Reliability, Availability And Maintainability Analysis Research Articles

RAM Analysis at Gas Turbine Power Plant with Six Sigma Method

The goal of this study is to identify breakdown that has an impact on the gas turbine engine's RAM and Six Sigma level in order to assess how well the gas turbine engine performance through the value of RAM (Reliability, Availability, and Maintainability) and Six Sigma. By gathering, compiling, categorizing, and conducting an analysis of data and information on the utilization of gas turbine engines, based on actual data and information, the descriptive analysis method is used to reveal the availability and performance of gas turbine engines. The findings of the RAM and Six Sigma level are examined utilizing the Pareto chart to identify the most impacted breakdown, the Fishbone diagram for root cause analysis, and the five why analysis approach for improvement suggestions. According to research findings, control system failure, VGV system failure, and load distribution problem have an impact on the RAM and Six Sigma level of two gas turbines. The Root cause of the issue is due to a number of factors, including mostly due to technical issues of unreliable old control system and VGV system design, an incorrect maintenance schedule implementation, an incompetent and ignorant of operator or technician to gas turbine engines.

A RAM extension to enhance ship planned maintenance system

ABSTRACT This study develops a knowledge-based planned maintenance system (PMS) supported by reliability, availability and maintainability (RAM) analysis. The system enables maintenance plan revisions based on the data analysis which calculates instant RAM values and predicts the future trends. The visualised data is monitored to support decisions at both the operational and management level. The proposed system is demonstrated with the periodical data of the main engine installed onboard a container ship. Particularly, the data visualization is conducted on fuel injection valves. The results illustrate that the enhanced PMS system adds value to the timely and effective planning of routine and non-routine maintenance tasks onboard ships. Considering the existing potential of PMS applications onboard ships, the RAM analysis provides reasonable contributions to ship engine room crew and technical managers. The further study focuses on developing a maintenance planning app to digitalise the process and to strengthen compliance with ISM Code Clause 10 and TMSA 4A.4 requirements.

RAM analysis of dynamic positioning system: An approach taking into account uncertainties and criticality equipment ratings

Currently, a Dynamic Position (DP) System is commonly used for offshore operations. However, DP failures may generate environmental and economic losses; thus, this paper presents the Reliability, Availability and Maintainability (RAM) analysis for two different generations of DP system (DP2 and DP3) used in drilling operations. In addition to the RAM analysis, the approach proposed herein considers the uncertainties present in the equipment failure data and provides more information about criticality equipment ratings and probability density functions (pdf) of the repair times. The reliability analysis shows that, for 3 months of operation, the total failure probability of the DP2 system is 1.52% whereas this probability for the DP3 system is only 0.16%. The results reveal that the bus-bar is the most critical equipment of the DP2 system, whereas the wind sensor represents the priority equipment in the DP3 system. Using 90% confidence level, each DP configuration was evaluated for a 1-year operation, finding a reliability mean equal to 70.39% and 86.77% for the DP2 system and the DP3 system, respectively. The DP2 system asymptotic availability tends to present a constant value of 99.98% whereas for the DP3 system, it tends to be 99.99%. Finally, the maintainability analysis allows concluding that the mean time for system repair is expected to be 3.6 h. This paper presents a logical pathway for analysts, operators, and reliability engineers of the oil and gas industry.

Reliability, availability and maintainability analysis of a bag production industry based on the six sigma DMAIC approach

PurposeThe purpose of this paper is to implement the six sigma (SS) strategy in a bag sector under actual operating circumstances based on defining-measure-analyze-improve and control (DMAIC). During the project, several statistical tools and methods have been used efficiently to create inferences. Thus, to measure and enhance system efficiency, the author calculate reliability, availability and maintainability (RAM) indices. Based on this research, the author show how the SS method and RAM analysis are very helpful in determining maintenance intervals, as well as in planning and organizing the appropriate maintenance strategy.Design/methodology/approachThis study introduces the step-by-step application of the DMAIC methodology for the identification and reduction of bag production line downtime and examines the present operations management. Thus, statistical techniques are used to analyze the failure and repair database. Pareto analysis, histograms and descriptive statistics at the machine and line-level of the historical data were conducted. Trend and serial correlation testing validated the hypothesis of independence and identical distribution of database was performed. In addition, with their best fit allocation, the RAM of both the bag production line and its machines was estimated at separate mission times.FindingsThe main goals of the applied method are to understand the nature of the downtime patterns and to accurately and quantitatively estimate the RAM characteristics of the bag production system. The assessment defines the production line's critical points, requiring further enhancement through an efficient maintenance approach. Therefore, by improving plant efficiency and safety, the author can decrease unplanned downtime and equipment failures.Originality/valueThis research is expected to serve as an attempt to conduct SS DMAIC methodology through RAM assessment and its impact on system efficiency under actual circumstances. The benefit of the methodology is that the manufacturing process is continuously monitored by suitable indicators, the use of which leads to a continuous improvement cycle.

Reliability, Availability and Maintainability Analysis to Improve the Operational Performance of Soft Water Treatment and Supply Plant

The purpose of this paper is to provide results for reliability, availability and maintainability (RAM) measures to improve the operational performance of a soft water treatment and supply plant (SWTS-Plant) through the illustrative case study. RAM analysis of SWTS plant installed in a high-rise society ABC, Jaipur was performed. The descriptive analysis of time to failure and repair has been made along with trend analysis and goodness-of-fit test. The best fitted distributed and parameters have been identified from the existing theoretical distributions using the maintenance data of ABC plant. Reliability and maintainability measures also calculated for the entire plant. It is observed that (i) the plant availability decline from 97.96% to 92.67% (ii) failures of five subsystems dominant with 81.5 % failures and (iii) average failure rate is 937.4 minutes. This study will be supportive to identify the occurring complications in the plant.

Reliability, availability and maintainability analyses for railway infrastructure management

Reliable, available, maintainable and safe operation in railway transportation is significant for passenger and freight transportation. For these reasons, European Union put into practice a standard in 1999 known as EN 50126 to prevent railway accidents and to ensure a high level of safety in railway operations. The EN 50126 standard consists of these following concepts: Reliability, Availability, Maintainability and Safety (RAMS). These concepts are also recognised as RAMS analyses, which enable to do risk analyses to minimise the risks to the acceptable levels. In this study, a model framework including some stages was developed and the Reliability, Availability and Maintainability (RAM) analyses were applied to the railway infrastructure management. In addition, a case study was analysed for Uzbekistan high-speed railways between Tashkent and Sirdaryo train stations. The RAM analysis techniques were used during the analysis stages. The analyses were performed for the track geometry and the each type of railway track components to achieve a reliable, available and maintainable railway infrastructure management.

Reliability, availability and maintainability analysis of a cement plant: a case study

Purpose The demand of cement in India is expected to increase rapidly as the government has been giving immense boost to various housing facilities, infrastructure projects, road networks and railway corridors. One of the ways to meet this rise in the demand of cement is to increase the capacity utilization of the existing cement plants by improving their availability. The availability of a cement plant can be improved by avoiding failures and reducing maintenance time through reliability, availability and maintainability (RAM) analysis of its subsystems. The paper aims to discuss this issue. Design/methodology/approach The data related to time between failure (TBF) and time to repair (TTR) of all the critical subsystems of a cement plant were collected over a period of two years for carrying out RAM analysis. Trend test and serial correlation test were performed on TBF and TTR data to verify whether these data are independent and identically distributed or not. Afterwards, the authors use EasyFit 5.6 professional software to find best-fit distribution of TBF and TTR data and their parameters. The effectiveness of a preventive maintenance policy was evaluated by simulating the real and proposed systems. Findings The results of the analysis show that the raw mill and the coal mill are critical subsystems of a cement plant from a reliability point of view, whereas the kiln is a critical subsystem from an availability point of view. The analysis shows that the repair time of the cement mill should be reduced for improving the availability of the cement plant. The RAM analysis showed that the capacity of the case study company is 17 percent underutilized due to maintenance-related problems and 15 percent underutilized because of management-related problems. Practical implications The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Thus, it would serve as a reference for reliability and maintenance managers in deciding maintenance strategies of cement plants as well as in improving their capacity utilization. Originality/value The study exhibits the usage of RAM analysis in deciding preventive maintenance programs of several cement plant subsystems. Even more, using a simulation study, the authors show that preventive maintenance of the cement plant beyond a certain level can be disadvantageous as it leads to an increase in downtime and decrease in availability.

Statistical analysis of failure data for estimating reliability, availability and maintainability of an automated croissant production line

PurposeThe purpose of this paper is to compute reliability, availability and maintainability (RAM) indices to measure and improve the performance of an automated croissant production line under real working conditions. Based on this study, the authors demonstrate how RAM analysis is very useful for deciding maintenance intervals and for planning and organizing the adequate maintenance strategy.Design/methodology/approachThe present work is carried out by analyzing failure and repair data based on statistical techniques. Descriptive statistics of the failure and repair data at workstation and line level were carried out. Trend and serial correlation tests validated the assumption of independence and identical distribution of the failure data were conducted. Moreover, the reliability and maintainability of both the croissant production line and its workstations have been estimated at different mission times with their best fit distribution.FindingsThe main objectives of the applied method are to understand the nature of the failure patterns, and to estimate the reliability and maintainability characteristics of the croissant production system in precise quantitative terms. The analysis identifies the critical points of the production line that require further improvement through effective maintenance strategy.Originality/valueThis study is anticipated to serve as an illuminating effort in conducting a complete RAM analysis and its effect on the performance of the system that works under real conditions. The advantage of the methodology is the continuous monitoring of the production process through appropriate indices, the utilization of which leads to a continuous cycle of improvement.

A new fuzzy methodology-based structured framework for RAM and risk analysis

The aim of this paper is to propose a new hybridized framework for analyzing the performance issues of a chemical process plant by utilizing uncertain, imprecise and vague information. In the proposed framework, Fuzzy Lambda–Tau (FLT) approach has been used for computing reliability, availability and maintainability (RAM) parameters of the considered system. Further, for enhancing the RAM characteristics of the system, improved Fuzzy Failure Mode Effect Analysis (FMEA) approach is adopted. Under improved Fuzzy FMEA approach, defined Fuzzy linguistic rating values in the form of triangular and trapezoidal Fuzzy numbers have been assigned by the experts to each risk factor of the listed failure causes. The proposed framework is demonstrated with an industrial application in a chlorine production plant of a chemical process industry. The results show decreasing trend for system availability and deposition of solid Nacl, mechanical failure, corrosion due to wet chlorine, scanty lubrication, improper adsorption and valve malfunctioning are identified as the most critical failure causes for the considered system. A comparative performance analysis between the proposed framework, Fuzzy technique for order of preference by similarity to ideal solution (Fuzzy TOPSIS), Fuzzy evaluation based on distance from average solution (Fuzzy EDAS) and Fuzzy Vlse Kriterijumska Optimizacija I Kompromisno Resenje (Fuzzy VIKOR) are then carried out to show the competence of the proposed framework. It is expected that the analytical results would be highly useful in formulating an optimal maintenance policy for such complex systems and may also be used for improving performance of similar plants.

RAM analysis of rotary drilling machines

Rotary drilling machines are the most common machines used for drilling the blast holes in mining and constructions activities. The vital role of drilling operation in mining activities reveals that, the performance analysis of drilling machines and their failure and repair behaviors are essential. There-fore, the present study focuses on the reliability, availability and maintainability (RAM) of drilling ma-chines. In this paper, four rotary drilling machines at Sarcheshmeh Copper Mine in Iran are considered for repair and failure data collection. RAM analysis of drilling machines is done using Markov Approach. Results show that the reliability of drilling fleet is decreased by 0.67% in per hour drilling. The hydraulic system is the main unavailability reason of all machines. Moreover, the most failures of the two newest machines are completely repaired in 25 hours

The Application of RAM Analysis in a CNC System

The reliability, availability and maintainability (RAM) analysis of a computerized numerical control (CNC) system is helpful for performing design modifications that are required to achieve minimum failures or to increase the mean time between failures (MTBF), to plan maintainability requirements, to optimize reliability and to maximize equipment availability. To demonstrate these benefits, this paper presents the application of RAM analysis in a CNC system. The Weibull approach is used to model the CNC system behavior. After determining the steady state solution for the CNC system behavior, the corresponding values of reliability and maintainability are estimated at different mission times. The computed results proved to be helpful for analyzing the CNC system behavior, which enabled a considerable improvement of the system performance by implementing suitable maintenance strategies.

RAM investigation of coal-fired thermal power plants: A case study

: Received 28 October 2011 Accepted December, 5 2011 Available online 8 December 2011 Continuous generation of electricity of a power plant depends on the higher availability of its components/equipments. Higher availability of the components/equipments is inherently associated with their higher reliability and maintainability. This paper investigates the reliability, availability and maintainability (RAM) characteristics of a 210 MW coal-fired thermal power plant (Unit-2) from a thermal power station in eastern region of India. Critical mechanical subsystems with respect to failure frequency, reliability and maintainability are identified for taking necessary measures for enhancing availability of the power plant and the results are compared with Unit-1 of the same Power Station. Reliability-based preventive maintenance intervals (PMIs) at various reliability levels of the subsystems are estimated also for performing their preventive maintenance (PM). The present paper highlights that in the Unit-2, Economizer (ECO) & Furnace Wall Tube (FWT) exhibits lower reliability as compared to the other subsystems and Economizer (ECO) & Baffle Wall Tube (BWT) demands more improvement in maintainability. Further, it has been observed that FSH followed Decreasing Failure Rate (DFR) and Economizer (ECO) is the most critical subsystem for both the plants. RAM analysis is very much effective in finding critical subsystems and deciding their preventive maintenance program for improving availability of the power plant as well as the power supply.

Reliability issues in the design and operation of process utility systems

Traditional operation optimization is effective to enhance the energy efficiency of a utility system for given operating scenarios. Total operating cost will be saved, but the penalty cost caused by utility system failures cannot be considered. Optimal operating conditions from traditional optimization might have less flexibility to respond to utility system failures or maintenance and might result in a high penalty cost. In practice, it is not unusual that a unit (boiler, gas turbine, steam turbine) could fail unexpectedly, and lead to an interruption of utility supplies. If an interruption occurs, processes will need to operate at partial load or even to be shut down due to insufficient energy supply. Even though there are standby facilities that could start up in several hours, the penalty cost could still be very high during the response time of utility systems. Safety implications might demand that the system be designed to operate under all possible circumstances. A balance between operating cost and penalty should be achieved for the minimum overall total cost. To obtain the true cost, an analysis of system reliability, availability and maintainability (RAM) is essential. Moreover, not only the operating conditions should be optimized, but also operating strategies should be selected properly, e.g. cold standby, hot standby, load-sharing, etc. A novel optimization methodology has been developed to systematically minimise overall cost by considering utility system failures, maintenance requirements and different operating strategies. Maximum overall site profit will be obtained through advanced optimization with RAM analysis. Copyright ? 2011, AIDIC Servizi S.r.l.

IFMIF accelerator: Database, FMEA, fault tree and RAM

In this paper, a reliability, availability and maintainability (RAM) analysis of the international fusion materials irradiation facility (IFMIF) accelerator is described. The RAM analysis consists on a statistical work from the results of a fault tree model based on the adaptation of an updated failure modes and effects analysis (FMEA). The results have been developed with different statistical analyses such as time dependency analyses, importance and sensitivity analyses, parametric analyses and uncertainty analyses in order to identify critical components on new design and maintainability strategies to improve IFMIF's availability.

Behavioural analysis of urea decomposition system in a fertiliser plant

Reliability, availability and maintainability (RAM) analysis of a system is helpful in carrying out design modifications, if any, and it is required to achieve minimum failures or to increase mean time between failures (MTBF), and thus it is used to plan maintainability requirements, optimise reliability and maximum equipment availability. To this effect, this paper presents the application of RAM analysis in the process industry. Fuzzy Lambda–Tau methodology is used here to model the system behaviour. Each system components, failure rate and repair time are represented by triangular fuzzy numbers with known spread. The methodology uses Petri nets to model the system instead of fault tree because it allows efficient simultaneous generation of minimal cuts and path sets. Various reliability parameters such as MTBF, expected number of failures (ENOF), reliability, availability, etc. are calculated. The computed results are presented to plant personnel for their performance considerably by adopting and practicing suitable maintenance policies/strategies.

Criticality analysis of a production facility using cost importance measures

When the estimated plant performance is inadequate, it is necessary to use appropriate methodologies and tools for production performance improvement with the minimum effort and cost in the design and/or operation phase. Hence, the concept of importance measure can be used for this purpose. It can be used to determine which components can be improved first in order to get the largest improvement in system performance. Within the system RAM (reliability, availability and maintainability) analysis, the Birnbaum importance analysis plays an important role in the performance improvement program. When both the components’ reliability and maintainability factors are considered in the importance measure analysis, it is noted that the component/system Mean Time to Repair (MTTR) is too short compared with component/system MTTR. Thus, it is necessary to bring the cost factors into the importance measure. This paper proposes a cost importance measure which considers both the reliability and the maintainability information of a system. Then, this cost importance measure is studied in a simple oil and gas production system.

RAM analysis of repairable industrial systems utilizing uncertain data

Industrial systems are mostly complex and considered as repairable. Also data, either collected or available (historical), reflecting their failure and repair patterns are limited, vague and imprecise due to various practical constraints. In such circumstances, their reliability, availability and maintainability (RAM) analysis may play an important role in any design modifications, if required, for achieving its optimum performance. However, it is difficult to estimate the RAM parameters of these systems up to a desired degree of accuracy by utilizing available information and uncertain data. This paper provides an idea, how can we estimate the RAM parameters of these systems by utilizing available information and uncertain data. For this purpose, Genetic Algorithms based Lambda–Tau (GABLT) technique is used. In this technique, expressions for the RAM parameters of the system are obtained by using traditional Lambda–Tau methodology and genetic algorithm is used to compute these parameters in the form of fuzzy membership functions utilizing quantified data in the form of triangular fuzzy numbers. A general RAM-Index is used for post RAM analysis to rank the subunits of the system on the basis of their performance. The approach has been applied to the press (series system) and washing (series–parallel system) units of a typical paper mill. The results may be helpful for the plant personnel for analyzing the systems’ behavior and to improve their performance by adopting suitable maintenance strategies.

Dependability & safety modeling and calculation: Petri nets

Since its birth, about fifty years ago, the reliability field develops methods and tools to satisfy its different needs and this is more and more difficult as industrial systems becomes more and more complex and required parameters more and more sophisticated. Then the simplistic reliability and availability calculations of the origins are no longer sufficient to fulfill the present time needs encountered when dealing with RAM (Reliability, Availability, and Maintainability) or SIL (Safety Integrity Level) analysis. The dynamical behavioral aspects and the combinatory explosion of the number of states of industrial size system imply to proceed to a qualitative jump to be able to manage them properly. This may be done simply by moving from the traditional analytical approach to the Monte Carlo simulation. Nevertheless to be implemented efficiently this approach needs a powerful model behaving a close as possible as the physical system which is modeled. Finite states automata are generally chosen for this purpose and, among them the stochastic Petri nets (SPN) have proven to be very effective. This is the aim of this paper to show how SPN may be used for RAM (i.e. dependability) and SIL (i.e. functional safety) objectives.

Performance modeling in critical engineering systems using RAM analysis

Reliability, availability and maintainability (RAM) analysis of system is helpful in carrying out design modifications, if any, required to achieve minimum failures or to increase mean time between failures (MTBF) and thus to plan maintainability requirements, optimize reliability and maximize equipment availability. To this effect, the paper presents the application of RAM analysis in a process industry. Markovian approach is used to model the system behavior. For carrying out analysis, transition diagrams for various subsystems are drawn and differential equations associated with them are formulated. After obtaining the steady state solution the corresponding values of reliability and maintainability are estimated at different mission times. The computed results are presented to plant personnel for their active consideration. The results proved helpful to them for analyzing the system behavior and thereby to improve the system performance considerably by adopting and practicing suitable maintenance policies/strategies.