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A CRITICAL LITERATURE REVIEW AND FUTURE PERSPECTIVE OF RAM APPROACHES FOR COMPLEX SYSTEMS IN VARIOUS PROCESS INDUSTRIES
Mausoof Sheikh1
!Ph.D. Scholar, Department of Production and Industrial Engineering, National Institute of Technology, Kurukshetra-136119, INDIA [email protected]
Dr. P.C. Tewari
Professor, Department of Mechanical Engineering, National Institute of Technology,
Kurukshetra-136119, INDIA [email protected]
Abstract
In the industrial systems there is a requirement that systems should work efficiently for long time. System performance is an important aspect for failure free operation but in real practice complete failure free operation of any production system is seldom possible. Detailed critical literature review for the past thirty three years of Reliability, Maintainability and Availability (RAM) approaches has been carried out which can help to improve performance of Complex systems. Review of some papers provided the detailed information about past and current scenario of RAM practices in research field and industries. Different RAM tools and techniques extracted from the review may be helpful in qualitative and quantitative analysis of the complex systems. In this paper, author tried to focuss on some major aspects of RAM approaches.
Keywords: Reliability, Availability, Maintainability, Safety, Markov, Petri Nets, Dependability.
I. Introduction
All assets would be developed in a perfect world with low failure rates, low maintenance costs and simplicity of use in mind. There should be adequate balance in the productivity of an asset with the cost of its purchase and maintenance. A team of design, systems, and reliability professionals will usually do RAM analysis during the design phase. Over the course of the asset's life, the study can be repeated by maintenance and service reliability engineers, who have vital information on the performance and health of the asset.
These three factors (Reliability, Availability and Maintainability) are all equally crucial and frequently complement one another. Machine is operational if it is available, reliable if it is likely to function correctly, and maintainable if it can be quickly rectified even if something goes wrong.
Reliability can be defined as the probability that a system will complete the task and run flawlessly in a specific environment for a set period of time. In reliability engineering, high levels of "lifetime" engineering uncertainty and failure hazards are addressed through prediction, prevention, and risk management. Although stochastic parameters influence and determine dependability, mathematics and statistics are not the only ways to achieve it. Reliability engineering is closely related to quality engineering, safety engineering and system safety.
Availability is a special parameter that combines serviceability and reliability criteria. It indicates the probability that an asset will be operational (neither maintained nor repaired) at any given time. Availability is measured at steady state, taking into account potential downtime during which the service may (and will) become unavailable during its expected useful life. In reliability engineering calculations, the failure rate is taken as the predicted strength of failure, assuming the component is fully functional in its original state.
Maintainability discusses the ease of maintenance on an asset and the resource requirements. The probability that an asset will resume its intended state after a maintenance duty can also be calculated using this method. Mean Time to Repair (MTTR) is a common metric used to evaluate it.
System engineers, logisticians and users are particularly interested in the three RAM (Reliability, Maintainability and Availability) characteristics of a system. Together these characteristics have an impact on a product or system's usefulness as well as its life-cycle costs. A decision-making tool known as Research on Reliability, Availability and Maintainability (RAM) is utilized to increase system availability, which in turn increase overall profitability and reduces cycle costs life. In engineering, the term "Reliability, Availability, Maintainability and Safety" is frequently used to describe a property of a product or system.
II. Critical Literature Review
Ciardo et. al. (1990) performed analysis of processing systems using semi-markov reward processes. The semi-markov reward process is an extension of an algorithm proposed by Beaudry, it was presented for the computation of accumulated reward in a semi-markov process [1]. Viswanadham et. al. (1991) formulated the performability of the fault-tolerant manufacturing system. Through examples, the authors try to show the importance of performability in automated manufacturing system design. Performability measures considered deal with throughput and manufacturing lead time, which essentially determine the competitiveness of a plant [2]. Kumar et. al. (1992) studied the analytic behavior of reliability and availability of the crystallizer system in sugar plants. The model was based on Chapman-Kolmogrov equations. The Laplace transform was used to derive steady-state availability and various state probabilities. The effect of failure and repair rates on availability has been studied [3]. Sharma and Bazovsky (1993) performed analyses of large and complex systems using Markov method. Laplace transform method was used to solve the differential equation. After the modeling, design engineers were able to evaluate their own design to increase the reliability of the system [4]. Behera et. al. (1994) used deterministic and stochastic based petri net to modelled the flexible manufacturing system. Performance evaluation of system has also been done. Generalized stochastic petri net was also used to modelled the flexible manufacturing systems. Performance measure obtained was almost equal for both deterministic petri net and generalized stochastic petri net [5].
Murty and Naikan (1995) investigated the optimization of a manufacturing plant's availability and maintenance costs. It has been concluded that before making any major decisions regarding the formation of the maintenance budget, it is prudent to carefully examine the economic viability of overspending on maintenance in order to increase plant availability [6]. Kumar et. al. (1996) assessed the shell gasification and carbon recovery processes in a urea fertilizer plant from a behavioral perspective. The author of this paper used straight forward probability considerations to formulate the issue. The equations for steady-state availability were derived, and they provided the equipment's behavior based on the analyses of the results. Based on the failure results, advise the maintenance manager with guidelines for carrying out the workplan for repairs, among other things [7]. Arora and Mehta (1997) evaluated the steam and power generation capacity of thermal power plants. The authors devised the expressions for steady-state availability and mean time between failures. Graphs illustrate how failure and repair rates affect system availability. The Chapman-Kolmogorov birth-death process and a probabilistic method were used in the modeling procedure. The critical system and subsystem made a decision to limit failures based on the results, and the plant staff was informed of the results so they could make plans for the system's failure-free operation [8]. Pellegrini et. al. (1998) used a statistical approach based on the semi-Markov technique to assess the availability and performance of electronic complex systems. The electronic system's resolution model of a semi-Markov process was identified from the findings, and the mean Laplace transform was used to calculate the asymptotic availability value [9]. Singh and Mahajan (1999) evaluated a production facility for utensils for availability and dependability. Differential equations resolved using the Laplace transformation. The Markovian method was used to investigate the effect of different parameter availability. The findings demonstrated that availability impacted when repair and failure rates are disrupted [10].
Borgnovo et. al. (2000) proposed modeling through Monte Carlo. The plant's tool management and operation were advised by Monte Carlo modeling. The paper's analysis looks at the operation and maintenance plan [11]. Zhang and Horigome (2001) looked at how the availability and dependability of the system's failure and repair rates evolved over time. The solution shows the system's availability and dependability with varying failure and repair rates [12]. Wang and Loman (2002) critically examined the K-out-of-N system's availability and dependability using M cold steady units. The design process for such power systems has been investigated and it has been found that this kind of design is capable of eliminating Single Point Failure (SFP), Common Mode Failure (CMF) and the greatest likelihood of human error [13]. Dai et. al. (2003) presented a model of a centralized heterogeneous distributed system in order to learn more about distributed system service availability and dependability. The model parameter's sensitivity was investigated. Conclusion has been made that the service reliability function can assist in appropriately allocating testing resources [14]. Rauzy [2004] described six approaches for calculating the time-dependent probability of Markov models. After a thorough investigation of techniques such full matrix exponentiation, Euler approach, Runge-Kutta method, and Adams-Bash ford multi-steps methods of order 2 and 4, it was shown that computers nowadays could potentially manage Markov networks with millions of transitions [15].
Marseguerra et. al. (2004) studied multi-objective optimization, which takes into account parameter uncertainty and is primarily based on genetic algorithms. This method gives the decision-maker a tool to use in order to find a solution that is also optimal in terms of expected safety behavior and allows for a high degree of assurance in the actual system performance after applying the procedure to more complex systems [16]. Gupta et. al. (2005) utilized the mathematical formulation of the model to propose a numerical analysis of the process's availability and reliability in the bute-oil processing plant. After discussion, it may indicate that the proposed
technique is applicable to complicated systems that are also governed by substantial differential equations [17]. Majeed and Sadiq (2006) utilized the Markovian method to create a model for the Dokan hydro power station. The discussion and modeling of the issue led to the conclusion that power station reliability decreased annually. Conclusion has been made that a poor maintenance program and the inexperience of engineers and technicians affected availability adversely [18]. Chuan ke and Kuangkhu (2007) conducted a comparison of the availability of repairable redundant systems. Four bootstrap approaches were used to compute a comparison of confidence intervals for steady-state availability [19]. Sharma and Kumar et. al. (2008) presented the Markovian method of obtaining system behavior through the use of RAM analysis in crucial engineering systems. The transition diagram was used to create the differential equations. Based on the results, it has been advised to the managerial staff that characteristics like MTBF and MTTR are important for the system's planning and maintenance [20].
Goyal et. al. (2009) carried out an availability analysis of a part of Rubber tube production system under pre-emptive resume priority repair. The methodology used was Markov modelling. The purpose of the paper was to improve operational availability. Based on the results, the effect of failure and repair rates on availability was found. This information helps maintenance management improve the overall reliability and availability of the system [21]. Adhikary et. al. (2010) analyzed a coal-fired power plant's RAM. Before the data are fitted best with a probability distribution, a trend test and a serial correlation test are used to verify the distribution of failure and repair data. The significant subsystem has been identified through the use of Pareto analysis. The findings led to the conclusion that a rise in MTBF and a decrease in MTTR increase the power plant's availability [22]. Vora et. al. (2011) evaluated performance of turbo generator system of thermal plant using probabilistic approach. Markov approach has been used for problem formulation through transition diagram. Based on result availability graphs of failure and repair for maximum availability has been analyzed [23]. Garg and Sharma (2012) analyzed the performance of the synthesis unit in a fertilizer plant. The system's behavioral sensitivity has also been investigated. The Lamda Tau-Technique was used to investigate the behavior of a complex system that could be improved. Eight significant dependability parameters were also registered as fuzzy membership function [24]. Wolde et. al. (2013) discussed the issue of railway carrier inspections and maintenance. Using mathematical modelling, this study ties failure and repair rates to system performance. This modelling was used to evaluate inspection plans for any system, further optimizing its cost [25].
Suleiman K et. al. (2013) dealt with applying a probabilistic strategy to analyze stochastic data and evaluate thermal power plant performance. According to the findings of the analysis, availability decreases as the failure rate rises, while availability rises as the repair rate rises and vice versa. The plant management can use the result-based system for system availability analysis [26]. Dewangan et. al. (2014) investigated the reliability of thermal power plant's steam turbines. Investigation has been done based on failure database of five year. Failure modes and effect analysis (FMEA) used to categorize critical components. Based on investigation it has been concluded that well planning and regular scheduled maintenance can improve the reliability of plant [27]. Aggarwal et. al. (2015) proposed a performance model based on the Markov birth-death process for calculating RAM, dependability, MTBF and MTTR. Modeling has been done mathematically using Chapman-Kolmogorov differential equations and probabilistic considerations. Most critical subsystem pointed and suggested management to take utmost care [28] Talebborouane et. al. (2016) applied sophisticated fault tree and stochastic Petri Net formalisms to examine the availability of safety-critical systems. Generalized stochastic Petri Nets and fault tree driven Markov processes were utilized for analysis to get over the drawbacks of the Markov process and Petri Nets. It concluded that Petri Net is better for modeling as compared to
fault tree driven Markov process [29]. Kumar and Tewari (2017) utilized Particle Swarm Optimization (PSO) to optimize and analyse the performance of a beverage plant system. Exponential distribution is considered for repair and failure rate, and Markov approach is used for mathematical modelling. Results have been discussed with plant management for the improvement of system performance [30].
Malik and Tewari (2018) modeled and prioritized maintenance for a coal-fired thermal power plant's water flow system. Chapman-Kolmogorov equations were derived to obtain performance modelling using the Markov approach. The authors demonstrated the proposed approach to assisting in this kind of decision-making process through the case study [31]. Singhal and Sharma
(2018) used the Markov process and generalized fuzzy numbers to analyse the availability of industrial systems. The uncertainty of data has been dealt with generalized fuzzy numbers. Availability analysis has been analysed through different arithmetic operations. The system analyst observed the impact of failure and repair rates on the system [32]. Velmurugan et. al.
(2019) used Markov process to analyze the reliability, availability and maintainability of the forming industry. MATLAB software was used to solve mathematical functions. Based on the results, most critical subsystem was established. The best maintenance policy has also been provided to the maintenance manager for optimal maintenance [33] Elusakin and Shafiee (2020) estimated the reliability of subsea blowout preventers using advanced analysis method stochastic Petri Nets with different failure modes. MTBF, availability and reliability terms obtained and analyzed. Sensitivity analysis was carried out to assess the impact that the redundancy design and fault coverage factor have on system performance. Based on the results, it defined that system availability and MTBF were significantly influenced by fault coverage and redundancy [34]. Jagtap et. al. (2020) optimized the availability of the boiler furnace system in coal-fired thermal power plant using Particle Swarm Optimization (PSO). The Markov method was used for the analysis of the system. Based on the results maintenance priority has been handed over to plant management [35].
Maihulla et. al. (2021) utilized RAMD (Reliability, Availability, Maintainability and Dependability) analysis to evaluate the efficiency of the complex system of reverse osmosis water purification equipment. The primary objective was to optimize the economy. The components were determined through sensitivity analysis. The RAM of a subsystem (the high-pressure pump) has a substantial effect on the system's overall availability, it was found after the discovery [36]. Kumar et. al. (2021) utilized the Petri Nets modeling method to examine the performance of a complex manufacturing system in order to influence the actual behavioral patterns of the many subsystems deployed in the plant. Subsystem that has been severely impacted by availability has been determined by the results [37]. Parkash and Tewari (2022) conducted modeling using the Markovian method and employed a probabilistic approach to design the Decision Support System (DSS) for assembly line maintenance. Probabilities for the steady state were determined using a transition diagram and by solving differential equations. The most important subsystem was found and subsystem maintenance priorities were finalized [38]. Kumar and Tewari (2022) evaluated performability features of ash handling system of a coal based thermal power plant using Petri Nets based techniques. Failure and Repair rate impact has been determined. Stochastic Petri Nets (SPN) applied for modeling. Based on the results, vital part of system has been identified. Petri Nets were found to reduce the time-consuming computational efforts required by Markov and other modeling methods while also ensuring better results [39] Behnamfar et. al. (2023) presented a continuous Markov process-based reliability analysis of wireless power transfer for electric vehicle charging. To determine overall system reliability, five subsystems were individually analyzed on individual reliability. Based on the results, it was discovered that the system was highly reliable over a twenty-year lifespan, with 66.31% availability [40]. Malik et. al.
Mausoof Sheikh, P.C. Tewari
LR AND FP OF RAM APPROACHES FOR COMPLEX SYSTEMS IN RT&A, No 1 (77)
VARIOUS INDUSTRIES Volume 19, March 2024
(2023) evaluated the performability of the veneer cutting system of the Plywood Plant using a stochastic approach, and Particle Swarm Optimization (PSO) was used for the optimization of the results. Based on the analysis, maintenance engineers get help optimizing overall maintenance costs and overall production costs [41].
III. Research Gaps
In this section, the RAM approach has been used to discuss the brief findings of a literature survey conducted over the last three decades.
1. In this survey, it has been carried out that Researchers primarily focused on RAM approaches however very limited work is reported regarding RAMD (Reliability, Availability, Maintainability and Dependability) and RAMS (Reliability, Availability, Maintainability and Safety). Researchers missed the importance of effect of Dependability and Safety on Reliability. Safety is an important aspect of working in a safe environment; it also increases the motivation of team members to work in any hazardous environment, whereas dependability is also an important aspect or parameter which effected reliability in positive way by accomplishing its assigned mission or services.
2. Several researchers discussed their efforts to increase plant availability through the use of suitable maintenance procedures, policies, and different operational schedules. But very few researchers reported the relation between cost and maintenance policies with operations schedule. Factors which affected cost also need to be focused.
3. It is observed from the literature review that many techniques, including fault tree analysis, Markov models, and Lambda tau technology, have been applied. Each of these techniques has a variety of benefits and drawbacks. But there is a tool Markovian Petri Nets which can make good balance between modeling and decision making power. Application of this kind of tool is very limited in the literature survey.
IV. Concluding Remarks
Detailed overview of the literature illustrates various RAM issues, tools and techniques applied in various plants and process industries. In literature survey authors majorly focused on maintenance plan, lowering maintenance cost, production costs and increasing performability and productivity etc. In order to further improve the plant's performability, various RAM tools and techniques can be utilized in both the design and the operational stages.
In order to ensure that the systems remain operational for an extended period of time, each plant is divided into a number of systems or subsystems for effective maintenance planning. Markov Analysis, Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis, Reliability Growth Analysis, Fuzzy Model, Monte Carlo technique, Chapman Kolmogorov birth- death process, Stochastic Petri Nets, Particle Swarm Optimization (PSO) and other techniques were utilized for the analysis and modeling. The paper also discusses the advantages and disadvantages of each of these techniques.
Mausoof Sheikh, P.C. Tewari
LR AND FP OF RAM APPROACHES FOR COMPLEX SYSTEMS IN RT&A, No 1 (77)
VARIOUS INDUSTRIES Volume 19, March 2024
Acknowledgements: The National Institute of Technology, Kurukshetra Director's outstanding assistance made it feasible to complete this work. The referees' suggestions and comments allowed the authors to improve the quality of the work, therefore they would like to express their sincere gratitude for that. I wish to thank my wife and parents for their love and assistance with this work during that time.
Disclosure Statement The authors declare that they have no conflict of interest.
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