement. An optimal strategic procurement function can prosper protracted research and recognize the levels of technical understanding to produce high performance and affordably priced modules for a successful transformation. This study presents a multi-attribute decision-making approach based on Entropy (ENT), Similarity Measure (SM), and TOPSIS Approach to evaluate FCH supplier selection strategies. This research examined the novelty of the Complex Fuzzy HyperSoft Set (CFHSS), which may respond to instabilities, ambiguity, and vagueness of facts in knowledge by simultaneously putting into consideration the amplitude and phase terms (P-terms) of complex numbers (C-numbers). The presented structure is the most suitable option for exploring FCH concerns as it allows for a more comprehensive array of membership values, and the periodic nature of the content can be expressed in P-terms to widen the content to a unit circle in a dynamic reference frame through the specification of the Fuzzy Hypersoft Set (FHSS). Secondly, the features in CFHSS may be further sub-divided into attribute values for easier comprehension. The paper also illustrates the apparent connection between FCH and CFHSS SM, ENT, and TOPSIS. These strategies may be used to determine the best approach from a group of possibilities that have a variety of applications in the field of optimization. The recommended methodology’s reliability and effectiveness are examined by evaluating the acquired findings from several prior studies. Some assessments have been done using various parameter values to validate the robustness of the suggested approaches. A scenario-based research project on the FCH modules decision problem is presumed to put the envisaged holistic strategy into action. Ultimately, comparisons are provided to demonstrate the usefulness of the proposed method.

Sortie-based aircraft component demand rate to predict requirements

PurposeForecasting techniques improve supply chain resilience by ensuring that the correct parts are available when required. In addition, accurate forecasts conserve precious resources and money by avoiding new start contracts to produce unforeseen part requests, reducing labor intensive cannibalization actions and ensuring consistent transportation modality streams where changes incur cost. This study explores the effectiveness of the United States Air Force’s current flying hour-based demand forecast by comparing it with a sortie-based demand forecast to predict future spare part needs.Design/methodology/approachThis study employs a correlation analysis to show that demand for reparable parts on certain aircraft has a stronger correlation to the number of sorties flown than the number of flying hours. The effect of using the number of sorties flown instead of flying hours is analyzed by employing sorties in the United States Air Force (USAF)’s current reparable parts forecasting model. A comparative analysis on D200 forecasting error is conducted across F-16 and B-52 fleets.FindingsThis study finds that the USAF could improve its reparable parts forecast, and subsequently part availability, by employing a sortie-based demand rate for particular aircraft such as the F-16. Additionally, our findings indicate that forecasts for reparable parts on aircraft with low sortie count flying profiles, such as the B-52 fleet, perform better modeling demand as a function of flying hours. Thus, evidence is provided that the Air Force should employ multiple forecasting techniques across its possessed, organically supported aircraft fleets. The improvement of the forecast and subsequent decrease in forecast error will be presented in the Results and Discussion section.Research limitations/implicationsThis study is limited by the data-collection environment, which is only reported on an annual basis and is limited to 14 years of historical data. Furthermore, some observations were not included because significant data entry errors resulted in unusable observations.Originality/valueThere are few studies addressing the time measure of USAF reparable component failures. To the best of the authors’ knowledge, there are no studies that analyze spare component demand as a function of sortie numbers and compare the results of forecasts made on a sortie-based demand signal to the current flying hour-based approach to spare parts forecasting. The sortie-based forecast is a novel methodology and is shown to outperform the current flying hour-based method for some aircraft fleets.

DEVELOPMENT OF METHODS OF RELIABILITY ASSESSMENT FOR TURRET BALL BEARING RING OF A BMP-2 INFANTRY FIGHTING VEHICLE

A large part of BMP-2 Infantry Fighting Vehicles needs to replace turret ball bearing rings. Under realization of replacement of spare parts and components made in Russia with domestic ones, KNVO "Fort" MVO Ministry of Internal Affairs of Ukraine made an experimental batch of balls for turret ball bearing rings of infantry fighting vehicles BMP type. As a result of modernization of a turret ball bearing ring, steel balls were replaced with balls made of composite material.
 A turret ball bearing is a large radial thrust bearing, cages of which are turret races. A stabile lower race is fixed by means of screws to a top of the vehicle‟s hull. Above the fixed race there is a movable upper race to which the turret is bolted.
 A method for assessing the reliability of turret ball bearing rings of military armored vehicles was developed. The results of tests of turret ball bearing rings of BMP-2 infantry fighting vehicle tower are given. The reliability of turret ball bearing rings of armored vehicles was assessed taking into account the damage to the balls. The main types of damage to the balls: non-compliance of balls average diameter and non-compliance of the spherical shape of the ball to the requirements of operating documentation. The impact of the probability of no-failure operation of the balls on the durability of the ball bearing is determined.
 It is necessary to take into account the presence of damage to the balls when determining the durability of the ball bearing. To validate the adequacy of the method, it is necessary to increase the test time of the ball bearing by conducting tests during its operation.

Penerapan Data Mining Association Rule Menggunakan Algoritma FP-Growth Untuk Persediaan Sparepart Pada Bengkel

Many individuals are interested in starting a workshop. By responding to each customer's desires, the workshop company may continue to develop, and so the data mining technique can address this challenge. The FP-Growth algorithm is one of the methods that may be used to determine the stock availability of automotive spare components such as engine oil, spark plugs, oil filters, ac filters, batteries, tires, and so on. This research is divided into four stages: problem identification, data gathering, data processing, and data testing. Based on the results of the testing, AK (Battery), OM (Engine Oil), and BS (Spark plug) received support values of 33% and 80%, respectively. Furthermore, the BN (Ban) and KR (Kampas Bram) values were found with 33% support and 80% confidence. Furthermore, we obtain AK (Battery) and OM (Engine Oil) with 33% support and 80% confidence, and BN (Tires) and OM (Engine Oil) with 33% support and 80% confidence. OM (Engineering Oil), AK (Battery), and BS (Battery Storage) are the abbreviations for the terms OM (Engineering Oil), AK (Battery), and BS (Battery (Spark plug)).

KOMPONEN CADANGAN DALAM SISTEM PERTAHANAN KEAMANAN RAKYAT SEMESTA DI ABAD 21

The dynamics of strategic environmental development have created a complex spectrum of threats, challenges and risks, the development of the strategic environment always brings changes to the complexity of threats and challenges to the defense of the State. Threat predictions that arise at any time can be categorized into three types of threats, namely military threats, nonmilitary threats, and hybrid threats. The establishment of the Reserve Component is considered not including the priority agenda and even shows irregularities in determining the priorities of the security sector reform agenda. If the government has the goal to strengthen the defense sector to be more professional, strong and modern, then the development of the main component, the Indonesian National Army (TNI), should be a priority agenda and need to be put forward by the government. The research will address what is seen as necessary by building universal people's defense and security systems in the face of military, non-military and hybrid threats. Based on the type of research, this research is included in case study research, while based on purpose, this research is a policy reserach, case study research is a study conducted intensively, detailed and in-depth on a particular organization, institution or symptom. Various national development activities carried out by the government to achieve the objectives contained in the Opening of the 1945 Constitution, namely protecting all Indonesians in the Universal People's Defense and Security System (Sishankamrata) are carried out in an integrated and sustainable manner in accordance with the priorities and needs of the country set through short-term and long-term national development programs. Implementation of spare components in support of the universal people's defense system in the 21st century. The reserve component is mandatory to be established in Indonesia as part of Indonesia's defense force, especially in the face of aght that is non-military.

Reliability assessment of the standby system with dependent components by bivariate exponential distributions

In the reliability analysis of systems, all system components are often assumed independent and failure of any component does not depend on any other component. One of the reasons for doing so is that considerations of calculation and elegance typically pull in simplicity. But in real-world applications, there are very complex systems with lots of subsystems and a choice of multiple components that may interact with each other. Therefore, components of the system can be affected by the occurrence of a failure in any of the components. The purpose of this paper is to give an explicit formula for the computation of the reliability of a system with two parallel active components and one spare component. It is assumed that parallel components are dependent and operate simultaneously. Two distributions of Freund’s bivariate exponential and Marshall–Olkin bivariate exponential are used to model dependency between components. The results show that the reliability of the system with Freund’s bivariate exponential distribution has lower reliability. The circumstances that lead to them, namely load-sharing in the case of Freund, results in lower reliability. Finally, a numerical example is solved to evaluate the proposed model and sensitivity analysis is performed on the system reliability function. The obtained results show that because the proposed model is influenced by the dependency, compared to traditional models, it has the characteristic of leading to reduced time to (first) failure for achieving specified reliability.

Predictive maintenance for multi-component systems of repairables with Remaining-Useful-Life prognostics and a limited stock of spare components

Aircraft maintenance is undergoing a paradigm shift towards predictive maintenance, where the use of sensor data and Remaining-Useful-Life prognostics are central. This paper proposes an integrated approach for predictive aircraft maintenance planning for multiple multi-component systems, where the components are repairables. First, model-based Remaining-Useful-Life prognostics are developed. These prognostics are updated over time, as more sensor data become available. Then, a rolling horizon integer linear program is developed for the maintenance planning of multiple multi-component systems. This model integrates the Remaining-Useful-Life prognostics with the management of a limited stock of spare repairable components. The maintenance of the multiple systems is linked through the availability of spare components and shared maintenance time slots. Our approach is illustrated for a fleet of aircraft, each equipped with a Cooling System consisting of four Cooling Units. For an aircraft to be operational, a minimum of two Cooling Units out of the four need to be operational. The maintenance planning results show that our integrated approach reduces the costs with maintenance by 48% relative to a corrective maintenance strategy and by 30% relative to a preventive maintenance strategy. Moreover, using predictive maintenance, components are replaced in anticipation of failure without wasting their useful life. In general, our approach provides a roadmap from Remaining-Useful-Life prognostics to maintenance planning for multiple multi-component systems of repairables with a limited stock of spares.

Analysis of export potential of ukraine in the context of european integration

European integration opens wide opportunities for Ukraine to cooperate with developed European countries, strengthening its position in the international arena. Export potential is the potential ability of a country to export goods or services. Exports of goods and services to EU countries in 2020 were $ 21.9 billion (37.1% of total exports), including exports of goods – $ 18.6 billion, exports of services – $ 3.3 billion. Compared to 2019, exports of goods to EU countries de- creased by $ 2.1 billion (10.3%). The export structure is dominated by agriculture products, the food industry (35%), and the metallurgical complex (16.7%). The greatest exporters of Ukrainian goods were the following EU countries: Poland ($ 3.3 billion or 6.71% of total exports of goods), Germany ($ 2.1 billion or 4.27%), Italy ($ 1.9 billion or 3, 86%), the Netherlands ($ 1.8 billion or 3.66%), Hungary ($ 1.3 billion or 2.64%), Romania ($ 1.1 billion or 2.24%). The analysis of the export potential of Ukraine shows the raw material structure of exports. Integration into the EU market as a raw material supplement is dangerous for the country because it can consolidate technological dependence on developed countries. Increasing the share of goods with a high level of processing increase the stability of export income. Promising areas of exporting activity are science-intensive industries: electronics, production of automation, technical means for non-traditional types of energy, new types of materials, biotechnology, etc. To transition Ukraine to the exporting of knowledge-intensive innovative products and successfully enter world markets, the Export Strategy of Ukraine (Roadmap for Strategic Trade Development) has been developed, which identifies the following promising sectors: information and communication technologies, software development, creative services, tourism, maintenance and repair of aircraft, production of spare parts and components for the aerospace and aviation industries, mechanical engineering, food industry. Sectors are grouped into clusters. An individual sectoral strategy is developed for each sector. Key words: export, export potential, European integration, goods, competitive advantages, market, sector.

Исследование качества семян укропа Anethum graveolens L сортов Грибовский и Лесногородский методом термического анализа

The paper presents data on the study of the chemical composition of dill (Anethum graveolens L) using foliar treatment of vegetative plants with the growth-regulating agent Nicosulfuron [2-(4,6-dimethoxypyrimidin-2-ylcarbomoyl-sulfamoyl) -N,N-dimethylnicotinamide]. Field experiments were carried out at the agrobiological station of the Humanitarian and Technological University of the city of Orekhovo-Zuevo, Moscow Region in 2016-2018. The soil of the experimental plots is sod-podzolic medium loamy. Plants were treated with a solution of Nicosulfuron with a concentration of 0.1 g/l according to the active substance. It was found that foliar treatment of vegetative plants with a solution of 2-(4,6-dimethoxypyrimidin-2-ylcarbomoyl-sulfamoyl)-N,N-dimethylnico-tinamide led to a change in the concentrations of macrocomponents in the seeds of dill varieties Gribovsky and Lesnogorodsky. Differential thermal analysis of DTA) of dill seeds was carried out using a thermoanalytical complex based on a derivatograph. The sample heating rate in a platinum crucible was 5, 10, and 20 degrees per minute. The DTA method showed a significant difference in the component composition of the organic matter of seeds of both varieties. 6 organic components can be grouped into two groups – with thermal decomposition temperatures of 200-400 °C and 400-600 °C. The treatment with Nicosulfuron leads to a shift in the accumulation of synthesized spare components of seeds towards easily degradable (up to 400 °C) components. This treatment effect is manifested in the fact that in the total mass of organic components of dill seeds (at the level of 87%), the fraction of readily decomposable organic matter is 64-70% for both varieties. In the control variant, without treatment with the drug, the biosynthesis of hardly degradable components, probably having a high molecular weight, and for high-molecular compounds having a high degree of polymerization, occurs. At the same time, the total activation energy for organic compounds in the control is 30-40% higher compared to the samples that were treated with Nicosulfuron.