Machine Reliability Research Articles

Error detection through modified phase II process monitoring under different classical estimators

In real life, the distribution of the errors during any life testing of products or process does not meet the assumption of normality. Statistical process control (SPC) is defined as the use of statistical techniques to control a process or production method. SPC tools and procedures can help to monitor process behavior, discover problems in internal systems, and find solutions for production issues. To identify and remove the variation in different reliability processes and to monitor the reliability of machines where the number of errors follows skewed distributions, we develop control charts to keep the process in control. For such situations, we have modified the existing control charts such as Shewhart control chart, exponentially weighted moving average (EWMA), hybrid exponentially weighted moving average (HEWMA) and extended exponentially weighted moving average (EEWMA) control charts. The current study introduced classical estimator based modified control charts for phase-II monitoring by assuming that the errors occur during the process follow skewed distribution called Beta Lehmann 2 Power function distribution (BL2PFD). The proposal for these control charts is based on the percentile estimator. We have compared all these control charts using Monte Carlo simulation studies and real-life applications to compare the proposed control charts. This study shows that an EEWMA control chart based on PE performs better than Shewhart, EWMA and HEWMA control charts, when the underlying distribution of the errors in process monitoring follows BL2PFD. These findings can be useful for researchers and practitioners in dealing with production errors and optimizing the output.

Opportunistic maintenance optimization of continuous process manufacturing systems considering imperfect maintenance with epistemic uncertainty

Due to the production process for continuous process manufacturing system (CPMS) cannot be stopped, the “opportunities” for maintenance can only occur within the specified time intervals. To improve the completion rate of production process, the focus of opportunistic maintenance for CPMS is whether the maintenance is to be performed at known time. Meanwhile, several opportunistic maintenance optimization models assumed imperfect maintenance to develop more reasonable maintenance plan. However, the parameters of imperfect maintenance cannot be accurately assessed (namely epistemic uncertainty) due to inadequate knowledge of maintenance and degradation mechanisms. This epistemic uncertainty was ignored in previous studies. Therefore, a novel opportunistic maintenance optimization model for CPMSs is proposed. The opportunity time window (OTW) concept is introduced to constrain the production-constrained maintenance opportunity. Three types of maintenance actions, including do nothing, perfect maintenance, and imperfect maintenance with epistemic uncertainty, are considered during the OTW to improve the production efficiency and performance of the manufacturing system. In the context of random and epistemic uncertainty, a stochastic fuzzy flow manufacturing network (SFFMN) is established to describe dynamic production processes and evaluate machine reliability. Moreover, a simulated annealing-based adaptive immune algorithm (SAAIA) with multiple immune operators is developed to address the opportunity maintenance optimization model of CPMSs. Finally, a case study of the hot rolling manufacturing system is provided to better understand the proposed method and demonstrate its effectiveness.

Use of iron in oil concentration sensor for continuous monitoring of marine diesel engine technical condition

The article examines the features of the general problem of reliability, accuracy and durability of machines, mechanisms and devices, namely, the issue of friction, lubricating action, wear of the surfaces of parts and working bodies, which exist among themselves in very complex correlational dependencies. An approach to increasing the reliability of a ship's diesel engine is proposed, which requires the development of effective calculation methods and models for predicting the durability and wear resistance of materials of parts in friction nodes at the limit of lubrication in a wide range of changes in operating conditions and taking into account the variable modes of operation of a ship's diesel engine. The article considers the general approach and specific features of the construction of the components of the diagnostic system of the ship's internal combustion engine. Based on the selected volume of tasks solved by the diagnostic system, the sequence of functioning of its elements is determined. The implementation of this algorithm can have a significant effect in the complex use of diagnostic information together with statistical information stored individually for each mechanism, when managing its technical condition. On the basis of the proposed diagnostic model, it is possible to recognize the technical condition of marine diesel engines based on tribomonitoring data, detecting changes in friction conditions and an increase in the rate of wear of parts of the cylinder-piston group. This will enable the initiation of preventive corrective actions aimed at ensuring the reliable and safe operation of marine engines

Enhanced quadratic discriminant analysis with sensor signal fusion for speed-independent fault detection in rotating machines

The predictive maintenance approach in the fault diagnosis of rotating machines is becoming important in industries in order to minimize operational cost and to improve the reliability of machines. Recent studies have focused on developing an effective prediction model to detect machinery faults at various speeds using machine learning techniques. In this research study, machine-learning-based models are developed to detect multi-component faults such as gear faults, bearing faults, and unbalanced shafts, by training the four speed data sets using decision trees, support vector machines and artificial neural networks. The machine learning models are improvised by fusing the vibration signals (X, Y and Z) and sound signals with the feature selection algorithm, minimal redundancy-maximum relevance (mRMR). The research work is extended by training a model with any three speeds and testing the trained model with the remaining speed. The state-of-the-art algorithms used to train all four speeds yield poor performance in the prediction of faults at testing speeds. A linear and quadratic discriminant analysis (QDA) is chosen based on its multivariate discrimination capability for better fault prediction at testing speed. The proposed combination of QDA with mRMR selection of fused vibration and sound feature set perform well in the detection of multiple faults at variable speeds.

Application of XGB-based metaheuristic techniques for prediction time-to-failure of mining machinery

Mining equipment is a critical component in the success of mining operations, and unplanned downtime can be costly. Efficient and intelligent maintenance planning is therefore essential to minimize downtime and maximize productivity. Consecutive time-to-failure (TTF) is an important indicator of machine reliability, and accurate TTF predictions enable effective preventive maintenance planning. Therefore, this study proposes hybrid models of extreme gradient boosting (XGB), optimized by particle swarm optimization (PSO) and gray wolf optimization (GWO), for the prediction of TTF in mining machinery. Additionally, validation of the hybrid model was conducted using support vector regression (SVR) method. Historical data on mining machine failures were collected, and a case study was conducted to investigate shovels in an open-pit mine. The PSO-XGB method was found to be the most accurate predictor of failure time with R2 values of 0.99, RMSE values of 50.66 and 51.77, MAE values of 4.52 and 10.81, and AARE values of 1.15 and 1.24 in the training and testing phases. This research highlights the importance of efficient and intelligent maintenance planning to minimize downtime and optimize productivity in mining operations.

Energy-oriented opportunistic maintenance optimization of continuous process manufacturing systems with two types of stochastic durations

For continuous process manufacturing systems (CPMSs) where the production process cannot be stopped, the “opportunities” for maintenance can only occur within the specified time intervals between two production batches. Moreover, opportunistic maintenance of CPMSs is not only to reduce downtime losses and maintenance costs, but also to improve productivity and energy efficiency. However, existing studies ignored stochastic uncertainties of production batch duration and maintenance duration, which can lead to overestimation of total benefit and reliability, and increase the risk of accidents. Therefore, an energy-oriented opportunistic maintenance (EOM) strategy for CPMSs with stochastic durations is proposed. The stochastic opportunity time window (SOTW) is introduced to characterize the uncertain “opportunity” of maintenance caused by the above-mentioned stochastic uncertainties. And, a stochastic flow manufacturing network (SFMN) is established to evaluate machine reliability and energy consumption under the internal and external uncertainties. Moreover, the optimization objective of EOM that takes into account energy, production and maintenance simultaneously is to maximize the expected system benefits by selecting appropriate maintenance actions during the SOTWs. Then, a genetic algorithm with multiple evolution strategies (GAMES) is developed to address the optimization problem. Finally, a case study is provided to verify the effectiveness of the proposed method.

Research of high-frequency remagnetization model in laminated magnetic cores of electromechanical and electromagnetic energy converters

The object of research in the work is charged magnetic conductors of electric machines and transformers. Laminated magnetic wire together with windings are important active parts of electric machines that participate in electromechanical energy conversion. The reliability of the entire machine is mainly determined by the actual condition of the inter-sheet insulation. Violation of the insulation causes parasitic eddy current circuits, which increases the specific losses, and also significantly affects the additional heating of the magnet wire and winding. The normative method for determining the quality of the charged core is the assessment of specific losses at a frequency of 50 Hz and an induction of 1 T, which should not exceed 2.5–4 W/kg. To determine local damage to the core, methods of local heating and fixation of overheating sites are used, which should not exceed 45 °C compared to the main part of the magnetic core. In the work, a two-dimensional field mathematical model of a charged magnetic circuit is developed. This makes it possible to carry out electromagnetic calculations in a near-real magnetic conductor, taking into account the variability of magnetic permeability, hysteresis, and the interaction of currents in adjacent plates of the magnetic conductor with each other, the so-called "proximity effect". On the basis of the developed models, graphs of current distribution and distribution of magnetic induction in one, two and three sheets were obtained. The resulting graphs show how the effect of current displacement increases with increasing frequency, where at a frequency of 100 kHz the magnetic induction density in the middle of the sheet goes to zero. The results of the research confirm the correctness of the model development in comparison with the classical calculation models also given, which allows them to be used for further research of high-frequency processes in charged magnetic circuits of electric machines

A Binary Black Widow Optimization Algorithm for Addressing the Cell Formation Problem Involving Alternative Routes and Machine Reliability

The Cell Formation Problem (CFP) involves the clustering of machines to enhance productivity and capitalize on various benefits. This study addresses a variant of the problem where alternative routes and machine reliability are included, which we call a Generalized Cell Formation Problem with Machine Reliability (GCFP-MR). This problem is known to be NP-Hard, and finding efficient solutions is of utmost importance. Metaheuristics have been recognized as effective optimization techniques due to their adaptability and ability to generate high-quality solutions in a short time. Since BWO was originally designed for continuous optimization problems, its adaptation involves binarization. Accordingly, our proposal focuses on adapting the Black Widow Optimization (BWO) metaheuristic to tackle GCFP-MR, leading to a new approach named Binary Black Widow Optimization (B-BWO). We compare our proposal in two ways. Firstly, it is benchmarked against a previous Clonal Selection Algorithm approach. Secondly, we evaluate B-BWO with various parameter configurations. The experimental results indicate that the best configuration of parameters includes a population size (Pop) set to 100, and the number of iterations (Maxiter) defined as 75. Procreating Rate (PR) is set at 0.8, Cannibalism Rate (CR) is set at 0.4, and the Mutation Rate (PM) is also set at 0.4. Significantly, the proposed B-BWO outperforms the state-of-the-art literature’s best result, achieving a noteworthy improvement of 1.40%. This finding reveals the efficacy of B-BWO in solving GCFP-MR and its potential to produce superior solutions compared to alternative methods.

PRODUCT QUALITY AS THE BASIS OF COMPETITIVENESS
 OF RUSSIAN ENGINEERING

The low level of competitiveness of domestic equipment significantly reduces consumer demand. This problem can be solved only on the basis of improving the quality level and operational reliability of manufactured machines, which are laid down in the production of equipment. (Research purpose) The research purpose is improving the manufacturing quality and reliability of Russian-made machines and equipment by improving their production and technical service. (Materials and methods) Investigated as initial information and materials the actual data on machines and equipment involved in agricultural production of countries; indicators of the intensity of their use and operational reliability. The following research methods were applied: monographic, comparative assessments, statistical, analysis and synthesis. (Results and discussion) The work is aimed at determining the reasons for the low level of quality of Russian equipment, substantiating the need for innovative development of production systems and technical service of machinery and equipment. It was determined that the basis of the high competitiveness of foreign equipment is the use of a proprietary method of technical service. The expediency of innovative development of the production and technological system and the creation of machine-building firms has been established. Only the company is interested in improving the quality of manufactured equipment, and only the company can organize branded technical service of its products. (Conclusions) The conducted organizational and technological studies have shown that improving the quality of manufacturing and reliability parameters of machinery and equipment based on the developed innovative method of organizing production and technical service will bring Russian engineering to a competitive level and ensure competitiveness and import substitution in technology.

Dimensional Accuracy of 3D Printed Dog-bone Tensile Samples: A Case Study

Three-dimensional (3D) printing technology has revolutionized manufacturing by enabling the rapid production of complex objects. However, ensuring dimensional accuracy in 3D printed parts remains a significant challenge due to various factors, including the selection of appropriate parameters during the Fused Deposition Modeling (FDM) process. Achieving dimensional accuracy is crucial in determining the reliability of a printing machine to produce objects that meet the expected results. This study aims to investigate the influence of FDM parameters (filling percentage and layer thickness) on the final dimensions of 3D printed parts made from polylactic acid (PLA) through a systematic experimental and statistical approach. The goal is to identify the optimal process parameter settings that minimize the error percentage in the dimensions of the printed parts using the Taguchi method. Overall higher dimensional accuracy was obtained, influenced mainly by the layer thickness parameter (in the case of Y direction dimensions) and by the filling percentage (in the case of Z direction dimensions – corresponding to sample thickness). The findings of this study provide valuable insight into identifying the optimal configuration for producing PLA 3D-printed components.

Enhancing Rotary Machine Reliability Through Condition-Based Maintenance Optimization

Rotary machines possess an inherent characteristic of generating vibrations, leading to the deterioration of critical components, particularly bearings and gears, ultimately failing the system. Vibration analysis is widely acknowledged as the predominant diagnostic technique employed for assessing the state of machinery and informing maintenance strategies. Condition-based maintenance (CBM) is a crucial component of proactive maintenance strategies that optimize machine availability by implementing timely interventions and minimizing costly breakdowns. This research endeavour aims to establish a comprehensive framework that enables evaluating the operational state of rotary machinery and its critical components, specifically emphasizing bearings. The interdependence between maintenance and machine health is evident, as a well-maintained machine requires minimal maintenance, while a machine undergoing deterioration requires immediate intervention. Rotary machines, which hold significant importance in various industrial processes, often face significant obstacles to bearing issues. These challenges lead to considerable disruptions in output and escalate maintenance costs. The current study examines the efficacy of CBM as a potential solution to the aforementioned issues. CBM is a maintenance strategy that utilizes real-time data on machine conditions to make informed decisions regarding maintenance interventions. By leveraging this approach, maintenance activities can be executed at the most opportune time, maximizing efficiency and effectiveness. CBM is a strategic approach that empowers enterprises to proactively mitigate failures, optimize maintenance schedules, and improve overall operational efficiency by accurately estimating the remaining usable life of machine components. This research study contributes to the growing body of knowledge on CBM, offering valuable insights into predictive maintenance and its potential to enhance the reliability and efficiency of rotary machinery.

Design of a multilink system for calculating high-frequency processes in electric machines with mesh windings

This study considers the design of a multi-link high-frequency circuit for calculating defective and defect-free insulation of mesh windings in order to increase the operational reliability of general-purpose electric machines. The object of research is mesh windings of electric machines. The problem to be solved: increasing the operational reliability of electric machines with general-purpose mesh windings by analyzing and modeling defects. The research results make it possible to model defects for the analysis of the state of insulation of electric machines with mesh windings. Special attention in the research was paid to induction motors with a worn-out resource, in particular, 4A80A4 UZ engine. The analysis includes phase-to-body capacitance, winding inductance, eddy current impedance, and winding impedance. Under the WN mode, a decrease in the impedance of the winding section from 3 % to the short-circuit mode was simulated; accordingly, the resonance frequencies for each case of 3 % were determined – 73990 Hz, short-circuit – 74450 Hz, as well as the corresponding input impedances 8938.7 and 8082.5. The corresponding voltage resonances and current resonances were also determined. Appropriate results were also given for the WG scheme. The results reported here relate to the design of the scheme and the research on the defects of the mesh winding. This contributes to the analysis of the state of insulation of mesh windings. The numerical data (resonant frequencies and input impedances) allow a better understanding of the behavior of windings in different states and degrees of defects. Given the research findings, it is possible to better identify and analyze potential defects in mesh windings, which in turn contributes to increasing the reliability of electric machines. The results of this study could be used in the field of diagnosis, service, and maintenance of electric machines with mesh windings

Scientific basis of creating hybrid drives to increase the energy efficiency of road construction machines

Problem. Possibilities for improving construction and road machines were explored, an analysis of existing publications was conducted to develop a theory for energy-efficient machine design using hybrid drives for working mechanisms and engines. Comparative tables were provided to show the energy distribution and consumption of different machines during operation. In order to improve fuel efficiency, environmental sustainability, and reliability of machines, a classification of methods for increasing the efficiency of construction and road machines was proposed, taking into account existing and prospective methods. Goal. The objective of the research is to develop a concept for creating energy-efficient construction and road machines with hybrid drives for working mechanisms and engines, which will be based on existing and prospective methods for increasing fuel efficiency, environmental sustainability, and machine reliability. Methodology. The issue of increasing the energy efficiency of machine operation is very important and relevant. This is due to the need to reduce fuel costs and minimize the negative impact on the environment. To achieve this goal, it is necessary to clearly classify the ways of improving the efficiency of basic machine components, including the engine, transmission, braking system, and other components. Results. The prerequisites for developing the concept of energy-efficient construction and road machines have been outlined, including the development of hybrid drives for working tools and engines, taking into account modern and promising methods of increasing fuel efficiency, ecological sustainability, and machine reliability. Practical value. All the improvements mentioned contribute to achieving the nominal power values used to perform useful work and overcome resistive forces, the magnitude of which characterizes the energy intensity of the process and its economic component. Using only a technical criterion is not effective for justifying the limiting values of drive and engine energy consumption, due to the instantaneous and insignificant change of the entire set of indicators depending on the load modes and duration of the working cycle process. Since the efficiency of the hydraulic drive depends on numerous factors and affects the durability of drive elements, the allowable minimum efficiency can be determined by applying economic criteria.

Calibration and Multiple Reliability Assessments of a Scrum Machine Instrumented to Measure Force

Coaches need reliable methods of quantifying rugby union scrum force performance in order to make data-driven decisions. The purpose of this study is to present the reliability of a replicable instrumented scrum machine. We performed 3 phases of deadweight calibration on 8 S-type load cells; during deadweight calibration, each load cell was loaded with ~20–200 kg. Phase 1 compared power sources (wall outlet vs. portable power station). Phase 2 tested the inter-session reliability of the load cells after 15, 30, 45, 60, and 420 min of run time. Phase 3 tested between-session reliability, comparing days 0, 1, 7, and 180. We also performed a phase of inter-trial reliability when humans pushed on the fully instrumented scrum machine. Fourteen collegiate rugby players performed four warm-up trials and then five 100%-effort trials; peak and average voltage during the push were compared between the 100%-effort trials. For all phases, statistical analyses show near-perfect reliability. Therefore, we conclude that our novel instrumented scrum machine is ready for in vivo data collection; other coaches or researchers could duplicate our methods to create their own reliable instrumented scrum machine.

Fractional-order mathematical model of single-mass rotor dynamics and stability

Ensuring the vibration reliability of rotary machines is based on the reliable mathematical model of rotor movement. Considering the critical factors leading to a stability loss is an important problem in up-to-date machinery. However, the presence of fractional-order hydrodynamic features of gap seals and the effect of anomalous energy dissipation lead to a need to clarify existing rotordynamic models by considering the fractional-order terms. Therefore, this article deals with the comprehensive modeling approach to study forced oscillations of a single-mass rotor and check its dynamic stability considering the fractional-order origin of the damping force. Moreover, the impact of fractional order on the damping factor and dynamic stability of whirl movement considering the circulation force in gap seals, is still not fully explored. This problem adds particular importance to the presented research. As a result, a single-mass flexible rotor model was extended by considering the fractional-order damping force. Moreover, based on the discovered asymptotic property of the Mittag-Leffler function, the impact of fractional order on the amplitude-frequency response was also determined. Finally, boundaries for dynamic stability loss were identified considering the fractional-order damping force. Overall, the study allowed the development and substantiation of a more generalized scientific and methodological approach to ensuring the vibration reliability of rotary machines.

Production Facilities Safety Assessment According to the Maximum Values of Machines Reliability

Introduction. At the stage of designing technical devices and performing appropriate strength calculations of metal structures, sufficiently large reserves of strength are taken, which, theoretically, exclude any failures of parts. In fact, the machines work with frequent failures. Of interest are undiagnosed failures that lead to a critical decrease in safety, especially at hazardous production facilities. It is assumed that the previously applied approaches of selective determination of the maximum (minimum) reliability value, based on point estimates of the distribution parameters of the two-parameter Weibull law, lead to an overestimation of the calculated indicators of the probability of failure-free operation, i.e. underestimation of risk. Therefore, the work objective is to consider an approach to assessing the risk of operating production facilities in a situation of accidental occurrence of dangerous and undiagnosed failures in systems.Materials and Methods. Methods for technical devices safety assessment based on probability theory were used in the work, and the probability of machine failure was determined based on the well-known method of reliability theory. This method consists in calculating and constructing distribution functions of random variables (load-bearing capacity and loading) that influence the occurrence of failure. The level of increase in the reliability index was determined, leading to frequent unpredictable failures of technical devices (machines) and a decrease in the safety of their operation.Results. The signs of inconsistency of strength calculations based on overestimated safety margins, which in theory exclude failures of parts and machines in general, are identified and substantiated. A new approach to risk assessment of operating production facilities in a situation of accidental occurrence of dangerous and undiagnosed failures by safety systems has been developed and implemented. An algorithm for determining the three parameters of Weibull's law for a population based on sample data has been developed. The resource distribution densities of the boom of the single-bucket excavator EK-14 are constructed. The recommendations are given to increase the probability of failure-free operation to 0.9989.Discussion and Conclusion. The results of the conducted research allow us to substantiate a new approach to risk assessment of operating production facilities in the event of dangerous and undiagnosed failures of basic parts by safety systems, leading to negative consequences.

A Situational Based Reliability Indices Estimation of ULT Freezer using Preventive Maintenance under Fuzzy Environment

Reliability of high demand machines is quite necessary and it can be maintained through proper and timely maintenance, Ultra-low temperature (ULT) freezer is one of those kinds of machines which are in high demand during covid-19 pandemic for the storage of vaccine. The rapid production of vaccines for the prevention of coronavirus disease 2019 (COVID-19) is a worldwide requirement. Now the next challenge is to store the vaccine in a ULT freezer. It’s become really a big problem to store the vaccine which creates the demand of ULT freezer. The present paper investigates a situational based performance of the ULT freezer with the aim to predict the impact of different component failures as well as human errors on the final performance of the same. For the study, it is not possible to extract the parameters (failure rate and repair time) of the components that never failed before. Thus, to overcome this difficulty, here authors use the possibility theory. Authors present the available data in Right triangular fuzzy number with some tolerance as suggested by system analyst. The lambda-tau methodology and arithmetic operations on right triangular generalized fuzzy numbers (RTrFN) are used to find the various performance parameters namely MTTF, MTTR, MTBF, reliability, availability, maintainability (RAM) and ENOF, under fuzzy environment. The proposed model has been studied using possibility theory under working conditions, preventive maintenance as well as under the rest of conditions. This study reveals the most and least critical component of the ULT freezer which helps maintenance department to plan the maintenance strategy accordingly.

Thermionic coating method with preliminary bombardment of the substrate surface with a stream of low energy ions

Relevance. Vacuum-plasma methods of applying functional coatings are widely used to increase the reliability and durability of machine and mechanism parts, cutting tools, and technological equipment, as well as in modern micro- and nanoelectronics for applying conductive and dielectric layers of various thicknesses. The study presents a method of thermionic coating that combines in one technological cycle the processes of surface cleaning by a stream of low-energy ions and plasma electron beam evaporation of a substance under conditions of thermionic plasma formation. Aim. The research aims to determine the possibility of using the presented methodology to create and process functional coatings without radiation damage to the substrate surface. Methodology. The experimental studies were carried out in a plasma electron beam system with a primary plasma source based on an arc discharge with a filament cathode. The samples were diagnosed using a scanning electron microscope. Results. The ion current density from the primary plasma was investigated to determine the efficiency of the surface cleaning mechanism by ion bombardment. The dependences of the ionic current density on the initial parameters of the experiment were determined. The results of the treatment of the (TiZr/TiSi) N sample surface with a plasma ion stream are presented. The obtained scanning electron microscope images showed that such treatment leads to the cleaning of the surface layer from various contaminants without damage and creates a substrate for further thermionic deposition of a coating with a high degree of adhesion. The mechanism of thermionic deposition of a titanium monolayer on a stainless-steel substrate previously cleaned by ion bombardment was studied. The revealed order of magnitude higher values of the ionic current to the substrate during the formation of thermionic plasma indicate a significant increase in the rate of the deposition process and contribute to the formation of a high-quality ion-plasma coating. Conclusions. The scanning electron microscope images of the sample surface showed that the titanium coating during thermionic deposition was uniformly distributed over the substrate surface, without any droplet phase, which indicates the suitability of this technique for applying functional coatings without radiation damage to the substrate surface

Strategi Perawatan Mesin Di Line Sabroe Menggunakan Metode RCM Dan MVSM Di PT XYZ

This study aims to analyze the RCM (Reliability Centered Maintenance) and MVSM (Maintenance Value Stream Mapping) strategies implemented by PT. XYZ in machine maintenance at the Sabroe Line. RCM is used to reduce equipment failures and ensure that each physical item or system is functioning as intended. Meanwhile, MVSM is used to identify waste in maintenance activities and perform repair analysis. The research method used is qualitative research with a case study approach. Data was collected through observation, interviews and analysis of related documents. The results of the research show that PT. XYZ has implemented the RCM and MVSM strategies effectively in engine maintenance at the Sabroe Line. RCM implementation helps to reduce machine failure and increase machine reliability. Meanwhile, MVSM helps identify and overcome waste in maintenance activities. In conclusion, the RCM and MVSM strategies are effective approaches in engine maintenance at the Sabroe Line. This research provides a better understanding of the importance of a planned and structured maintenance strategy in improving engine performance. The recommendation for future research is to involve more departments and measure the impact of RCM and MVSM strategies on overall operational productivity and efficiency.

Improving the Operational Reliability of Agricultural Machines

The results of a study of a new design of the joint, which provides an increase in the strength and durability of the bearing joints of the parts of the working bodies of agricultural machines, are presented. In the case of installation of the bolts of the proposed design in the part to which the nut is adjacent, with a slight interference, a rigid sealing of the bolt shaft is guaranteed and bending stresses are excluded in the sections that are directly located at the thread and in the thread itself.