FMECA Analysis Research Articles

FMECA and Failure Data Analysis of Domestic Wheeled Walking-Aid

The gradual acceleration of the aging population in China has led to an increased demand for mobility aids, and the reliability of domestic wheeled walking-aid is one of their important attributes, but there is little research on the reliability of mobility aids. This paper conducts the failure mode, effects and criticality analysis on domestic wheeled walking-aid. By collecting, collating and analyzing the 26 failure modes, the key modules are the chassis and the lifting system. The key modules are obtained, and the failure data is analyzed to find out that the lifetime distribution model is log-normal and the 0.95 lower confidence limit for reliability life of product t 0.9 is 2489.4 hours. The study aims to provide ideas for the reliability analysis of other active medical devices and calls for the formation of a reliability study review point for the industry that meets the requirements of Chinese medical device regulations.

The Reliability Analysis and FMECA Analysis of Cryogenic Distribution System for Cryogenic System of HL-3

The Reliability Analysis and FMECA Analysis of Cryogenic Distribution System for Cryogenic System of HL-3

S-FMECA: A Novel Tool for Sustainable Product Design - Additive Manufacturing

The choices made in the early design stage (EDS) will largely define the environmental impacts of a product. The purpose of this paper is to develop an eco-design method used for assessing semi-quantitatively the sustainability of an additively manufactured product since the EDS. This article presents a semi-quantitative method to support EDS-conscious environmental decisions. A novel Sustainable-Failure Mode, Effect, and Criticality Analysis (S-FMECA) tool is developed to support designers in the conceptual design phase, to guide the choices, and to provide a valuable evaluation of the future additively manufactured product. Through the integration of the environmental aspects in FMECA analysis, systematic prevention of errors, and enhancement of sustainability since the EDS would be the main advantage of this tool.

Perbaikan Sistem Perawatan Mesin Forming dengan Metode FMECA dan RCM Berdasarkan Analisis OEE Pada PT XYZ

PT XYZ is a manufacturing company operating in the automotive sector. One of this company's flagship products is train brake pads. In production activities there are several machines, including forming machines. Based on secondary data, it is known that this forming machine has the largest contribution to product defects. This research was conducted using the OEE, FMECA, and RCM methodology. The OEE methodology is used to identify the level of effectiveness of forming machines, the FMECA methodology is used to identify critical machines, and the RCM methodology is used to determine machine repair and maintenance intervals and determine the selection of tasks in maintenance activities. The research results show that the OEE value of the forming machine is 83.79%, which is below standard. Based on the FMECA analysis, it is known that there are 2 components that are classified as critical components, namely sheet loading and molding. So, an analysis of maintenance scheduling was carried out on these two components, it was found that the sheet loading component required maintenance every 352,016 minutes and component replacement every 11.58 days with task selection in the form of a directed time. On molding components, maintenance is carried out every 328.60 minutes and component replacement every 11.46 days with the task selection being failure discovery.

Analysis of coupling system failures on freight trains

This paper presents an analysis of train coupling failure that led to trains break apart on the Serbian Railways over 10 years period. Train coupling failure of freight trains with single locomotives was considered. The analysis was done based on accident data combine with FMECA risk assessment. As a result distribution of failure along the train, driving regime and velocity were obtained, as well as the frequency of failure concerning the length and mass of the trains, load status, etc. The systematization of coupling failure helped to establish conditions leading to failure and to define the parameters causing it. Risk factors for coupling failure were determined using FMECA risk assessment. Preventive measures are recommended for the revision of maintenance. Risk analysis of coupling system failure can be different depending on the time of analysis (regulations, exploitation conditions) and the applied maintenance practice. FMECA analysis applied to train coupling systems based on regulation shows different permissible risk values that don't match exploitation data.

基于数据挖掘技术的谷物收获机割台可靠性分析

With the rapid development of agricultural modernization, the reliability of agricultural machinery had become the key to improving the development level of agricultural machinery and equipment in China. Aiming at the problems of subjectivity, fuzziness, high test cost and difficult data acquisition in the Failure Mode, Effects and Criticality Analysis of grain harvester, an FMECA analysis method based on Data Mining Technology was proposed in this paper. In this study, Python 3.7.8 is used to collect and process the fault data of the header of the grain harvester. According to the data analysis, it is concluded that the fault rate of the cutter component is the highest in the whole system. Then the agreed hierarchy of header was analyzed by Analytic Hierarchy Process, and it was concluded that the blade part failure mode was the most hazardous. The results show that the grain harvester should strengthen the inspection and maintenance of the blade of the cutter in the working process. The research results showed the feasibility of the FMECA method based on Data Mining Technology in agricultural machinery reliability analysis, which opens up a new idea of grain combine harvesters’ reliability analysis and provides the possibility to obtain the reliability level of harvesters with low input.

Prolonged degradation and reliability assessment of installed modules operational for 10 years in 5 MW PV plant in hot semi-arid climate

The current work presents detailed degradation and reliability assessment of installed PV modules in grid tied 5 MW solar PV plant in hot semi-arid climate. Defects and failures of 336 modules out of 2078 visually inspected c-Si modules with 10 years of operational period in hot semi-arid climate is evaluated using FMECA statistical tool and I-V curve measurement. The novelty of the research conducted is presenting long term degradation of PV modules in utility scale PV plant installed for 10 years in outdoor environment in remote location, carrying FMECA analysis of visually degraded modules along with on-field electrical characterization. Correlation of identified defect and failures with electrical parameters of PV module is also presented. The results obtained indicate light and dark EVA discoloration, EVA discoloration with cell and metallization discoloration, snail trails, backsheet burnt, glass breakage with or without cell cracks to be the most dominant and frequently occurring defects and failures with high severity. The inspected plant has considerable degradation as compared to other plants in the same area in hot semi-arid climate and therefore degradation investigation of the plant is important in identifying various possible causes of observed degradation and studying impact of degradation on module performance. Based on the results obtained and analysis conducted, several important preventive and corrective measures along with important recommendations have been enlisted for mitigating failures and improving the system performance.

A novel decision support system for managing predictive maintenance strategies based on machine learning approaches

Nowadays, the industrial environment is characterised by growing competitiveness, short response times, cost reduction and reliability of production to meet customer needs. Thus, the new industrial paradigm of Industry 4.0 has gained interest worldwide, leading many manufacturers to a significant digital transformation. Digital technologies have enabled a novel approach to decision-making processes based on data-driven strategies, where knowledge extraction relies on the analysis of a large amount of data from sensor-equipped factories. In this context, Predictive Maintenance (PdM) based on Machine Learning (ML) is one of the most prominent data-driven analytical approaches for monitoring industrial systems aiming to maximise reliability and efficiency. In fact, PdM aims not only to reduce equipment failure rates but also to minimise operating costs by maximising equipment life. When considering industrial applications, industries deal with different issues and constraints relating to process digitalisation. The main purpose of this study is to develop a new decision support system based on decision trees (DTs) that guides the decision-making process of PdM implementation, considering context-aware information, quality and maturity of collected data, severity, occurrence and detectability of potential failures (identified through FMECA analysis) and direct and indirect maintenance costs. The decision trees allow the study of different scenarios to identify the conditions under which a PdM policy, based on the ML algorithm, is economically profitable compared to corrective maintenance, considered to be the current scenario. The results show that the proposed methodology is a simple and easy way to implement tool to support the decision process by assessing the different levels of occurrence and severity of failures. For each level, savings and the potential costs have been evaluated at leaf nodes of the trees aimed at defining the most suitable maintenance strategy implementation. Finally, the proposed DTs are applied to a real industrial case to illustrate their applicability and robustness.

Application of system analysis and preventive maintenance on cigarette packer line

The use of system analysis and preventive maintenance in today’s industry becomes a necessity as it increases equipment availability. These methods reduce the frequency of failures. The objective of this article is to present a case study for improving the reliability and availability of a production group in an industrial enterprise. Next, we present an improvement in maintenance. Finally, we present and discuss the application of preventive maintenance. Through an industrial manufacturing model, we will combine three tools; SADT modelling, the FMECA analysis and the Pareto diagram to arrive at an optimal maintenance approach that will be a decision support tool in order to minimize the repair costs and the downtime of the system.

An approach to a maintenance plan for a turbine of hydroelectric power plant. Optimisation based in RCM and FMECA analysis

<p class="JARTEAbstract">The generation of electric energy is a continuous process of great strategic importance in the development of countries. The evolution in the last decades of different environmental control protocols at a global level has influenced the rise of renewable energies with low impact on the environment. These reasons make it important that this process has an effective maintenance management system that guarantees adequate reliability, availability and useful life of its assets. This article describes the implementation of the optimization of the traditional preventive maintenance that is carried out in regular temporary intervals with unavailability of the hydroelectric group, to be able to take advantage of the data base of operation of the group (failure modes, criticality, application of maintenance strategies to condition and maintenance 4.0, etc…).</p>

Fuzzy FMECA analysis of radioactive gas recovery system in the SPES experimental facility

Selective Production of Exotic Species is an innovative plant for advanced nuclear physic studies. A radioactive beam, generated by using an UCx target-ion source system, is ionized, selected and accelerated for experimental objects. Very high vacuum conditions and appropriate safety systems to storage exhaust gases are required to avoid radiological risk for operators and people. In this paper, Failure Mode, Effects, and Criticality Analysis of a preliminary design of high activity gas recovery system is performed by using a modified Fuzzy Risk Priority Number to rank the most critical components in terms of failures and human errors. Comparisons between fuzzy approach and classic application allow to show that Fuzzy Risk Priority Number is able to enhance the focus of risk assessments and to improve the safety of complex and innovative systems such as those under consideration.

PO-1944: FMECA analysis of VMAT prostate treatment

PO-1944: FMECA analysis of VMAT prostate treatment

Hybrid risk analysis model for analyzing the urban infrastructure risk

The operation of urban infrastructure (UI) system is crucial for supporting societal needs. In the practical development of UI system, a wide range of uncertain and potential extreme event as well as disasters will inevitably result in risks to UI system. Thus, the inherent risks exert significant consequences on the dependent community. Conventional Risk Analysis (RA) methods tend to focus solely on the magnitude issue. Considering the complex nature of risk and its impact on the community, little attention has been given to analyze the risk and its impact in an integrated manner. This research aims to develop a novel hybrid RA model for analyzing significant risk in terms of its' magnitude and impact pattern to community. The hybrid RA model integrates the analysis between Fuzzy-based FMECA and Social Network Analysis. The applicability of the model is demonstrated using a case study of urban water supply infrastructure. Following the data analysis and discussion, it is found that the model capable to capture the risk impact which is characterized not only by its' magnitude but also by the degree of association between individuals and risks, and the dynamic of the spread of impact. This research contributes to the body of knowledge by delivering theoretical framework that can promote UI decision-makers towards analyzing and better understanding UI risk and its’ impact, and practical tools that could potentially provide a further path for developing mitigation strategy and policies toward addressing complex UI risks, and thus enhance the resilience of both UI system and the communities.

Failure modes, effects and criticality analysis of a 3kW@4.5K helium refrigerator

The comprehensive research facility for key systems of fusion reactors was included in the “13th Five-Year Plan” priority project in China. In order to meet the requirements of cryogenic testing of large superconducting magnets, it is proposed to build a 3kW@4.5K refrigerator and carry out research on 3kW@4.5K superfluid helium cryogenic system. In order to evaluate the reliability of the 3kW refrigerator, the FMECA analysis was performed on the helium refrigerator. The refrigerator system is divided into three subsystems: the compressor system, the monitoring and control system and the cold box, to identify the failure mode and the impact on the refrigerator system related functions. The critical value is calculated and the critical matrix is drawn by the severity and the occurrence of the rating criteria. Identify the parts with high and medium risks and propose corresponding risk mitigation measures.

Maintenance system of semi-trailer and risk priority number

The new maintenance system of semi-trailer combination as a most used road freight transport means is the subject of interest in this article. The real experiences from practice and creation of the FMEA analysis of the system using software support are the basis of wear and damage analysis of air brake system components used on the semi-trailer combination. The desire to improve market position of the company, customer satisfaction, but also the product specifications, government regulatory requirements, agency recommendations, and legal implications are the grounds for continuous improvement of the product quality, reliability and safety. These reasons push the product manufacturers to perform risk analyses, which helps them identify and minimize system failures during the life cycle of product. One of the risk analysis techniques recommended by international standards to identify possible failure causes is the FMEA methodology. It helps to locate the failures and reduce their consequences, so that the intended function of the machine is fulfilled. In this paper was presented the wear and damage analysis of individual components of air brake system and creating of the FMECA analysis for semi-trailer combination. Base on them, new methods to detect failures of components of air systems, preventive measures and set up of a new planned preventive maintenance system for air brakes was designed. The cost of the proposed maintenance system is 2.2 times higher than the cost of the current maintenance system, but it minimizes the failures and their consequences (traffic accidents).

ANALYSIS OF DETERMINING CRITICAL COMPONENTS USING FMECA METHOD IN SEAWATER PUMP OF DIESEL GENERATOR CATERPILLAR 3412

The seawater pump on the Caterpillar 3412 Diesel Generator is one of the important component to make the Diesel generator can work well. This section serves to circulate seawater for the heat transfer process. The seawater pump is part of a cooling system of the engine which keeps the engine temperature from being too overheat. Seawater pumps with continuous operational conditions, resulting in reduced component reliability. This study applies the FMECA method to identify opportunities for failure at the seawater pump. From the calculation of FMECA, it is obtained an assessment of the level of risk from a failure model that can give priority scale to preventive maintenance that can be done in the future. FMECA analysis of 27 components in seawater pump on the Diesel Generator, found 7 components that had RPN values above the average. The following are the 4 components with the highest RPN value, namely Shaft (7C-3493) RPN value 420,44; Key (175-6716) RPN value 300,31; Bearing Inner (4M-6107) RPN value 285 and Bearing Roller (3N-8463) RPN value 253,13. Components that have high RPN values require more attention, such as routine checks and periodic maintenance.Keyword: Seawater pump, Caterpillar 3412 Diesel Generator, FMECA, RPN.

4. Application of the FMECA analysis in breast radiotherapy with active breath hold

Purpose The Deep Inspiration Breath Hold (DIBH) technique was introduced in order to freeze the breathing motion in a mid-inhale position with a computer controlled valve, with the purpose of lowering heart dose in left breast radiotherapy. A training project with FMECA analysis was started, aiming to write and implement a protocol, improved by proactive clinical risk analysis and feedback from the operators (radiotherapists, radiographers and medical physicists). Methods and materials At first, few operators were involved to take knowledge and dexterity with the system. They became the tutors and the core of the improvement group for the subsequent training project. The project was comprised of four stages: (1) implementation of the technique (tutors); (2) field training (tutors and operators); (3) training course on FMEA/FMECA analysis (all operators and clinical governance department); (4) implementation of the FMECA analysis in left breast radiotherapy DIBH treatments (tutors and FMEA-workgroup; the FMEA workgroup consisted of these professional roles: radiotherapists, radiographers, medical physicists and clinical governance area’s physicians). Results The outputs for each stage were: (1) redact the protocol and the training checklist; (2) training of all operators and application of the self-evaluation checklist; (3) understanding the clinical risk principles; (4) application of the FMEA analysis, data processing and final report. The self-evaluation checklist was comprised of 37 targets, with achieved/partially-achieved/not-achieved check boxes. The FMEA table was comprised of 48 activities, subdivided in 5 phases (DIBH-suitable-patients detection, treatment simulation, planning, radiotherapy treatment delivery, quality control), with pertinent Risk Probability Numbers associated. Points 1–3 were completed, while completion of point 4 is expected for the first half of 2018. Conclusion The application of the FMEA/FMECA method allowed us to introduce proactive methods to analyze and manage the clinical risk related to the introduction of the new DIBH technique. The FMEA/FMECA method was included in a training project which allowed to obtain feedback from all the involved operators, improving the understanding of the work process, the skill and safety in the practical use and the redaction of a multidisciplinary protocol.

A priori indicator identification to support predictive maintenance: application to machine tool

Predictive maintenance requires the identification of the parameters to be monitored and sensors to be implemented on a system. In industrial companies, usually such goal is tackled by implementing sensor and after see if one can extract some indicators related to degradation. The lack of methodology makes the benefits of predictive maintenance to be lower than expected. Indeed, its implementation is done by “the rule of the thumb” using some metrics “a posteriori” in order to show the relevancy of the instrumentation. Hence, a structured approach is required in order to define “a priori” the most suitable indicators to be relevant for degradation monitoring and related instrumentation to be implemented. Thus, the paper presents a methodology based on a coupled approach of FMECA and Hazard Operability analysis (HAZOP) which aim is to contribute to the deployment of predictive maintenance strategies by clearly identify pertinent indicator. This approach is based on the formalization of concepts of knowledge which permit to constitute the first pillars of predictive maintenance approach. The formalization step leads to promote meta-model and reference model of knowledge. The feasibility and the interests of such approach are shown on the case of machine tool GROB G520 located in RENAULT Cléon Factory. It consists in particularizing the reference model proposed to identify automatically and in a more efficient the right indicators/parameters on which the predictive maintenance of this machine tool should be based.

TCH-037 Risk Assessment of Cytotoxic Drug Compounding: Manual Vs. Robotic

BackgroundErrors in cytotoxic drug compounding can cause serious harm to patients due to the low therapeutic ratio. Robots are intended to decrease the risk of medication errors through 100% verification...

Proactive evaluation of clinical risk: a FMECA analysis in pediatric chemotherapy.

In 2010-2011, we used FMECA to prospectively assess risk-management in chemotherapy of children with cancer, in a third level Italian children's Hospital (Ospedale Pediatrico Bambino Gesù; OPBG). We designed a flow chart representing the entire process; we described potential failure points for each step of the process, as well as their potential underlying causes. We calculated the risk priority number (RPN) of each failure point based on the severity of the failure, the frequency of occurrence, and the likelihood of detecting the failure prior to completion of the process. All FMECA activities were supported by a web-based tool. The highest RPN values were observed for failure points of the paper-based chemotherapy medication orders sent from clinicians to Pharmacy, the transcription of the orders into the Pharmacy paper-based work-sheet for medication preparation, and the selection of medications to be used for chemotherapy preparation. Causes of these failures were mostly related to illegible or incomplete handwriting. As a consequence of these results, the implementation of an electronic ordering process for children's chemotherapy medications was proposed as risk-reducing action.