Maintenance Procedures Research Articles

Pioneering Maintenance Strategies for Enhanced Reliability of Low Voltage Switchboards

This study highlights the critical need for rigorous maintenance protocols, focusing on routine inspections, preventative measures, and timely corrective actions. Low voltage switch panels (PHB-TR) are vital for ensuring the efficiency and reliability of electricity distribution systems. Through systematic analysis of existing maintenance procedures and field evaluations across diverse setups, the research confirms that structured maintenance not only mitigates the risk of failures but also significantly reduces workplace accidents. The findings advocate for strict adherence to standard operating procedures and improved coordination among technicians, suggesting these strategies as global standards for enhancing the safety and functionality of electrical distribution networks. Highlights: Proper maintenance ensures optimal performance and reduces the risk of system failure. Adherence to applicable SOPs is crucial to prevent work accidents. Coordination and adherence to job distribution streamline work execution. Keywords: PHB-TR Maintenance, Split Switch Panel Maintenance, Low Voltage Split Switch Board

A Digital Twin Development Framework for an Electrical Submersible Pump (ESP)

Premature failure of a sub-system can be critical for an industrial Cyber-Physical System (CPS). A digital twin (DT) assisted predictive maintenance procedure can reduce the risk of costly unplanned maintenance. This study presents a generalized DT development framework for an Electrical Submersible Pump (ESP) that can assist in predictive maintenance. The framework is applied on a single-phase ESP as a proof of concept. The maximum winding temperature of the selected ESP is simulated using a multiphysics simulation tool with transient electromagnetic and transient heat transfer solvers. The simulation parameters were refined using data captured through an ESP free-run experiment. Simulating the total energy loss in the ESP stator and rotor and the transfer of heat from the outer fluid domain facilitates a relationship between the measurable external temperature and the maximum temperature in the stator winding. Following a design of experiments (DOE) approach, a series of simulations were run to establish a statistical model for the winding temperature in terms of the fluid temperature, the time duration a particular temperature was persistent, and the initial maximum stator winding temperature. As the instantaneous maximum stator winding temperature is related to the remaining useful lifetime, it was shown using a case study that the proposed framework can prognosticate the ESP failure, assisting effective decision-making for predictive maintenance of a CPS.

Choice modelling of eCooking adoption by households in Ghana

ABSTRACT The use of electric cooking appliances, also referred to as eCooking devices, presents a practical and sustainable solution for achieving universal access to clean cooking facilities by 2030. A choice modelling analysis on the factors that influence the selection of an eCooker in Ghana has been conducted to facilitate market expansion for organisations seeking to offer clean cooking services. The study utilised Analytical Hierarchy Process (AHP), Fuzzy-TOPSIS, and Data Envelopment Analysis (DEA) methodologies to assess and rank electric cookers based on crucial factors such as kWh consumption rate, cooking efficiency, affordability, time-saving features, ergonomics, space utilisation capabilities, compatibility with cookware types, ease of cleaning and maintenance procedures, accessibility, among others. The rate of consumption was identified as the most critical factor, emphasising the significance of energy efficiency in the decision-making process. The analysis showed that the induction stove was optimal, considering both Fuzzy-TOPSIS and DEA evaluations. Although the induction stove may consume a considerable amount of electricity, its efficiency, performance, and other attributes make it the preferred choice. This study presents a systematic approach to assessing and ranking electric cooking stoves in Ghana, offering valuable insights for both consumers and policymakers.

The Effects of Different Nitrogenous Fertilizer Sources and Doses on Football Field Grass Performances

Nitrogen has a huge importance in terms of ensuring the development of roots and shoots in grass and giving plants resistance to diseases. Using the right fertilizer in appropriate doses in the maintenance and repair of football fields is one of the maintenance procedures that increase grass performance. This study was carried out on the football field grass established at Iğdır University Sehit Bulent Yurtseven Campus during the 2020 vegetation period in Iğdır conditions. The research aimed to determine the most suitable fertilizer type and dose for football fields. The experiment was designed with three replications according to the randomized blocks factorial trial design. In the application area, a grass mixture of Festuca arundinacea Jaguar 4G 30%, Festuca arundinacea Apache 20%, Festuca arundinacea Arid III 20%, Lolium perenne Belida 15% and Lolium perenne Esquire 15% was used. As nitrogenous fertilizer sources, 20-10-10 7SO3, 15-5-20 + 2 CaO + MgO, ammonium sulfate (21% N) and urea (46% N) fertilizers are 0, 2, 4, 6 and 8 g/m 2/ It was administered in monthly doses. In the study, the effects of nitrogen use in fertilization on grass plant height, quality, fresh grass amount, and leaf green tone and leaf texture were observed. As a result of the study, it was determined that the most ideal fertilizer type and dose were 6 and 8 g m-2 doses of urea and ammonium sulfate fertilizers.

An Internet-of-Things-Based Dynamic Scheduling Optimization Method for Unreliable Flexible Manufacturing Systems under Complex Operational Conditions

The dynamic scheduling problem (DSP) in unreliable flexible manufacturing systems (UFMSs) with concurrency, conflicts, resource sharing, and sequential operations is a complex optimization problem that requires the use of efficient solution methodologies. The effectiveness of scheduling UFMSs relies on the quality of equipment maintenance. Currently, UFMSs with consistently large queues of parts awaiting service employ a repair-after-failure approach as a standard maintenance procedure. This method may require unexpected resources, incur costs, consume time, and potentially disrupt the operations of other UFMSs, either partially or fully. This study suggests using a predictive maintenance (PdM) strategy that utilizes the Internet of Things (IoT) to predict and avoid early mechanical equipment failures before they happen in UFMSs, thereby reducing unplanned downtime and enhancing reliability. Therefore, the objective of this paper is to construct timed Petri net (TPN) models using the IoT for the PdM configuration of mechanical equipment in the dynamic scheduling problem of UFMSs. This necessitates that users represent the specific problem using TPNs. The process of PN modeling requires the utilization of domain knowledge pertaining to the target problems as well as to machine information. However, it is important to note that the modeling rules for PNs are straightforward and limited in number. Consequently, the TPN model is applied to generate and formulate mixed-integer linear programming (MILP) instances accurately. This is done to identify the optimal production cycle time, which may be implemented in real-life scenarios. Several UFMS instances are used to demonstrate the applications and effectiveness of the proposed method. The computational results demonstrate that the proposed method shows superior solution quality, effectively solves instances for a total of 10 parts and 6 machines, and achieves a solution in a reasonable CPU time.

Interactive simulations as a tool for logistics and maintenance of IFMIF-DONES

Pre-configured virtual reality (VR) simulations of the logistics and maintenance processes have proven to be useful for identifying potential design issues as well as planning operations during an early design phase of facility. But VR simulations can also be used to deeply explore the feasibility of these procedures in a more interactive manner, so that we can identify potential risks and difficulty levels from early stages and study different maintenance strategies to assist the maintenance worker during these procedures. This article presents a framework to design and validate logistics and maintenance procedures in complex facilities, such as the International Fusion Materials Irradiation Facility DEMO Oriented Neutron Source (IFMIF-DONES). Our framework begins with a preparatory phase where essential information about the procedures and Computer-Aided Design (CAD) models is compiled into a comprehensive Virtualization Task Document (VTD). Differently from previous work, this VTD allows representation of parallel tasks. We implement the interactive version of the virtual environment, where the different maintenance and logistics equipment, as well as a virtual maintenance worker is controlled by the user (the person executing the interactive simulation). We have validated this interactive framework with two simulations for the installation process of the Superconducting Radio Frequency Linear accelerator (SRF Linac) modules in IFMIF-DONES. In one simulation (the automatic one), the procedures are reproduced as they are planned, while in the second simulation (the interactive one) the user freely controls the movements of the moving parts of the crane, grab and release plant equipment, move platforms, etc. Based on our simulations, the interactive version allows easier detection of potential points of collisions as well as more precise assessment of the difficulty of the tasks to be performed.

Preliminary Nose Landing Gear Digital Twin for Damage Detection

An increase in aircraft availability and readiness is one of the most desired characteristics of aircraft fleets. Unforeseen failures cause additional expenses and are particularly critical when thinking about combat jets and Unmanned Aerial Vehicles (UAVs). For instance, these systems are used under extreme conditions, and there can be situations where standard maintenance procedures are impractical or unfeasible. Thus, it is important to develop a Health and Usage Monitoring System (HUMS) that relies on diagnostic and prognostic algorithms to minimise maintenance downtime, improve safety and availability, and reduce maintenance costs. In particular, within the realm of aircraft structures, landing gear emerges as one of the most intricate systems, comprising several elements, such as actuators, shock absorbers, and structural components. Therefore, this work aims to develop a preliminary digital twin of a nose landing gear and implement diagnostic algorithms within the framework of the Health and Usage Monitoring System (HUMS). In this context, a digital twin can be used to build a database of signals acquired under healthy and faulty conditions on which damage detection algorithms can be implemented and tested. In particular, two algorithms have been implemented: the first is based on the Root-Mean-Square Error (RMSE), while the second relies on the Mahalanobis distance (MD). The algorithms were tested for three nose landing gear subsystems, namely, the steering system, the retraction/extraction system, and the oleo-pneumatic shock absorber. A comparison is made between the two algorithms using the ROC curve and accuracy, assuming equal weight for missed detections and false alarms. The algorithm that uses the Mahalanobis distance demonstrated superior performance, with a lower false alarm rate and higher accuracy compared to the other algorithm.

Fault detection in wind turbines: a supervised learning approach with multilayer perceptron neural network

The expansion of energies aligning with sustainable development requirements is continually progressing. A particular focus on wind turbines (WT), characterized as a highly intricate system, has brought attention to the costs associated with operation and maintenance. This has prompted a quest for increasingly efficient maintenance procedures. This article proposes that deviations from expected behavior be detected and classified as failure using operational data from permanent magnet direct drive wind turbines, obtained through the supervisory control and data acquisition system. To achieve real-time fault detection and gather information on the state of faults, the CFS subset evaluator method was employed to extract the most relevant attributes from the dataset. Experimental results demonstrate that the strategy of selecting the most pertinent attributes for the Multilayer Perceptron algorithm (MLP), comprising four layers, in fault classification, resulted in a high recognition rate for detecting and classifying faults in wind turbines. Computational results validating the models are presented.

LITEC: An experimental facility for the validation of the IFMIF-DONES Impurity Control System

The Impurity Control System (ICS) of IFMIF-DONES is devoted to assuring lithium purity. After its circulation through the target, some undesired products will contaminate the lithium: deuterium, hydrogen, tritium, and beryllium. In addition, due to the high velocity of the flowing lithium, the target assembly, piping system, and other auxiliaries are subjected to a significant corrosion rate, thus leading also to the presence of metallic impurities in the liquid lithium (iron, nickel, molybdenum…). Finally, nitrogen, oxygen, and carbon will also be present.These impurities may compromise the operation of the facility: they may enhance the erosion/corrosion effect, shortening the operational life of equipment; they may be activated having an important impact on safety strategy, maintenance, and operational procedures; finally, the erosion caused to the target nozzle may produce fluid perturbations affecting to different aspects: fluid-dynamics, cavitation, and thermo-mechanics.The ICS extracts a fraction of the liquid from the DONES main lithium loop to be purified in dedicated traps, to maintain impurities below permissible levels to achieve the required safety and operational conditions.The validation of the ICS at a relevant circuit size will be performed in a new experimental facility called LITEC (The LIthium TEchnologies CIEMAT loop). It consists of a forced circulation lithium circuit. An electromagnetic pump provides a wide operational range for testing all the purification systems envisioned in the ICS. It has four test sections, where trap prototypes will be installed. An injection system also foresees the possibility of introducing impurities to simulate realistic IFMIF-DONES conditions. Finally, a specific branch will monitor online and offline the impurities.LITEC will contribute significantly to clarifying key aspects of the design and operation of IFMIF-DONES lithium systems and will be a reference facility for research activities in lithium technologies. In this work, its engineering design, operational parameters, and characteristics are presented.

Aligning disaster recovery to company technical direction and objectives

One of the many concerns of disaster recovery specialists is how to create disaster recovery scenarios, strategies and related solutions that meet the vision of management while building solutions for the critical business process within budget, with refined technical resources and operational and maintenance processes and procedures similar to those utilised in production. Rather than consider disaster recovery as a separate environment from production, this paper suggests that there are areas where the disaster recovery solution can map more closely to production solutions to better manifest the critical business process, avoiding the decreased sales forecasts and reputational impacts resulting from an outage. There is no magic here — just ideas for designing a solution and enhancements to the disaster recovery programme that may help to meet business expectations. A disaster recovery site based on similar production technical solutions and overall corporate IT vision can provide such benefits as: faster recovery time objective; faster availability of the data while maintaining data integrity; fewer manual procedures during switch/failover; ability to utilise similar resources to work both environments resulting in a smaller training programme; similar operational and maintenance processes and procedures; ability to switchover components rather than declaring disaster recovery; and an environment that supports production by running critical business process while production suffers an outage or requires maintenance. This paper provides readers with ideas to take back to their disaster recovery solution and how it manifests the critical business process during an outage.

Data-Driven Models Applied to Predictive and Prescriptive Maintenance of Wind Turbine: A Systematic Review of Approaches Based on Failure Detection, Diagnosis, and Prognosis

Wind energy has achieved a leading position among renewable energies. The global installed capacity in 2022 was 906 GW of power, with a growth of 8.4% compared to the same period in the previous year. The forecast is that the barrier of 1,000,000 MW of installed wind capacity in the world will be exceeded in July 2023, according to data from the World Association of Wind Energy. In order to support the expected growth in the wind sector, maintenance strategies for wind turbines must provide the reliability and availability necessary to achieve these goals. The usual maintenance procedures may present difficulties in keeping up with the expansion of this energy source. The objective of this work was to carry out a systematic review of the literature focused on research on the predictive and prescriptive maintenance of wind turbines based on the implementation of data-oriented models with the use of artificial intelligence tools. Deep machine learning models involving the detection, diagnosis, and prognosis of failures in this equipment were addressed.

A Method for Unseen Object Six Degrees of Freedom Pose Estimation Based on Segment Anything Model and Hybrid Distance Optimization

Six degrees of freedom pose estimation technology constitutes the cornerstone for precise robotic control and similar tasks. Addressing the limitations of current 6-DoF pose estimation methods in handling object occlusions and unknown objects, we have developed a novel two-stage 6-DoF pose estimation method that integrates RGB-D data with CAD models. Initially, targeting high-quality zero-shot object instance segmentation tasks, we innovated the CAE-SAM model based on the SAM framework. In addressing the SAM model’s boundary blur, mask voids, and over-segmentation issues, this paper introduces innovative strategies such as local spatial-feature-enhancement modules, global context markers, and a bounding box generator. Subsequently, we proposed a registration method optimized through a hybrid distance metric to diminish the dependency of point cloud registration algorithms on sensitive hyperparameters. Experimental results on the HQSeg-44K dataset substantiate the notable improvements in instance segmentation accuracy and robustness rendered by the CAE-SAM model. Moreover, the efficacy of this two-stage method is further corroborated using a 6-DoF pose dataset of workpieces constructed with CloudCompare and RealSense. For unseen targets, the ADD metric achieved 2.973 mm, and the ADD-S metric reached 1.472 mm. This paper significantly enhances pose estimation performance and streamlines the algorithm’s deployment and maintenance procedures.

Integrated Voltage Vector–Based SVPWM for Reliability and Performance Enhancement of Five-Level HANPC Inverters

Power converters are designed to operate over a wide range of voltages to meet various industrial demands. Recently, multilevel inverters have been receiving considerable attention owing to their ability to reduce the current ripple and its associated harmonic distortion. However, for applications requiring high voltage/power ratings, large electrolytic capacitors are essential, which are significantly affected by the ripple in the DC-link current. This causes a significant reduction in the lifespan and reliability of the power converter and necessitates expensive diagnosis and maintenance procedures. Therefore, an effective method of integrated voltage vector-based space vector pulse-width modulation is proposed in this study for minimizing the ripple in the DC-link and common-mode voltage of five-level hybrid active neutral-point-clamped (5L-HANPC) inverters. The proposed method uses a unique control algorithm that can smoothly select the required voltage vectors without a noticeable distortion in the output current waveforms. Moreover, the proposed method can be applied without modifying the original topology of the 5L-HANPC inverter or adding complex compensations to the control algorithm. Extensive simulation and experimental results are provided to demonstrate the capability of the proposed approach to reduce the DC-link current ripple over a wide range of modulation indices.

Development of standardized nursing terminology for the process documentation of patients with chronic kidney disease.

European Nursing care Pathways (ENP) is a professional care language that utilizes software to map care processes and utilize the data for research purposes, process control, and personnel requirement calculations. However, there is a lack of internationally developed terminology systems and subset specifically designed for the nutritional management of CKD. The aim of this study was to create a subset of the standardized nursing terminology for nutrition management in patients with chronic kidney disease (CKD). According to the guidelines for subset development, four research steps were carried out: (i) Translation of version 3.2 of the ENP (chapter on kidney diseases) and understanding of the framework structure and coding rules of the ENP; (ii) Identification of relevant six-dimensional nursing terms; (iii) Creation of a framework for the subset; (iv) Review and validation by experts. A subset for CKD nutritional care was created as part of this project, comprising 630 terms, with 17 causal relationships related to nursing diagnoses, 115 symptoms, 31 causes, 34 goals/outcomes, 420 intervention specifications and 13 resources, including newly developed care terms. All terms within the subset have been created using a six-step maintenance procedure and a clinical standard pathway for nutrition management in the SAPIM mode. This terminology subset can facilitate standardized care reports in CKD nutrition management, which is used to standardize nursing practice, quantify nursing, services, guidance on care decisions, promoting the exchange and use of CKD nutrition data and serve as a reference for the creation of standardized subset of nursing terminology in China.

Analisis Keandalan Main Battery Peshawar CRJ-1000 Di Maskapai Garuda Indonesia

The main battery on the CRJ-1000 aircraft is an important component in the aircraft's electrical system. The main battery functions as the main source of electric power when the aircraft is turned off or when the aircraft engine is not operating. If there is a failure in the aircraft's battery it can cause disruption to other systems so that the aircraft cannot fly or Aircraft on Ground (AOG). In Garuda Indonesia's CRJ-1000 aircraft battery, there were several findings where the battery failed before reaching the scheduled removal time. This study aims to analyze the reliability of the CRJ-1000 main battery on the Garuda Indonesia airline. The analytical method is carried out by collecting historical data on main battery failures and calculating the Mean Time Between Failure (MTBF) and Availability values for a certain period. In addition, an analysis was also carried out on maintenance procedures and replacement of the main battery carried out by Garuda Indonesia airline technicians. The results of the analysis show that the MTBF of the CRJ-1000 main battery on Garuda Indonesia airlines has a fairly good value, but there is a need for improvement in maintenance procedures and replacement of the main battery to increase availability. The recommendations proposed are evaluating the main battery maintenance and replacement procedures, as well as increasing the availability of main battery spare parts which can speed up repair times in failure situations.

Age Estimation of Transmission Line Using Statistical Health Index and Failure Probability Curve-Fitting Method

The aging process of transmission lines has a direct impact on the reliability and safety of the power grid. Therefore, an accurate age estimation method is imperative for effective maintenance planning and infrastructure investment. This paper introduces a systematic methodology for estimating the age of overhead transmission lines, utilizing the percentage statistical health index (%SHI) and the failure probability curve-fitting (FPCF) method. The %SHI, employing a scoring and weighting approach derived from test results and inspections, is used to assess the actual condition of transmission line equipment. Additionally, the FPCF approach is applied to illustrate the connection between the SHI and the likelihood of failure, facilitating the assessment of transmission line age by fitting failure probability curves to the SHI data. This age is directly associated with the probability of experiencing a failure. The evaluation was conducted on 924 towers situated along four transmission lines connecting the 115 kV substations S1–S2, S3–S4, S5–S6, and S7–S8. These transmission lines are in four regions with diverse terrain and environments such as mountains, rice fields, and more. In the SHI calculation, practical testing results and historical failure data were applied. The results clearly indicate that there were notable disparities in the age estimations for transmission lines in diverse geographical regions of Thailand when compared to their actual ages. These discrepancies can be attributed to various factors, including the local environment, such as rainfall, flooding, and salt-laden air as well as specific geographical features like mountainous and coastal terrain. To mitigate the deterioration of transmission lines in all regions, it is essential to implement a proactive maintenance strategy. This strategy should involve more frequent inspections, the use of advanced monitoring technologies, and the establishment of robust maintenance procedures, with which it would become possible to enhance the accuracy of equipment condition assessments, ultimately resulting in an overall improvement in the reliability of transmission lines.

Operation and Maintenance in Solar Plants: Eight study cases

The use of solar photovoltaic generation is growing up nowadays. New developments have been achieved lowering the prices of the modules and their installation. Nevertheless, the operation and maintenance of these plants still needs improvements in order to enhance their efficiency and economic balance. This paper presents a detailed analysis of eight photovoltaic (PV) plants revealing improvements on the monitoring system and the maintenance procedures. The common failures in PV plants have been established and their losses have been estimated. A correct diagnostic method using good information and monitoring systems could have reduced the losses.

Move schedules: fast persistence computations in coarse dynamic settings

AbstractMatrix reduction is the standard procedure for computing the persistent homology of a filtered simplicial complex with m simplices. Its output is a particular decomposition of the total boundary matrix, from which the persistence diagrams and generating cycles are derived. Persistence diagrams are known to vary continuously with respect to their input, motivating the study of their computation for time-varying filtered complexes. Computing persistence dynamically can be reduced to maintaining a valid decomposition under adjacent transpositions in the filtration order. Since there are $$O(m^2)$$ O ( m 2 ) such transpositions, this maintenance procedure exhibits limited scalability and is often too fine for many applications. We propose a coarser strategy for maintaining the decomposition over a 1-parameter family of filtrations. By reduction to a particular longest common subsequence problem, we show that the minimal number of decomposition updates d can be found in $$O(m \log \log m)$$ O ( m log log m ) time and O(m) space, and that the corresponding sequence of permutations—which we call a schedule—can be constructed in $$O(d m \log m)$$ O ( d m log m ) time. We also show that, in expectation, the storage needed to employ this strategy is actually sublinear in m. Exploiting this connection, we show experimentally that the decrease in operations to compute diagrams across a family of filtrations is proportional to the difference between the expected quadratic number of states and the proposed sublinear coarsening. Applications to video data, dynamic metric space data, and multiparameter persistence are also presented.

Integrating Building Information Modeling (BIM) for optimal lifecycle management of complex structures

A fundamental issue in the development and engineering industries is the efficient management of complex structures during their entire lifecycles. Traditional fragmented techniques have been used, and this has led to instances of poor communication and subpar performance, particularly in the context of repair and restoration initiatives. Building information modeling (BIM) emerged as a ground-breaking strategy that offers a digital representation of a building's attributes and facilitates effective collaboration among several stakeholders. The current study examines how BIM impacts complex building management throughout the course of a structure's existence. It focuses on how BIM helps to advance maintenance procedures, environmental initiatives, and project effectiveness. Exploratory factor analysis (EFA), structural equation modeling (SEM), and literature research are the three phases of the study's methodology. A thorough investigation was carried out in Pakistan's Rawalpindi and Islamabad region utilizing a quantitative technique. The poll of 159 participants produced intriguing findings. The process of EFA serves to verify constructs and questions, ensuring their reliability and validity. On the other hand, SEM is used to assess the structural relationships between variables and their impact on BIM based lifecycle management. The findings suggest that the application of BIM is favorably influenced by each phase of a project, namely Design, Construction, Operation and Maintenance, Renovation and Retrofitting, and End-of-Life Decisions. This highlights the need to implement a complete BIM strategy across all stages of a project's lifespan, which may enhance facility management, decrease expenses, and promote sustainability. The results of this study have significant consequences for professionals and politicians, highlighting the crucial need to provide incentives and regulations to promote the use of BIM in building projects.

Analyzing the Failure of a Truck's Rear Axle Shaft Requires a Thorough Investigation to Pinpoint the Root Cause of the Issue

The analysis of a failed rear axle shaft from a dumper truck involved a comprehensive investigation to ascertain the underlying cause of the failure. Visual inspection, material analysis, mechanical testing, and fracture analysis were conducted to assess the condition of the axle shaft. The axle shaft exhibited signs of fatigue failure, with the fracture surface showing fatigue striations. Microstructural analysis revealed a coarse grain structure with inclusions, indicating potential material defects. Tensile testing showed that the axle shaft had lower-than-expected mechanical properties, suggesting a possible issue with material quality or heat treatment. Based on the analysis, the root cause of the failure was determined to be a combination of material defects and fatigue loading. Types of investigation like as visual examination, chemical analysis, hardness test, tensile test, fractography and ultrasonic test, and microstructure examination. Microstructure observation of the sample indicates a normal ferrite–pearlite (lower critical point) sorbite-type structure with some spheronization seen on some portions Results indicate that the failure occurred due to a sudden load on the axle shaft, specifically at its weakest point. The shear stresses on the axle shaft were insufficient to withstand the stresses caused by the sudden loading. Based on the analysis, make recommendations for corrective actions to prevent similar failures in the future. This may include design improvements, material changes, maintenance procedures, or operational changes. This may include design improvement, material changes, maintenance procedures, and operational changes. Implement the recommended corrective actions to prevent similar failures in other axle shafts or similar components.