Failure Of Critical Components Research Articles

Corrosion characterization of engine connecting rods using fringe projection profilometry and unsupervised machine learning

The consequences associated with corrosion, a global industrial peril, cost an estimated $ 2.5 trillion annually to inspect, rectify, and prevent. In addition to significant economic losses, corrosion-induced failure of critical components in transport systems, like automobiles, may also lead to loss of human life. Hence, it is essential to eradicate corrosion in its early stages. The most vital automobile component is its engine, whose failure can cause fatal accidents. Regular quality inspection and maintenance by skilled personnel is essential to prevent this. Automating this task will address this domain’s personnel shortage while mitigating the risk of human error. To enable the performance of this task without the need for human intervention, we determine the morphological parameters affected by corrosion in automotive engine components, namely connecting rods, using fringe projection profilometry, a high-speed 3D profiling technique capable of achieving sub-millimeter accuracy. We then perform classification using k-means clustering into low, medium, and high corrosion bands, based on the parameters obtained from 3D imaging. The model was able to achieve a high accuracy of 88.57%. The accuracy was determined by considering the visual classification performed by a Material Science Expert as the ground truth.

On the coupled dynamics of vertical cladding panels and industrial frame structures subject to out-of-plane seismic loading

Industrial facilities typically consist in large-span single-storey prefabricated buildings having a rectangular floor space. Frame structures made with either steel, timber or precast concrete members are mostly employed to support the roof, while cladding panels create the building enclosure. Their interaction with the frame typically plays a relevant role in the overall building dynamics, potentially leading under seismic excitation to both local and global collapses. Experience shows that a critical component failure is that of the panel-frame connection. Current design approaches classify the panels as “non-structural members” and the forces at the connections induced by the out-of-plane seismic loading are evaluated with approximate expressions. Neglecting the dynamic interaction between the panel and the frame, however, may lead to an oversimplified description of the mechanical problem and inaccurate estimates of the forces at the connections. To overcome these drawbacks, in this work a different approach is pursued in which the interaction between the fundamental sway mode of the frame and the out-of-plane motion of the cladding panel is studied within a rigorous mechanical setting. The focus is on the very frequent case of vertical cladding panels, supported at the ground and retained out-of-plane by the frame. Starting from the development of the equations of motion for the coupled frame-panel structure, a minimal set of parameters controlling the dynamics of the system is identified. The spectral properties of the structure are analytically investigated to gain a clear insight on the coupled frame-panel structure. This is characterized by frequency veering and hybridization between the mode deforming the frame and the local modes of the panel. The system response for seismic excitation, then, is studied with a stochastic approach. Parametric analyses focusing on the values of the forces at the top and bottom connections of the panel and on the lateral displacement of the frame show that while the frame drift is controlled mainly by the first mode of the coupled frame-panel system, the top and bottom connection forces of the panel require at least consideration of the first two modes of the coupled system. This information is of great importance in deriving a reduced model of the coupled system. The proposed procedure allows for a thorough understanding of the coupled system dynamic response, and represents a viable alternative to derive the design response quantities of interest.

Joint Optimization of Preventive Maintenance and Spare Parts Ordering Considering Imperfect Detection

The optimization of preventive maintenance and spare part ordering strategies for modern production equipment is of utmost importance, given its substantial influence on the reliability of equipment systems. Furthermore, the optimization problem discussed here has a direct impact on the reduction of maintenance expenses, thus making it a significant area of research. The optimization of preventive maintenance and spare parts ordering techniques for contemporary industrial equipment, which is a massive and complex system, faces substantial obstacles notwithstanding prior research efforts in the subject. Prior studies have typically assumed a fixed lead time for spare parts ordering, often leading to discrepancies with actual practice. When faced with a critical component failure, such as rolling bearings, it is not advisable for the decision maker to strictly adhere to the ordering strategy. Therefore, this paper presents a novel approach to the maintenance management method, which optimizes preventive maintenance and spare parts ordering strategies using a dynamic early warning period model based on different equipment states. The model incorporates two maintenance approaches, namely normal ordering and emergency ordering, and the equipment will adopt the corresponding maintenance method according to its state. Furthermore, the model takes imperfect detection of equipment states into account since equipment monitoring is not always accurate. Numerical experiments were conducted using rolling bearings, which are a crucial component in typical mechanical equipment, as a case study. The findings indicate that the improved model exhibits a unit time cost of 1.3021, whereas the original model has a unit time cost of 1.3611. Consequently, the new model effectively reduces the maintenance cost. This new method can better resolve the coordination challenge between preventive maintenance and spare parts ordering for equipment, the enhancing of equipment system reliability, and reduce maintenance expenses. In summary, the text presents a significant contribution in the form of a proposed preventive maintenance model that offers increased flexibility, aiming to effectively reduce maintenance costs.

Maintenance Design of The Main Engine Support Systems on KMP. Kormomolin Under System Dynamics Scheme

The operational activities of the ship's main engine support system elevated the possibility of failure. The main engine support system at KMP. Cormomolin, which belongs to PT. ASDP Indonesia Ferry (Persero), is extremely crucial to the ship's operation. Once the ship is not sailing, maintenance and repair can be handled. The component evaluation engine can be employed to accurately estimate inadequacies in the main support system. Failure Mode Effect and Critical Analysis (FMECA) identifies the root cause of critical component failures such as filters in the fuel system and cooler and sea chest filters in the cooling system. This study generates maintenance recommendations for the main engine support system for five years, including: fuel oil filter maintenance intervals every 151 hours at a cost of IDR 14,169,072, cooler maintenance intervals every 2481 hours at a cost of IDR 16,313,508, and sea chest filter maintenance intervals every 722 hours at a cost of IDR 11,167,152. For the fuel system, the cost care percentage is 81%, and for the cooling system, it is 46% after 5 years.

Cooling strategy for punches in hot compound extrusion of critical train components

Failure of critical train components (CTCs) affects normal train operation or can cause serious accidents, resulting in economic losses. The design and manufacture of large, complex and precise punches is critical for the manufacture of CTCs. During extrusion, punches are at high temperature, which has a negative influence on the processing accuracy and reliability of CTCs. Hot compound deformation due to a long punch stroke reduces the life of punches, increasing manufacturing costs. Therefore, ensuring the timely cooling of punches is important for machining accuracy. A cooling strategy for punches under hot compound extrusion of CTCs is proposed. Based on computer-aided engineering technology, the cooling process of a punch was numerically simulated. Then, the design of an auxiliary mould was optimised and the process parameters were adjusted. The theoretical temperature rise of the punch was calculated and a formula for temperature rise and cooling of the punch obtained. According to the forced convective heat transfer of cooling water, the convective heat transfer coefficients on the surface of the cooling pipe were calculated. The interior and external heat dissipation of the punch were simulated using finite elements and the production beat and compound extrusion parameters were calculated. Interior circulation cooling equipment was then designed. Variations in the temperature field distribution were obtained after punch extrusion and heat dissipation using infrared temperature measuring equipment. The experimental and theoretical results agreed.

Improved Thermo-Mechanical Fatigue Resistance of Al-Si-Cu 319 Alloys by Microalloying with Mo.

Thermo-mechanical fatigue (TMF) is one of the most detrimental failures of critical engine components and greatly limits their service life. In this study, the out-of-phase TMF (OP-TMF) behavior in Al-Si-Cu 319 cast alloys microalloyed with Mo was systematically investigated under various strain amplitudes ranging from 0.1-0.6% and temperature cycling at 60-300 °C and compared with the base 319 alloy free of Mo. Cyclic stress softening occurred in both experimental alloys when applying the TMF loading, resulting from the coarsening of θ'-Al2Cu precipitates. However, the softening rate of the Mo-containing alloy was lower than that of the base 319 alloy because of its lower θ'-Al2Cu precipitate coarsening rate per cycle. The Mo-containing alloy exhibited a longer TMF lifetime than the base alloy at the same strain amplitude. Microalloying 319 alloy with Mo enhanced the TMF resistance mainly by slowing the coarsening of θ'-Al2Cu precipitates and providing supplementary strengthening from thermally stable Mo-containing α-dispersoids distributed in the Al matrix. The energy-based model was successfully applied for predicting the TMF lifetime with a low life predictor factor, which agreed well with the experimentally measured fatigue cycles.

Safety Concerns in Mobility-Assistive Products for Older Adults: Content Analysis of Online Reviews.

Older adults who have difficulty moving around are commonly advised to adopt mobility-assistive devices to prevent injuries. However, limited evidence exists on the safety of these devices. Existing data sources such as the National Electronic Injury Surveillance System tend to focus on injury description rather than the underlying context, thus providing little to no actionable information regarding the safety of these devices. Although online reviews are often used by consumers to assess the safety of products, prior studies have not explored consumer-reported injuries and safety concerns within online reviews of mobility-assistive devices. This study aimed to investigate injury types and contexts stemming from the use of mobility-assistive devices, as reported by older adults or their caregivers in online reviews. It not only identified injury severities and mobility-assistive device failure pathways but also shed light on the development of safety information and protocols for these products. Reviews concerning assistive devices were extracted from the "assistive aid" categories, which are typically intended for older adult use, on Amazon's US website. The extracted reviews were filtered so that only those pertaining to mobility-assistive devices (canes, gait or transfer belts, ramps, walkers or rollators, and wheelchairs or transport chairs) were retained. We conducted large-scale content analysis of these 48,886 retained reviews by coding them according to injury type (no injury, potential future injury, minor injury, and major injury) and injury pathway (device critical component breakage or decoupling; unintended movement; instability; poor, uneven surface handling; and trip hazards). Coding efforts were carried out across 2 separate phases in which the team manually verified all instances coded as minor injury, major injury, or potential future injury and established interrater reliability to validate coding efforts. The content analysis provided a better understanding of the contexts and conditions leading to user injury, as well as the severity of injuries associated with these mobility-assistive devices. Injury pathways-device critical component failures; unintended device movement; poor, uneven surface handling; instability; and trip hazards-were identified for 5 product types (canes, gait and transfer belts, ramps, walkers and rollators, and wheelchairs and transport chairs). Outcomes were normalized per 10,000 posting counts (online reviews) mentioning minor injury, major injury, or potential future injury by product category. Overall, per 10,000 reviews, 240 (2.4%) described mobility-assistive equipment-related user injuries, whereas 2318 (23.18%) revealed potential future injuries. This study highlights mobility-assistive device injury contexts and severities, suggesting that consumers who posted online reviews attribute most serious injuries to a defective item, rather than user misuse. It implies that many mobility-assistive device injuries may be preventable through patient and caregiver education on how to evaluate new and existing equipment for risk of potential future injury.

Digital Twins for predictive maintenance: A case study for a flexible IT-architecture

The Digital Twin offers great potential for use in predictive maintenance applications to prevent failures of critical components. However, due to the absence of standardized defined functionalities of Digital Twins and the associated software tools, the creation of Digital Twins is linked to a high expenditure of resources. This effort is due to static connections of components within the IT-architecture, which cannot be reused for other Digital Twins, as these IT-architectures are mainly single-case solutions. Although there are approaches for creating flexible IT-architectures, these have not yet been examined in depth for their reusability to build Digital Twins with different implementation conditions. Therefore, the goal of this case study is to investigate the reusability and the associated reduction of effort involved in building Digital Twins. For this purpose, the approaches of an IoT-platform and a service-oriented architecture are combined to create a reusable and flexible IT-architecture for Digital Twins. This IT-architecture is applied to a first use case of a Digital Twin for a compressor and then adapted to a second use case of a Digital Twin for a wind turbine. These use cases have different implementation conditions, but both find application in predictive maintenance. Finally, the reusability is evaluated and, in this context, the extent to which the resources required for building Digital Twins can be reduced when utilizing a flexible IT-architecture.

Recent Developments on Dielectric Barrier Discharge (DBD) Plasma Actuators for Icing Mitigation

Ice accretion is a common issue on aircraft flying in cold climate conditions. The ice accumulation on aircraft surfaces disturbs the adjacent airflow field, increases the drag, and significantly reduces the aircraft’s aerodynamic performance. It also increases the weight of the aircraft and causes the failure of critical components in some situations, leading to premature aerodynamic stall and loss of control and lift. With this in mind, several authors have begun to study the thermal effects of plasma actuators for icing control and mitigation, considering both aeronautical and wind energy applications. Although this is a recent topic, several studies have already been performed, and it is clear this topic has attracted the attention of several research groups. Considering the importance and potential of using dielectric barrier discharge (DBD) plasma actuators for ice mitigation, we aim to present in this paper the first review on this topic, summarizing all the information reported in the literature about three major subtopics: thermal effects induced by DBD plasma actuators, plasma actuators’ ability in deicing and ice formation prevention, and ice detection capability of DBD plasma actuators. An overview of the characteristics of these devices is performed and conclusions are drawn regarding recent developments in the application of plasma actuators for icing mitigation purposes.

Critical Vertex Identification and Suppression Strategies of Excess Carrying Failure

Suppressing large blackouts caused by the failures of critical components in complex power systems is a systematic project that needs to be comprehensively carried out from multiple aspects, such as planning, construction, and operation control. This article proposes the concept of electrical carrying quantity based on the electrical betweenness to clarify the characteristics of excess carrying failure analysis from the sight of the topology of power networks. Then, the excess carrying propagation model is constructed, which fully considers the basic topological properties and the configuration of generators and loads of complex power networks. Accordingly, the critical vertices that make network redundancy less effective in suppressing failure propagation are identified, which are defined as stubborn vertices. Afterward, an effective edge-cutting algorithm with low algorithm complexity is proposed based on the nature of stubborn vertices as the failure propagation suppression strategy. Finally, the method has been demonstrated on the IEEE 118-bus system. The results show that network redundancy combined with edge-cutting control operation can completely suppress the propagation of excess carrying failures in complex power systems.

Bridge Network Seismic Risk Assessment Using ShakeMap/HAZUS with Dynamic Traffic Modeling

Bridge infrastructures are critical nodes in a transportation network. In earthquake-prone areas, seismic performance assessment of infrastructure is essential to identify, retrofit, reconstruct, or, if necessary, demolish the infrastructure systems based on optimal decision-making processes. As one of the crucial components of the transportation network, any bridge failure would impede the post-earthquake rescue operation. Not only the failure of such high-risk critical components during an extreme event can lead to significant direct damages, but it also affects the transportation road network. The consequences of these secondary effects can easily lead to congestion and long queues if the performance of the transportation system before or after an event was not analyzed. These indirect losses can be more prominent compared to the actual damage to bridges. This paper brings about seismic performance assessment for the Cyprus transportation network from which the decision-making platform can be modeled and implemented. This study employs a seismic hazard analysis based on generated USGS ShakeMap scenarios for the risk assessment of the transportation network. Furthermore, identification of the resiliency and vulnerability of the transportation road network is carried out by utilizing the graph theory concept at the network level. Moreover, link performance measures, i.e., traffic modeling of the study region is simulated in a dynamic traffic assignment (DTA) simulation environment. Finally, for earthquake loss analysis of the bridges, the HAZUS loss estimation tool is used. The results of our investigations for three different earthquake scenarios have shown that seismic retrofitting of bridges is a cost-effective measure to reduce the structural and operational losses in the region.

Hybrid Fault-Tolerant Control for Air-Fuel Ratio Control System of Internal Combustion Engine Using Fuzzy Logic and Super-Twisting Sliding Mode Control Techniques

Safety and critical applications employ fault-tolerant control systems (FTCS) to increase reliability and availability in the event of a failure of critical components. Process facilities may employ these technologies to cut down on production losses caused by equipment failures that occur on an irregular or unscheduled basis. Air–fuel ratio (AFR) adjustment in the fuel system of internal combustion engines (ICE) is crucial for enhancing engine efficiency, saving fuel energy, and safeguarding the environment. This paper proposes a novel hybrid fault-tolerant control system (HFTCS) for controlling the AFR in ICEs that combines the features of both an active fault-tolerant control system (AFTCS) and a passive fault-tolerant control system (PFTCS). The fault detection and isolation (FDI) unit is designed using fuzzy logic (FL) as part of an AFTCS to give estimated sensor values to the engine controller when the sensor becomes faulty. Super-twisting sliding mode control (ST-SMC) is implemented as part of a PFTCS to maintain AFR by adjusting the throttle actuator in the fuel supply line under faulty conditions. Lyapunov stability analysis is also performed to make sure that the system remains stable in both normal and faulty conditions. According to the results in the Matlab/Simulink environment, the suggested system stays robust and stable during sensor faults. In faulty situations, it also maintains the AFR at 14.6 without any degradation, and a comparison with previous studies is carried out. The study shows that the suggested approach is an innovative and highly dependable solution for AFR control in ICEs, preventing engine shutdown and output loss for higher profitability.

Failure mapping and critical measurements for the operating condition assessment of power transformers

The causes of failure of critical component of the electrical power distribution network like the power transformers, has always attracted the interest of the scientific and technical community, since the failures of electrical transformers almost always have a great impact on the consumers, as they can lead to a black out situation. A reliable and coherent maintenance schedule, that would predict the causes and prevent un-expectable shutdowns of power transformers, is of outmost importance nowadays, since electrification is expanding in terms of volume and power, as well as in terms of production sources, voltage and location. Such a reliable and coherent maintenance schedule depends on many factors and this article describes the parts of oil-immersed power transformers that are prone to failure. It also illustrates the relationship of the well known dissolved gasses that appear in the insulating oil as a result of specific operating faults, with specific measurements that should be done periodically, in order to prevent a major failure. Additionally, it describes the relationship between these dissolved gases with specific maintenance actions that should be implemented during the preventive maintenance process.

Application of probabilistic methods to turbine engine disk life prediction and risk assessment

Turbine engine disk life prediction and understanding the associated risk remains a significant challenge for today’s designer. Despite advances made in materials testing and characterization, as well as, the application of damage tolerance and linear elastic fracture mechanics modeling, there remains a void in properly assessing loading, geometry, and material design property variability. Add to this the application of advanced hybrid and composite material systems and the need to accurately deal with material variability is even greater. There still remain incidents of failure of critical components which were not properly accounted for by the existing analytical methods, testing, and inspections employed today. Application of probabilistic methods offers an effective and useful approach to modeling this variability while also providing a means by which to assess random variable sensitivity and risk assessment. Current research, as well as, applicable industry and government regulatory guidelines and publications were examined and will be presented. An assessment of the most effective tools, modeling methods, and predictive risk of failure assessments together with recommendations for future work will be discussed. The potential for probabilistic methods to provide a cost-effective way to manage fleet engine and component usage is presented, as well as, its ability to enhance the safe implementation of Retirement for Cause concepts to fleet management.

Flow-Induced Vibration of Solitary Wire-Wrapped Cylinders in Axial Flow

Vibration of nuclear power plant components can cause fretting wear and fatigue that can eventually lead to component failure. Flexible, high-aspect-ratio components under flow, such as the wire-wrapped cylindrical fuel elements in a liquid metal-cooled fast reactor core, are particularly susceptible to vibration due to their low natural frequencies. The flow-induced vibrations experienced by such components tend to be random and of low amplitude and frequency; however, at critical flow velocities these components can experience self-excited, fluid-elastic instabilities that can lead to immediate failure. Such failures of critical reactor components, particularly those that act as fission product barriers, can lead to prolonged shutdowns of nuclear power plants and even to their permanent closure. Thus, a better understanding of the vibration response of wire-wrapped cylinders in axial flow is needed. This study details the development of a theoretical model that incorporates the effects of a helical wire wrap along a cylinder to understand its impact on the dynamic response of the cylinder under flow. This theoretical model is compared against experimental vibration data of varying geometries of solitary wire-wrapped cylinders in confined axial flow. The results of this study provide an improved knowledge of how a helical wire wrap can affect the dynamic response of a cylinder under flow.

Evaluation of Unreliable Flow Lines with Limited Buffer Capacities and Spare Part Provisioning

We consider a model of an N-stage flow line with stochastic processing times and interstage buffers that decouple adjacent production stages. Machine downtimes are induced by failures of critical machine components. Each machine is assumed to have exactly one of these failure-prone components. To achieve high machine availability, it is assumed that spare parts for those failure-prone critical components are kept in stock. Failed components are immediately replaced with new, functioning components, and a one-for-one replenishment policy is applied for the restocking of those spare parts. We present a novel decomposition approach to approximate the average throughput and inventory for a system with an arbitrary number of machines, buffers, and spare parts. With a detailed numerical study, we analyze the impact of different parameter constellations on the approximation quality. We demonstrate the remarkable accuracy of our method by comparing our results with both exact and simulated values. Using our method, we further study the complex interaction and partial substitution effects between buffer sizes and spare part base-stock levels on the logistical performance of the flow line.

Strain sensing in GFRP via fully integrated carbon nanotube epoxy film sensors

Structural health monitoring of composite structures enables early damage detection to prevent critical component failure. Surface-mounted strain gauges are commonly applied to monitor the integrity of composite structures in highly loaded areas. However, strain gauges can only measure strain on the structure’s surface and are exposed to environmental influences. Within this paper, fully integrated carbon nanotube thin-film sensors for strain and damage sensing in glass fibre reinforced polymers (GFRP) via electrical resistance measurements are presented. Single wall carbon nanotube epoxy thin-films were manufactured using a manual film applicator, partially pre-cured, placed on dry glass fabrics and infused in a resin transfer moulding process. The mechanical properties of the composites and strain sensing capabilities of the integrated sensors were studied for various load cases and different laminate lay-ups. Results of quasi-static and step-wise three-point bending and tensile tests show that the integrated films allow for localised strain measurements in GFRP without significant loss of mechanical properties. Open hole tensile tests proof the ability to monitor local strain and damage in highly loaded areas enabling failure prediction via threshold resistance change values. The proposed thin-films enable a tailored strain and damage monitoring of GFRP offering the possibility for measurements at different material depths, over large sections or selectively in highly loaded areas. The manufacturing process is easily automatable and suitable for large scale manufacturing.

Real-Time and Online Lubricating Oil Condition Monitoring Enabled by Triboelectric Nanogenerator.

An intelligent monitoring lubricant is essential for the development of smart machines because unexpected and fatal failures of critical dynamic components in the machines happen every day, threatening the life and health of humans. Inspired by the triboelectric nanogenerators (TENGs) work on water, we present a feasible way to prepare a self-powered triboelectric sensor for real-time monitoring of lubricating oils via the contact electrification process of oil–solid contact (O–S TENG). Typical intruding contaminants in pure base oils can be successfully monitored. The O–S TENG has very good sensitivity, which even can respectively detect at least 1 mg mL–1 debris and 0.01 wt % water contaminants. Furthermore, the real-time monitoring of formulated engine lubricating oil in a real engine oil tank is achieved. Our results show that electron transfer is possible from an oil to solid surface during contact electrification. The electrical output characteristic depends on the screen effect from such as wear debris, deposited carbons, and age-induced organic molecules in oils. Previous work only qualitatively identified that the output ability of liquid can be improved by leaving less liquid adsorbed on the TENG surface, but the adsorption mass and adsorption speed of liquid and its consequences for the output performance were not studied. We quantitatively study the internal relationship between output ability and adsorbing behavior of lubricating oils by quartz crystal microbalance with dissipation (QCM-D) for liquid–solid contact interfaces. This study provides a real-time, online, self-powered strategy for intelligent diagnosis of lubricating oils.

Material selection for long life and high durability for special purpose type of flexure bearing

A special type of flexure bearings are installed to support a compressor motor and a displacer within a cryocooler which is used in space applications. The fatigue life of spring is a critical factor for such applications, to ensure that the cryocooler does not fail. The flexure spring is used in the setup of an eccentric type of flexure bearing. The present study analyzes various significant parameters and properties in selecting the best suitable material to achieve finite-fatigue life. To avoid a failure of such critical component, batch testing is carried out. The three materials which are compared with respective SN-curve are a] beryllium copper, b] Stainless Steel (3 0 4) and c] Titanium. The study has been carried out to find the best suitable material for flexure bearing. Finite Element Analysis (FEA) is used to understand flexure springs stress and displacement.

Hardfacing and its effect on wear and corrossion performance of various ferrous welded mild steels

Wear and corrosion exist as one of the main important factor of energy and material losses in mechanical and chemical process. This work is about the methods to evaluate the wear and corrosion resistant properties of the mild steel like EN-8, EN-9 and EN-24 by calculating its corrosion rate. All materials have to be analyzed for its wear properties since higher wear can lead to a machine failure. The Pin on Disc apparatus is used for the analysis. Every oil-washed system- engines, hydraulics, transmissions, and final drives- produces wear metals in everyday operation. If wear accelerates, the concentration of wear metal particles increases, signaling a problem. Wear Analysis allows us to find problems before they result in major repairs or machine failure. Prediction of the material behaviour at the increasing load is necessary for a safe working of the machines. The ferrous materials are hardfaced using Tungsten Inert Gas welding process. The wear analysis of ferrous welded materials is carriedout. The various forms of mild steel selected are selected are EN 8, EN 9, EN 24. The materials are hardfaced using TIG (Tungsten Inert Gas) welding process and filler material used is same for all the materials. The materials are cut into specific dimensions using Wire cut EDM process. These specimens are tested for its wear properties, microhardness etc. Pin on Disc apparatus is used for wear analysis and Vicker’s microhardness tester is used for microhardness. Similarly a corroded component results in reduced life. Corrosion results in unexpected failures of critical components. Corrosion testing is a very time-consuming process; especially in the case of outdoor atmospheric tests. Such long timescales involved in such tests prevent the opportunity for proper materials selection. The vey commonly used corrosion tests are measurements of the weight loss or thickness loss. This test can be simply done in laboratory in limited period of time and thereby it’s possible to predict the corrosion rate of the materials. By comparing wear and corrosion rates of hardfaced and non hardfaced surface its possible to conclude that the hardfacing improves both the wear and corrosion resistant property of these materials. .