Quality and Efficiency Improvement Through Process FMEA—A Case Study

Purpose – The purpose of this paper is to present a structured way for the definitions of the Process Failure Mode and Effect Analysis (FMEA) attributes, such as potential failure mode, potential cause and potential effect, in order to make it simpler to define the controls and scores. Design/methodology/approach – This study performs, through a case study in incoming inspection of raw material, the comparison of a conventional application of the Process FMEA with a proposal based on the concepts of process approach defined by ISO 9001. Findings – Even written in a form similar to a script, the application of Process FMEA is a very complex activity and, like most quality tools, before being applied, FMEA should be clearly understood by the team. One way to facilitate this understanding is considering the sequence of events in the failures analysis to understand their causes and effects, just as are the sequences of inputs and outputs in the definition of the process approach addressed in ISO 9001. Originality/value – This paper shows a simple way to better structure Process FMEA, facilitating meetings with multidisciplinary teams.

Failure modes and effects analysis (FMEA) is a popular reliability tool in petroleum engineering. In FMEA, potential failure modes or corrective actions are evaluated, each assigned a Risk Priority Number (RPN) score, and prioritized for decision making. FMEA is also known as Failure Modes, Effects, and Criticality Analysis (FMECA), while focuses on failure modes prioritization. Despite of the popularity of FMEA and FMECA, it is not clear, how potential failure modes and corrective actions could be represented systematically, for effective decision making. In this paper, two new representations (i.e., a tree representation and a vector representation), for potential failure modes and corrective actions, are proposed. The tree representation for a potential failure mode allows its root cause(s), effect(s) and corrective action(s), together with their severity, occurrence and detection rating(s), to be represented as a three-layer tree model. The tree representation for a corrective action with similar contents is outlined too. The RPN model, together with its score, is represented as a node of the tree model. These tree models can also be represented as their associated equivalence layered-vector representations. In this paper, the usefulness of the proposed approaches is illustrated with benchmark FMEA worksheets pertaining to petroleum engineering.

Purpose:Though FMEA (Failure Mode and Effects Analysis) is becoming more widely adopted for risk assessment in radiation therapy, to our knowledge it has never been validated against actual incident learning data. The objective of this study was to perform an FMEA analysis of an SBRT (Stereotactic Body Radiation Therapy) treatment planning process and validate this against data recorded within an incident learning system.Methods:FMEA on the SBRT treatment planning process was carried out by a multidisciplinary group including radiation oncologists, medical physicists, and dosimetrists. Potential failure modes were identified through a systematic review of the workflow process. Failure modes were rated for severity, occurrence, and detectability on a scale of 1 to 10 and RPN (Risk Priority Number) was computed. Failure modes were then compared with historical reports identified as relevant to SBRT planning within a departmental incident learning system that had been active for two years. Differences were identified.Results:FMEA identified 63 failure modes. RPN values for the top 25% of failure modes ranged from 60 to 336. Analysis of the incident learning database identified 33 reported near‐miss events related to SBRT planning. FMEA failed to anticipate 13 of these events, among which 3 were registered with severity ratings of severe or critical in the incident learning system. Combining both methods yielded a total of 76 failure modes, and when scored for RPN the 13 events missed by FMEA ranked within the middle half of all failure modes.Conclusion:FMEA, though valuable, is subject to certain limitations, among them the limited ability to anticipate all potential errors for a given process. This FMEA exercise failed to identify a significant number of possible errors (17%). Integration of FMEA with retrospective incident data may be able to render an improved overview of risks within a process.

Use of failure mode and effect analysis (FMEA) to improve active surveillance for methicillin-resistant Staphylococcus aureus (MRSA) at a university-affiliated medical center

Objective To investigate IMRT planning process using the combined application of failure modes and effects analysis (FMEA) and fault tree analysis (FTA) by reference to the report of Task Group 100 of the AAPM, and stablish and optimize the quality. Methods A multidisciplinary team detailed the process mapping of IMRT planning using Eclipse TPS. The team evaluated the potential failure modes (FMs) of every process step. The evaluation was divided into two groups according to whether quality management (QM) was considered. For every FM, occurrence (O), severity (S) and detectability (D) by consensus were evaluated, and the product of O, S and D yielded the risk priority number (RPN), which permitted the ranking of the FMs. Finally, FTA was used to determine the root factors contributing to the riskiest failure modes. Results The IMRT plan process consisted of 10 major sub-processes and 33 steps, which amounted to 47 failure modes. For the group without quality management, the RPN of FMs was between 13.2-271.8, 27 of which had RPN≥80, and 18 FMs had S≥8. For the group with quality management, the RPN of FMs was between 11.2-158.4, 11 of which had RPN≥80. The difference of RPN between the two groups was statistically significant (RPN of the group without QM=101.17±66.34, RPN of the group with QM=59.54±35.64, t=8.501, P<0.05). Finally, FTA was used to determine the root factors contributing to the FMs, i. e., prescription dose definition and importing images. Conclusions The FMEA and FTA methods are operable and practical, which can systematically and comprehensively analyze the potential failures and risks existing in the process of IMRT plan. And the FMEA and FTA can contribute to establish and optimize the quality management program in radiotherapy. Key words: Intensity modulated radiotherapy; Failure modes and effects analysis; Failure tree analysis; Quality management

To develop a proactive risk assessment model for human papillomavirus (HPV) genotyping testing by integrating Failure Mode and Effects Analysis (FMEA) with quality indicators (QIs), ensuring compliance with ISO 15189:2022 and improving diagnostic accuracy. A multidisciplinary team designed and performed detailed FMEA across pre-analytical, analytical, and post-analytical phases of HPV genotyping testing. To improve objectivity, we integrated Sigma metrics into the FMEA framework through a molecular diagnostics-specific model of QIs (MQI). The FMEA model systematically identified testing phases, potential failure modes, their effects, root causes, and existing controls. Risk was quantified using Severity, Occurrence (from 1-year QI data), and Detection scores (1-5 scale). Risk Priority Numbers (RPNs) were calculated (Severity×Occurrence×Detection) to prioritize failure modes, with mandatory interventions implemented for high-risk items (RPN≥40). Five high-risk failure modes (e.g., sample misidentification, data analysis errors) were identified and successfully mitigated to acceptable levels (RPN<40) through process optimization and standardization, achieving RPN reductions of 20-80 %. We established a molecular diagnostics-specific MQI, comprising 14pre-analytical, 25 analytical, and three post-analytical phase QIs. QI-based risk assessment of 35 evaluable QIs for HPV genotyping testing revealed one high-risk QI ("Incorrect results due to information system failures") and three medium-risk QIs, all of which were addressed through corrective actions. This study developed an integrated FMEA-QI model for HPV genotyping testing, establishing both a traditional FMEA framework and a molecular diagnostics-specific MQI. The combined approach improves risk assessment objectivity and enables multidimensional analysis compared to conventional methods.

The completeness and accuracy of the front pages of electronic medical records (EMRs) are crucial for evaluating hospital performance and for health insurance payments to inpatients. However, the quality of the first page of EMRs in China's medical system is not satisfactory, which can be partly attributed to deficiencies in the EMR system. Failure mode and effects analysis (FMEA) is a proactive risk management tool that can be used to investigate the potential failure modes in an EMR system and analyze the possible consequences. The purpose of this study was to preemptively identify the potential failures of the EMR system in China and their causes and effects in order to prevent such failures from recurring. Further, we aimed to implement corresponding improvements to minimize system failure modes. From January 1, 2020, to May 31, 2022, 10 experts, including clinicians, engineers, administrators, and medical record coders, in Zhejiang People's Hospital conducted FMEA to improve the quality of the front page of the EMR. The completeness and accuracy of the front page and the risk priority numbers were compared before and after the implementation of specific improvement measures. We identified 2 main processes and 6 subprocesses for improving the EMR system. We found that there were 13 potential failure modes, including data messaging errors, data completion errors, incomplete quality control, and coding errors. A questionnaire survey administered to random physicians and coders showed 7 major causes for these failure modes. Therefore, we established quality control rules for medical records and embedded them in the system. We also integrated the medical insurance system and the front page of the EMR on the same interface and established a set of intelligent front pages in the EMR management system. Further, we revamped the quality management systems such as communicating with physicians regularly and conducting special training seminars. The overall accuracy and integrity rate of the front page (P<.001) of the EMR increased significantly after implementation of the improvement measures, while the risk priority number decreased. In this study, we were able to identify the potential failure modes in the front page of the EMR system by using the FMEA method and implement corresponding improvement measures in order to minimize recurring errors in the health care services in China.

Background: Neonatal intensive care units are prone to a variety of errors due to their special conditions. Failure mode and effects analysis (FMEA) is a method for risk assessment and management, which assesses the safety of patient care processes through its system approach. Objectives: The present study aimed to identify and assess common medical errors at Amirkola Children’s hospital NICU in 2016. Methods: This was a cross-sectional study conducted from September 2015 to February 2016 in the NICU of Amirkola Children’s Hospital in the city of Babol to identify and assess the medical errors and their effects qualitatively and quantitatively using FMEA through direct observations of the NICU processes, brainstorming, and focus group discussions (FGD). The FMEA standard worksheet was used for data collection. The collected data were analyzed using Excel 2010. Results: In this study, 4 key processes were selected through studying the care methods and brainstorming including drug administration, infection control, medical equipment use, and laboratory tests; 27 activities and 50 potential failure modes, as well as their impacts were detected and recorded in the final worksheet of FMEA. According to the calculated PRNs, 27 potential failure modes with PRN > 65 were determined as high-risk failures. The highest and lowest PRNs were, respectively, related to improper and incomplete washing and disinfecting the hands (PRN = 127) and illegibility of the lab requests for laboratory tests (PRN = 32). Conclusions: Based on the findings of this study, 57 potential failure modes in 4 key processes of the studied NICU were determined, among which 27 potential errors and failures with high risks were recognized. Therefore, it can be suggested that the senior managers and administrators should create multidisciplinary teams for patient safety at the organizational and unit levels

Proposal of a risk analysis model to diminish negative impact on patient care by preanalytical errors in blood gas analysis (BGA). Here we designed a Failure Mode and Effects Analysis (FMEA) risk assessment template for BGA, based on literature references and expertise of an international team of laboratory and clinical health care professionals. The FMEA identifies pre-analytical process steps, errors that may occur whilst performing BGA (potential failure mode), possible consequences (potential failure effect) and preventive/corrective actions (current controls). Probability of failure occurrence (OCC), severity of failure (SEV) and probability of failure detection (DET) are scored per potential failure mode. OCC and DET depend on test setting and patient population e.g., they differ in primary community health centres as compared to secondary community hospitals and third line university or specialized hospitals. OCC and DET also differ between stand-alone and networked instruments, manual and automated patient identification, and whether results are automatically transmitted to the patient's electronic health record. The risk priority number (RPN=SEV×OCC×DET) can be applied to determine the sequence in which risks are addressed. RPN can be recalculated after implementing changes to decrease OCC and/or increase DET. Key performance indicators are also proposed to evaluate changes. This FMEA model will help health care professionals manage and minimize the risk of preanalytical errors in BGA.

One of the prominent techniques in the field of Total Quality Management (TQM) is Failure Mode and Effects Analysis (FMEA). FMEA facilitates the recording of failures and analysing them to provide solutions for preventing their recurrence. During the early periods of FMEA evolution, there were two types namely Design FMEA and Process FMEA (PFMEA) in practice. In recent days, more types such as System FMEA, Service FMEA and Maintenance FMEA are being prescribed by the researchers. Meanwhile, a number of benefits of FMEA implementation have been reported. Yet, FMEA has not found its implementation in various fields. One among them is service field. This paper reports the examination of FMEA implementation in service industry. This direction of research led to the design of an improved model, named as 'Modified service FMEA'. Its implementation was examined in an Indian State Government owned passenger Transport Company. Despite certain practical hurdles, this exercise was successful in developing modified service FMEA table and pinpointing the seriousness of failures through the portrayal of Service Lost (SL) and Cost Lost (CL).

The ship-to-ship (STS) transfer of cargo operations are increasingly safe procedures, nevertheless they remain difficult and complex operations. The adverse effects of a potential accident demands a detailed and thorough work on risk and safety analysis for the transfer operations. In the light of the above, the Process Failure Mode and Effects Analysis (PFMEA) which is a branch of the traditional Failure Mode an d Effects Analysis (FMEA), is applied in combination with a Fuzzy Inference System (FIS) methodology to evaluate different risk scenarios of STS transfer of cargo operations. Although PFMEA is currently applied mainly to manufacturing processes, the aim of the paper is to implement this methodology to the ship-to-ship transfer of cargo. A significant advantage of the PFMEA is the analytical review of the STS operations. Nevertheless, serious drawbacks such as the fact that different combinations of the three implemented risk constituents may lead to the same Risk Priority Number (RPN) or the determination of the relative importance among the three risk factors of the PFMEA namely the likelihood of occurrence (O), the severity of a failure (S), and the ability to detect the potential failure (D), make the PFMEA weak and ineffective. To deal with the aforementioned weaknesses a fuzzy inference system (FIS) based on Mamdani's methodology, is applied as a remedy. The objective of this paper is to assess and evaluate different hazardous scenarios in an STS transfer operation implementing the PFMEA in combination with a FIS. To do so, a team of experts with relative experience with respect to STS transfer operations evaluated certain hazardous scenarios that have derived by the study of several guidelines and recommendations regarding these operations. The paper concludes with interesting insights emerged by the aforementioned tasks.

Purpose- Quality activities should include all product life processes, starting from the determination of customers' demands and prejudices to the service activities provided to customers. By integrating quality-oriented practices, conducting FMEA, and employing Pareto analysis, the research aims to enhance the system's reliability, efficiency, and overall performance. This, in turn, can lead to improved customer satisfaction, reduced costs, increased productivity, and a more sustainable and successful operation in the packaging department. Methodology- In order to keep up with the rapidly developing technology, to be open to innovations with developing technologies, to be in an advantageous position against competitors and ultimately to satisfy customers and fulfil their satisfaction; it is necessary to meet the demands and needs of customers without error and at low cost. Failure Modes and Effect Analysis is applied to provide the sustainability of the production system without the failures. This study focuses on failure analysis, defining failure modes, and conducting error prevention studies within the context of businesses. The aim is to achieve zero failure and zero error by implementing effective prevention techniques. By identifying the root causes of failures and errors, businesses can develop strategies and procedures to prevent them from occurring in the first place. This proactive approach helps ensure a higher level of quality, reliability, and customer satisfaction. By emphasizing the importance of error and failure prevention, businesses can strive for continuous improvement, minimize disruptions in the production system, reduce costs associated with rework or product recalls, and maintain a strong competitive position. Implementing zero failure-error and zero error-failure prevention techniques is crucial for sustaining a reliable and efficient production system. Findings- This research shows that quality is a science that people meet in reality, not simply a theoretical concept. All organizations in the universe should take their quality management systems one step further with their approach to quality processes. In this context, the concept of zero failure-error in production or service lines has become important. By applying FMEA and considering sustainability aspects, the research aims to enhance the manufacturing process, minimize risks and failures, and contribute to sustainable practices in the food industry. Conclusion- The mentioned sample study on Failure Modes and Effects Analysis (FMEA) in food packaging within the production department of a food sector enterprise in the Marmara region highlights the importance of preventing possible failure modes and their impact on the sustainability of production. One key aspect emphasized in the study is the potential reduction of food and packaging waste by minimizing packaging or substituting oil-based materials with renewable resources. By utilizing environmentally friendly food packaging, various advantages can be achieved, including a decrease in food loss and waste, as well as a reduction in the negative environmental impact associated with managing packaging materials and waste. To accomplish this, it is crucial to address food demands throughout the entire food supply chain, with particular attention to transportation and consumption stages. In order to optimize the sustainability of food and packaging systems as a whole, it is necessary to consider the product and its packaging as an integrated system. By applying FMEA and considering the potential failure modes in food packaging, the study aims to identify areas for improvement and implement measures that enhance sustainability throughout the production process. Keywords: Failure prevention, failure mode and effect analysis, quality, sustainable production. JEL Codes: M10, L15, O14

Application of failure mode and effect analysis in an assisted reproduction technology laboratory

Evidence theory is a useful tool for modeling and reasoning uncertain information inherent in experts’ evaluations, which is not handled efficiently in traditional failure mode and effects analysis (FMEA). This study proposes an integrated FMEA method that incorporates evidence theory and is applied to human reliability assessment. The human error information of a human-machine system in FMEA is described as a directed graph by a Bayesian network (BN) to assess the dependence among potential human-related failure modes. The BN is extended to propagate the epistemic uncertainty of FMEA team members, where belief mass is applied to model uncertainties in team members’ knowledge and to convert their subjective cognition into varying levels of uncertainty. Risk indexes for occurrence, severity and detection from multiple sources are defined as a special assessment state. The combination of the belief mass of different failure modes is performed using extended Dempster’s rules to avoid the influence of conflicting evidence. Finally, an application in the healthcare system is provided to verify the effectiveness of our model. A comparison with other fuzzy FMEA methods is also conducted, demonstrating the advantages of the proposed model in dealing with decision-makers’ epistemic uncertainty and potential failure mode interdependencies.

Purpose:A failure mode and effect analysis (FMEA) of skin lesions treatment process using Esteya™ device (Elekta Brachyterapy, Veenendaal, The Netherlands) was performed, with the aim of increasing the quality of the treatment and reducing the likelihood of unwanted events.Methods:A multidisciplinary team with experience in the treatment process met to establish the process map, which outlines the flow of various stages for such patients undergoing skin treatment. Potential failure modes (FM) were identified and the value of severity (S), frequency of occurrence (O), and lack of detectability (D) of the proposed FM were scored individually, each on a scale of 1 to 10 following TG‐100 guidelines of the AAPM. These failure modes were ranked according to our risk priority number (RPN) and S scores. The efficiency of existing quality management tools was analyzed through a reassessment of the O and D made by consensus.Results:149 FM were identified, 43 of which had RPN ≥ 100 and 30 had S ≥ 7. After introduction of the tools of quality management, only 3 FM had RPN ≥ 100 and 22 FM had RPN ≥ 50. These 22 FM were thoroughly analyzed and new tools for quality management were proposed. The most common cause of highest RPN FM was associated with the heavy patient workload and the continuous and accurate applicator‐patient skin contact during the treatment. To overcome this second item, a regular quality control and setup review by a second individual before each treatment session was proposed.Conclusion:FMEA revealed some of the FM potentials that were not predicted during the initial implementation of the quality management tools. This exercise was useful in identifying the need of periodic update of the FMEA process as new potential failures can be identified.