Failure Mode Effect And Criticality Analysis Method Research Articles

Application of the FMECA method on the electro-hydraulic system for drilling machine type NKH45

This article focuses on the implementation of a preventive maintenance strategy, responding to a major challenge: the search for optimization in minimizing downtime of the radial drilling machine (NKH45). Crucially positioned at the heart of the mechanical manufacturing process, this machine holds significant influence on overall production performance and availability. In consideration of the strategic importance of this equipment within the framework of the mechanical manufacturing activity, an advanced methodology, in particular FMECA (Failure Mode Effects and Criticality Analysis), is implemented. FMECA represents one of the most recommended approaches in this context, based on reliability, allowing the meticulous identification of the main causes of functional failures of equipment. FMECA is a risk prevention method. It is used to improve the reliability of a product, a process or even a means of production. It makes it possible to assess the criticality of potential failures in a system. According to the recommendations of the maintenance department of the company specializing in the construction of agricultural equipment, this study will focus on a subsystem of the electro-hydraulic part of the NKH45 radial drilling machine, we use the FMEA Analysis method (Failure Mode Effects and Criticality Analysis). Thanks to this approach, it is possible to identify the main reasons for equipment breakdowns that affect production and to classify these breakdowns in order to develop an optimal maintenance strategy aimed at: reducing the number of breakdowns, preventing breakdowns, improving the preventive maintenance, reduce downtime, improve corrective maintenance, therefore the ultimate objective of this approach is to design an optimal maintenance action plan in order to significantly minimize downtime, which slows down production flow.

Evaluation of the risk of occupational exposure to antineoplastic drugs in healthcare sector: part II - the application of the FMECA method to compare manual vs automated preparation.

Healthcare workers handling antineoplastic drugs (ADs) in preparation units run the risk of occupational exposure to contaminated surfaces and associated mutagenic, teratogenic, and oncogenic effects of those drugs. To minimise this risk, automated compounding systems, mainly robots, have been replacing manual preparation of intravenous drugs for the last 20 years now, and their number is on the rise. To evaluate contamination risk and the quality of the working environment for healthcare workers preparing ADs, we applied the Failure Mode Effects and Criticality Analysis (FMECA) method to compare the acceptable risk level (ARL), based on the risk priority number (RPN) calculated from five identified failure modes, with the measured risk level (MRL). The model has shown higher risk of exposure with powdered ADs and containers not protected by external plastic shrink film, but we found no clear difference in contamination risk between manual and automated preparation. This approach could be useful to assess and prevent the risk of occupational exposure for healthcare workers coming from residual cytotoxic contamination both for current handling procedures and the newly designed ones. At the same time, contamination monitoring data can be used to keep track of the quality of working conditions by comparing the observed risk profiles with the proposed ARL. Our study has shown that automated preparation may have an upper hand in terms of safety but still leaves room for improvement, at least in our four hospitals.

Réforme de l’accès dérogatoire : impact sur la gestion dans une PUI et identification des risques

The reform of derogatory access authorisations (DAs) on 1st July 2021 has distorted the routine of the hospital pharmacists dealing with innovative medicines that are waiting for marketing authorization or approval. There are two distinct categories of DAs: Compassionate Access Authorisations (CAAs) are granted by the French National Agency for the Safety of Medicines (ANSM) while Early Access Authorisations (EAPs) are granted at the request of pharmaceutical companies by the French National Authority for Health (HAS). All AAPs and a majority of the AACs are supported by a Protocol for Therapeutic Use and Data Collection (PTU-DC).The aim of this study is to assess the impact of the reform on pharmacy process one year following its implementation, and to identify the risks related to the new circuits.The working group, composed of three pharmacists carried out an initial assessment of the effects first measured the impact of the reform on medicine processes in DAs. They performed a comparison of the changes in their management methods: 3 months prior to the reform (M0), and 3 months (M3) and 12 months (M12) post-reform.Risks analysis was conducted using the FMEA (Failure Modes, Effects and Criticality Analysis) method. The analysis was limited to the process steps specific related to DAs drugs were analyzed. The critical severity of the risk situations identified was rated. A critical hierarchy matrix was used to establish priority actions. The priority actions to be taken were determined using the critical hierarchy matrix.Over the span of one year, the number of DAs in our establishment showed a 31.7% increase, from 41 at M0 to 54 at M12. At M0, the proportion of drugs needed inclusion via a drug- specific digital platform, specific to each drug, stood at 27% (11/41) of drugs at M0 while at M12, it rose to 52% (28/54).The percentage of PTU-DCs therefore increased by a factor of 1.7, rising from 29% (12/41) at M0 to 47% (21/45) at M3 and 60% (32/54) at M12. For orders, which are always nominative, approval depends on both the presence of the PTU-DC tracking sheet being present in 12% of PAAs, and the inclusion number in 26% of PAAs.The risk analysis shows 44 failure modes and 28 risk situations. Among the failure modes, 33 have a consequence of acceptable or tolerable criticality under control, whilst 11 are deemed of unacceptable criticality. A suitable control method exists has been identifies for 3 of them. Finally, the ranking evaluation of criticalities has highlighted 4 situations which require immediate action as a priority: delivery times, obtaining completed tracking sheets and ordering procedures.The aim of the DAs reform is to simplify access to innovative medicines. However, the reform has significant and damaging repercussions on pharmaceutical activities. Corrective measures need to be taken in conjunction with all parties involved in the circuits including laboratories and service providers (CROs), authorities and healthcare professionals.

Reliability Study of an Intelligent Profiling Progressive Automatic Glue Cutter Based on the Improved FMECA Method

This study introduces the fuzzy theory approach as an enhancement to the traditional failure mode, effect, and criticality analysis (FMECA) method in order to address its limitations, which primarily stem from subjectivity and a lack of quantitative analysis. The proposed method, referred to as FMECA improvement based on fuzzy comprehensive evaluation, aims to quantify the qualitative aspect of the analysis and provides a detailed outline of the analysis procedure. By applying the enhanced FMECA method to assess the reliability of an intelligent profiling progressive automatic rubber cutter, the hazard ranking for each failure mode of the cutter can be determined, thereby identifying areas that require reliability improvement. The analysis outcomes demonstrate that this method establishes a theoretical foundation for subsequent cutter improvement designs, enables early identification of potential failures, and consequently leads to a reduced failure rate and an enhanced reliability level for the intelligent profiling progressive automatic cutter. Furthermore, this innovative agricultural equipment reliability analysis and testing approach holds significant value in elevating the reliability standards of agricultural equipment as a whole and can be explored and implemented in other agricultural machinery contexts.

Risk Assessment and Reliability Analysis of Oil Pump Unit Based on D-S Evidence Theory

Oil pumps are crucial equipment in pipeline transportation, and their safe and reliable operation is essential for the smooth and efficient operation of the oil station and associated pipelines. The failure of oil pumps can result in significant consequences, making it crucial to evaluate their safety for effective maintenance and reliable system prediction. Failure mode, effects, and criticality analysis (FMECA) is a quantitative fault analysis technique that assigns priority to fault modes using the risk priority number (RPN). However, the RPN may not accurately express uncertainty judgments of risk factors given by multiple experts. To address this limitation, this paper proposes a novel FMECA method based on the D-S evidence theory. The method involves using interval form to obtain risk factor evaluations from experts and data combination to obtain a multi-value representation of the RPN for each fault mode. The prioritization of fault modes is optimized using confidence and fidelity distribution to eliminate multiple modes of the same level. Finally, the normalization method is used to determine the risk degree ranking of oil pump units. Overall, the proposed method is an effective and practical approach for the risk evaluation and reliability analysis of oil pump units.

Advanced FMECA Method Based on Intuitionistic 2-Tuple Linguistic Variables and the Triangular Fuzzy Analytic Hierarchy Process

Failure mode effects and criticality analysis (FMECA) is a commonly adopted approach to defining, assessing, and reducing possible failures in designs, systems, processes, products, and services. Traditional FMECA ranks the failure modes of products based on a risk priority number (RPN), which is obtained by multiplying the risk elements. Conventional FMECA has the shortcomings of badly handling unknown information and unreasonably assessing RPNs. To deal with these issues, an advanced FMECA method based on intuitionistic 2-tuple linguistic variables (I2LVs) and the triangular fuzzy analytic hierarchy process (TFAHP) is proposed. In this method, the fuzzy evaluation of risk elements given by different FMECA members is represented by I2LVs, which can efficiently handle unknown information. The TFAHP method is adopted to assess the weights of risky elements and rank the risk priorities of different failure modes. Finally, an application case of an insulated-gate bipolar transistor is used to verify the effectiveness and robustness of the proposed method.

Failure criticality evaluation of ship propeller shaft system based on Fuzzy FMECA method

The propeller shaft system is the key system for power transmission on board. The components of the system are complex, the working environment is bad, the failure modes are numerous, and the failure consequences are serious. FMECA (Failure Modes, Effects and Criticality Analysis) is difficult to accurately and quantitatively carry out criticality assessment. Therefore, in view of the complex navigation environment, the fuzzy FMECA method is used to evaluate the failure mode criticality of propeller shaft system. On the basis of FMECA, the factor set with maintainability and testability is established, and the factor level set, fuzzy evaluation matrix and factor weight set are determined, and the consistency judgment is made. Finally, the fuzzy comprehensive evaluation is carried out to obtain the accurate and quantifiable failure mode criticality ranking. Compared with the traditional FMECA method, fuzzy FMECA can consider the limited maintenance conditions and test conditions on board, accurately quantify the criticality degree, and take into account more expert opinions, so as to improve the authenticity, accuracy and repeatability of criticality assessment. Therefore, the fuzzy FMECA method can better evaluate the criticality degree of propeller shaft system, and the results can effectively guide the improvement of propeller shaft design and maintenance work.

Risks associated with the evolution in the compounding process of parenteral nutrition solutions: use of the “FMECA” method

Abstract Objectives An audit of the practices of our compounding unit was performed in 2016: areas of improvement were proposed, such as the automatization of our process. An automated compounder was acquired (MediMixmulti® MF4120R). The aim of the study was to anticipate the risks of the new process, in order to improve its security and to support the professionals during this evolution of our compounding process. Methods The Failure Modes, Effects and Criticality Analysis (FMECA) method was carried out in order to detect potential failures brought by the automatization of parenteral nutrition (PN) manufacturing in the new process. The FMECA method included four steps that were divided into five work sessions of one and a half hour each over a period of two months. A working group made up of professionals involved in the PN production process was set up (pharmacists, pharmacy resident, manager and pharmaceutical technician). Results Fifty failure modes were determined by this analysis, of which 96% could have an impact on the patient, 90% on the health staff and 74% on the product. The FMECA shows that 18 failure modes have a tolerable or unacceptable CI (CI≥100) for which it is necessary to implement preventive measures as a priority. This work also made it possible to review the barrier measures already in place for the current process. Conclusions The risk analysis allowed us to analyze the failures of both the actual and the future manufacturing processes. Once the most critical failure modes were identified, specific recommendations were proposed and an improvement plan was established. First, the compounder needs to be fully qualified. Then, the quality manual of the PN process will be reviewed and updated. Once these steps are completed, the pharmacy professionals (pharmacists, pharmacy technicians) will be trained and the PN production will be performed using the automated compounder on a daily basis.

Integrated RMA with FMECA analysis using a graphical inteface: case study recycling iso-butane pump (CP2K)

The objective of our work is the implementation of a new approach for the dependability enhancement of a recycling iso-butane pump (Skikda CP2K petrochemical plant) based on automateddependability analysis system including the automation of the RMA (Reliability, Maintainability, Availability) study and FMECA (Failure Mode Effect and Criticality Analysis) method. After the system description, we present briefly the principle of the automated method. The system analysis in degraded mode is realized by using FMECA method. This automated analysis brings out the different failure modes, their causes and their consequences of each component. The result is risks minimization and reliability enhancement of the considered system.

Controlling Risks in the Compounding Process of Individually Formulated Parenteral Nutrition: Use of the FMECA Method (Failure modes, effects, and Criticality Analysis)

AbstractParenteral nutrition (PN) in the neonatal intensive care unit (NICU) involves a succession of risky processes. The objective was to identify and prioritize the risks associated with PN in order to improve the quality of the pathway. A failure modes, effects, and criticality analysis (FMECA) was used to identify potential PN pathway failure modes. A multidisciplinary working group conducted a functional analysis of the processes, then listed the failure modes (FM). The FM criticality was assessed on a scale from 1 to 5 for occurrence (O), severity (S), and detection (D). The risk priority number (RPN), ranging from 1 to 125, was calculated. The FMECA identified 99 FM (prescription (n=28), preparation (n=48), and administration (n=23)). The median RPN was 12, with scores ranging from 3 to 48. 25 % of the scores had an RPN>21.75.Among them, 12 were associated with prescription FM, 5 were associated with FM related to preparation and 8 were associated with a FM linked to administration. It allowed us to prioritize areas of potential quality improvement for parenteral nutrition of the preterm infant. The results demonstrated the need for the presence of a clinical pharmacist in the NICU to ensure the quality of PN process.

A Novel Approach to Support Failure Mode, Effects, and Criticality Analysis Based on Complex Networks

Failure Mode, Effects and Criticality Analysis (FMECA) is a method which involves quantitative failure analysis. It systematically examines potential failure modes in a system, as well as the components of the system, to determine the impact of a failure. In addition, it is one of the most powerful techniques used for risk assessment and maintenance management. However, various drawbacks are inherent to the classical FMECA method, especially in ranking failure modes. This paper proposes a novel approach that uses complex networks theory to support FMECA. Firstly, the failure modes and their causes and effects are defined as nodes, and according to the logical relationship between failure modes, and their causes and effects, a weighted graph is established. Secondly, we use complex network theory to analyze the weighted graph, and the entropy centrality approach is applied to identify influential nodes. Finally, a real-world case is presented to illustrate and verify the proposed method.

An Extended FMECA Method and Its Fuzzy Assessment Model for Equipment Maintenance Management Optimization

The failure mode, effect and criticality analysis (FMECA) is a famous bottom-up analytical method for quantifying and ranking critical failures of a product normally at its design stage. At present, as the importance of equipment maintenance increases in industry, FMECA is often applied in maintenance management. In practical cases, equipment is composed of different components, and its maintenance optimization should consider requirements of reliability, availability and costs together. This paper proposes the method called the extended failure mode, effect and criticality analysis (e-FMECA) for equipment maintenance management optimization on the basis of the FMECA theory. This method gives the procedure of analyzing the risks of different failure modes associated with reliability, availability and maintenance costs of equipment. In order to measure these risks of reliability, availability and maintenance costs quantitatively, a fuzzy risk priority method for e-FMECA is developed. Finally, the case study of the e-FMECA method in terms of metro rolling stocks is given. The proposed e-FMECA might be beneficial for selecting the maintenance strategies, maintenance polices and maintenance optimizing objects for maintenance management optimization.

Failure modes and criticality analysis of the preliminary design phase of the Mars Desert Research Station considering human factors

This work presents an extension to the traditional FMECA (Failure Modes, Effects and Criticality Analysis) method to include the effects of human factors concerning accessibility/repairability, probability of contact and degree of contact. The authors refer to this extension to the traditional FMECA as the Human Design Approach (HDA). All data used in this study was collected during the stay of two of the authors at the Mars Desert Research Station (MDRS) in the Utah desert, USA. The MDRS is a laboratory for carrying out research in order to understand and investigate the difficulties of how to live and work on another planet. The results show that following the HDA can enhance the safety and reliability of the MDRS. There is still a significant amount of research required concerning reliability analysis of the space habitat in terms of the selection of optimum designs, the modification of systems, as well as access, inspection and maintenance strategies, human factors and environmental impacts. This preliminary study will assist the design engineers with the selection of an optimum configuration for space habitats and can be extended to any case where humans can influence function of an environment.

TITIK KRITIS PRODUKSI MINYAK SAWIT BERKELANJUTAN DI PT.XYZ

The change of business paradigm towards sustainable development requires industry players to produce palm oil in a sustainable manner. One of them is to follow the guidelines of Principles and Criteria (PnC) of sustainable palm oil production endorsed by Roundtable on Sustainable Palm Oil (RSPO). Researchers interested to know the constraints (critical point) of the company in meeting all the principles and criteria for sustainable palm oil production. Identification of critical points will have an important role to know how far the performance and constraints faced by the company in fulfilling all the principles and criteria to produce sustainable palm oil. The purpose of this study is to analyze the critical point on sustainability criteria and indicators in PT.XYZ. Methods of data collection research conducted by interview and observation in the field. Researchers use RSPO Principles and Criteria (PnC) parameters as parameters of sustainable palm oil production implementation. Method of data analysis using FMECA (Failure Modes, Effects and Criticality Analysis ) method with 2 stages, namely FMEA (Failure Mode and Effects Analysis) and CA (Criticality Analisis). The FMECA analysis shows that there are 5 critical criteria and 6 critical indicators in fulfilling all the principles and criteria of sustainable palm oil production in PT.XYZ.

Reliability Analysis of Isothermal Forming Hydraulic Press Body Based on FMECA

As a special kind of advanced aerospace sheet metal forging equipment, more and more attention has been paid to the design and development of isothermal forming hydraulic press. Failure Modes, Effects and Criticality Analysis (FMECA) mathod is an effective technique to improve the reliability of products. To improve the reliability of isothermal forming hydraulic press, this paper propose FMECA method to predict all potential failure modes, causes and effects in the design stage. Then improvement and preventive measures are accordingly put forward to alleviate or eliminate failure effects. Finally, the reliability of hydraulic press body is improved using the FMECA mathod, which also provides a basis for reliability analysis and design of other systems.

Determining critical infrastructure risks using social network analysis

PurposeThe purpose of this paper is to develop a novel risk analysis method named fuzzy critical risk analysis (FCRA) for assessing the infrastructure risks from a risk-community network perspective. The basis of this new FCRA method is the integration of existing risk magnitude analysis with the novel risk impact propagation analysis performed in specific infrastructure systems to assess the criticality of risk within specific social-infrastructure interrelated network boundary.Design/methodology/approachThe FCRA uses a number of scientific methods such as failure mode effect and criticality analysis (FMECA), social network analysis (SNA) and fuzzy-set theory to facilitate the building of risk evaluation associated with the infrastructure and the community. The proposed FCRA approach has been developed by integrating the fuzzy-based social network analysis (FSNA) method with conventional fuzzy FMECA method to analyse the most critical risk based on risk decision factors and risk impact propagation generated by various stakeholder perceptions.FindingsThe application of FSNA is considered to be highly relevant for investigating the risk impact propagation mechanism based on various stakeholder perceptions within the infrastructure risk interrelation and community networks. Although conventional FMECA methods have the potential for resulting in a reasonable risk ranking based on its magnitude value within the traditional risk assessment method, the lack of considering the domino effect of the infrastructure risk impact, the various degrees of community dependencies and the uncertainty of various stakeholder perceptions made such methods grossly ineffective in the decision-making of risk prevention (and mitigation) and resilience context.Research limitations/implicationsThe validation of the model is currently based on a hypothetical case which in the future should be applied empirically based on a real case study.Practical implicationsEffective functioning of the infrastructure systems for seamless operation of the society is highly crucial. Yet, extreme events resulted in failure scenarios often undermine the efficient operations and consequently affect the community at multiple levels. Current risk analysis methodologies lack to address issues related to diverse impacts on communities and propagation of risks impact within the infrastructure system based on multi-stakeholders’ perspectives. The FCRA developed in this research has been validated in a hypothetical case of infrastructure context. The proposed method will potentially assist the decision-making regarding risk governance, managing the vulnerability of the infrastructure and increasing both the infrastructure and community resilience.Social implicationsThe new approach developed in this research addresses several infrastructure risks assessment challenges by taking into consideration of not only the risk events associated with the infrastructure systems but also the dependencies of various type communities and cascading effect of risks within the specific risk-community networks. Such a risk-community network analysis provides a good basis for community-based risk management in the context of mitigation of disaster risks and building better community resilient.Originality/valueThe novelty of proposed FCRA method is realized due to its ability for improving the estimation accuracy and decision-making based on multi-stakeholder perceptions. The process of assessment of the most critical risks in the hypothetical case project demonstrated an eminent performance of FCRA method as compared to the results in conventional risk analysis method. This research contributes to the literature in several ways. First, based on a comprehensive literature review, this work established a benchmark for development of a new risk analysis method within the infrastructure and community networks. Second, this study validates the effectiveness of the model by integrating fuzzy-based FMECA with FSNA. The approach is considered useful from a methodological advancement when prioritizing similar or competing risk criticality values.

Experts’ knowledge renewal and maintenance actions effectiveness in high-mix low-volume industries, using Bayesian approach

Increasing demand diversity has resulted in high-mix low-volume production where success depends on the ability to quickly design and develop new products. This requires sustainable production capacities and efficient equipment utilization which are ensured through appropriate maintenance strategies. Presently, these are derived from experts' knowledge, capitalized in FMECA (failure mode, effect and criticality analysis), and effective maintenance procedures. Abu-Samah et al. (Failure prognosis methodology for improved proactive maintenance using bayesian approach. In: 9th IFAC symposium on fault detection, supervision and safety for technical processes. Paris, France, 2015) found increasing unscheduled breakdowns, failure durations and number of repair actions in each failure as the key challenges while sustaining production capacities in complex production environment. Obviously, maintenance based on the historical knowledge is not always effective to cope up with an evolving nature of equipment failure behaviors. Therefore, this paper presents an operational methodology based on Bayesian approach and an extended FMECA method to support experts' knowledge renewal and maintenance actions effectiveness. In the proposed methodology, FMECA files capitalize and model experts' existing knowledge as an operational Bayesian network (O-BN) to provide real-time feedback on poorly executed maintenance actions. The accuracy of O-BN is monitored through drifts in maintenance performance measurement (MPM) indicators that result in learning an unsupervised Bayesian network (U-BN) to discover new causal relations from historical data. The structural difference between O-BN and U-BN highlights potential new knowledge which is validated by experts prior to updating existing FMECA and associated maintenance procedures. The proposed methodology is evaluated in a well-reputed high-mix low-volume semiconductor production line to demonstrate its ability to dynamically renew experts' knowledge and improve maintenance actions effectiveness.

WITHDRAWN: Failure analysis of tyre production process using FMECA method

Abstract This paper presents a failure analysis of real industry case using FMECA method. The case study is conducted in a tyre manufacturing industry focusing on the machine components mechanism failures. Field failures record data are systematically analyzed to identify and classify the failure modes, effects and determined the criticality index on the subject under study. The details of step-by-step in applying FMECA according to the case study, the resultsand discussion have been presented accordingly. It is then concluded and proved that the FMECA method is beneficial to rank and prioritize failures systematically and thus help engineering team to perform the improvement project based on the right problem. Keywords : Failure analysis, Industry case study, Failure Mode Effect and Criticality Analysis (FMECA) 1. Introduction Every machine and process in daily manufacturing operations has it owns modes of failure. These modes of failures are where the state of termination of the ability of an item of any part, component, device, subsystem, functional unit, component or system that can be individually considered, to perform a required function takes in place as per definition by SS-EN 13306 [1]. In short, there are two types of failure which are the functional failure and the potential failure. A functional failure is the inability of an item or the component containing itto meet a specified performance standard meanwhile the potential failure is an identifiable physical condition which indicates a functional failure is imminent by referring to Nowlan and Heap [2].

A novel general risk assessment method using the soft TOPSIS approach

Risk assessment is a systematic method of identifying and preventing product design and production planning process problems. It is a critical step in the risk management procedure. Most current risk assessment tools use failure mode, effects, and criticality analysis (FMECA) to evaluate the risk of failure. The traditional FMECA method uses linguistic terms to represent the severity, occurrence, and detection on a numerical scale from 1 to 10. It cannot deal with the incomplete information of attribute data. In a high technology industry, in order to meet the market’s real demand and provide a suitable product, an original design manufacture (ODM) company offers customized design, production, and integration service to satisfied clients’ needs. However, there are many uncertainties, imprecise, vague, and subjective information in the process of collecting data of an ODM company that will increase the difficulty of risk assessment. It cannot be fully solved by the traditional FMECA method. Therefore, considering both tangible and intangible criteria, this paper proposes a soft technique for order preference by similarity to ideal solution (TOPSIS) approach to solve the risk assessment problem. At last, a case study of ODM notebook module development is provided to demonstrate this practicability and rationality of the proposed method under incomplete information. Compared with existing traditional RPN and TOPSIS methods, the proposed method can deal with group decision-making problems in a more efficient manner.

Predictive maintenance using FMECA method and NHPP models

Most of predictive maintenance technologies are inaccessible to small scale and medium scale industries due to their demanding cost. This paper proposes a predictive maintenance policy using failure mode effect and criticality analysis (FMECA) and non-homogeneous Poisson process (NHPP) models which require minimal use of advanced monitoring technologies and sophisticated data acquisition systems. Most of the repairable systems show long term reliability degradation with repeated overhauls. Here, critical component of a system or machinery exhibiting sad (deteriorating) trend is used as an indicator to predict overall maintenance time of a system. Firstly, the component to be used as an indicator for predictive maintenance is chosen using FMECA method, in which the most critical component is chosen. Secondly, the failure data of the chosen component is analysed using NHPP models and based on analysis of the data, relevant NHPP model is selected and finally, the Mean Time Between Failure (MTBF) of the component is compared with the threshold mean time between failure [MTBF(Th)] of the component to decide the overall maintenance time for the system. The developed methodology is validated on an overhead crane in a steel manufacturing company.