Failure Mode And Effect Analysis Tool Research Articles

Assessing the Risk of Occupational Hazard Using the FMEA Tool Among Hospital Staff at Multispecialty Hospital

Considering the importance of occupational hazard assessment, this study has been performed to identify the risks for employees who especially undergo a major occupational hazard that affects their efficiency and productivity. The study aimed to assess the risk of occupational hazard using Failure Mode and Effect Analysis (FMEA) and strategy to modify the healthcare packages provided by the hospital to the staff. A survey and personal interviews were done at a private multispecialty hospital in Chennai using a descriptive study methodology. The survey included 150 hospital employees from four departments: CSSD (6 participants, covering all available samples), Maintenance (41 participants, chosen at random), Nursing (60 participants, chosen at random), and Housekeeping (43 participants, chosen at random). To collect data, a standardized questionnaire aligned with the Occupational Safety and Health Administration (OSHA) was used (https://www.osha.gov/laws-regs/standardinterpretations/1987-08-06). In addition, unstructured personal interviews with key workers were undertaken. The data revealed that CSSD workers encountered most of the stated dangers, with 100% admitting to workplace risks such as needle sticks, chemical allergies, the risk of burns, and awkward ergonomic postures. Maintenance workers reported a 54% risk of pain and discomfort, 32% of sleep loss following night shifts, and 37% of chemical risks. Nursing personnel cited poor ergonomic posture (68%) as a key concern, followed by sleep loss (62%), and the risk of cuts (52%). Housekeeping personnel cited hazards of falls (69%), poor ergonomic postures (40%), and infectious disease exposure (31%). The study emphasizes the need to address occupational health risks in healthcare settings by thoroughly reviewing the many occupational health hazards that impact healthcare professionals. However, it is important to remember that the study relied on data from the previous six months, potentially leaving out undetected risks. Furthermore, the study emphasized the impact of these dangers on healthcare personnel, emphasizing the problem of events being underreported inside the institution. Notably, the study emphasized the importance of paying close attention to occupational dangers such as needle sticks, chemical exposure, burns and ergonomic concerns in healthcare professionals' daily health management.

Proposal of a facilitating methodology for fuzzy FMEA implementation with application in process risk analysis in the aeronautical sector

PurposeThis study aims to propose a facilitating methodology for the application of Fuzzy FMEA (Failure Mode and Effect Analysis), comparing the traditional approach with fuzzy variations, supported by a case application in the aeronautical sector.Design/methodology/approachBased on experts' opinions in risk analysis within the aeronautical sector, rules governing the relationship between severity, occurrence, detection and risk factor were defined. This served as input for developing a fuzzyfied FMEA tool using the Matlab Fuzzy Logic Toolbox. The tool was applied to the sealing process in a company within the aeronautical sector, using triangular and trapezoidal membership functions, and the results were compared with the traditional FMEA approach.FindingsThe results of the comparative application of traditional FMEA and fuzzyfied FMEA using triangular and trapezoidal functions have yielded valuable insights into risk analysis. The findings indicated that fuzzyfied FMEA maintained coherence with the traditional analysis in identifying higher-risk effects, aligning with the prioritization of critical failure modes. Additionally, fuzzyfied FMEA allowed for a more refined prioritization by accounting for variations in each variable through fuzzy rules, thereby improving the accuracy of risk analysis and providing a more realistic representation of potential hazards. The application of the developed fuzzyfied FMEA approach showed promise in enhancing risk assessment in the aeronautical sector by considering uncertainties and offering a more detailed and context-specific analysis compared to conventional FMEA.Practical implicationsThis study emphasizes the potential of fuzzyfied FMEA in enhancing risk assessment by accurately identifying critical failure modes and providing a more realistic representation of potential hazards. The application case reveals that the proposed tool can be integrated with expert knowledge to improve decision-making processes and risk mitigation strategies within the aeronautical industry. Due to its straightforward approach, this facilitating methodology could also prove beneficial in other industrial sectors.Originality/valueThis paper presents the development and application of a facilitating methodology for implementing Fuzzy FMEA, comparing it with the traditional approach and incorporating variations using triangular and trapezoidal functions. This proposed methodology uses the Toolbox Fuzzy Logic of Matlab to create a fuzzyfied FMEA tool, enabling a more nuanced and context-specific risk analysis by considering uncertainties.

Automatic Failure Modes and Effects Analysis of an Electronic Fuel Injection Model

In the development of safety-critical systems, it is important to perform failure modes and effects analysis (FMEA) to identify potential failures. However, traditional FMEA activities tend to be considered difficult and time-consuming tasks. To compensate for the difficulty of the FMEA task, various types of tools are used to increase the quality and the effectiveness of the FMEA reports. This paper explains an automatic FMEA tool that integrates the model-based design (MBD), FMEA, and simulated fault injection techniques in a single environment. The automatic FMEA tool has the following advantages compared to the existing FMEA analysis tool: First, the automatic FMEA tool automatically generates FMEA reports, unlike the traditional spreadsheet-based FMEA tools. Second, the automatic FMEA tool analyzes the causality between the failure modes and the failure effects by performing model-based fault injection simulation. In order to demonstrate the applicability of the automatic FMEA, we used the electronic fuel injection system (EFI) Simulink model. The results of the automatic FMEA were compared to those of the legacy FMEA.

FMEA tool to analysis of blow molding machine damage

Machine performance in industry has a vital role in the production floor. The machine operates smoothly will support the achievement of production targets. One sector produces packaging products made based on plastic experiencing a failure production process due to the frequent stopping of the Blow Molding Machine. Fishbone diagram and Failure Mode and Effect Analysis (FMEA) is used to find information about the factors cause the Blow Molding Machine to stop. Fishbone diagram is used to determine the factors cause the failure of the Blow Molding Machine in running the production process. FMEA is used to identify the factors causing loss and determine the priority level of risk based on the RPN value. The mold damage factor has the highest RPN value. Mold failure is most significant cause of Blow Molding Machine stops operating. The mold is damaged when stored in the spare part warehouse due to crushed by a material made of metal. Mold is stored in an unsuitable location. Analysis using a fishbone diagram to determine the root of the problem handled.

Reliability Analysis of Forest Machines Due to FMEA Method

Abstract The article deals with the research of operational reliability of forest felling machines with the method FMEA (Failure Mode and Effect Analysis) and its implementation for observed machines in the organization. Forwarders 810D by John Deere were chosen for this research. The research was realized in real operational conditions. Application of the FMEA method allows flexibility in case of unexpected situations and optimization of human potential abilities. FMEA tool is a tool preventing outages operational reliability and preventive tool for ensuring the maintenance of facilities. This paper explores and verifies the operational reliability theory in practical real-world conditions, resulting in a reduction in operating (variable) costs, minimization of failures and readiness and increased performance of observed machines.

The Utility of Failure Modes and Effects Analysis of Consultations in a Tertiary, Academic, Medical Center.

Failure modes and effects analysis (FMEA) is a tool used to identify potential risks in health care processes. We used the FMEA tool for improving the process of consultation in an academic medical center. A team of 10 staff members-5 physicians, 2 quality experts, 2 organizational consultants, and 1 nurse-was established. The consultation process steps, from ordering to delivering, were computed. Failure modes were assessed for likelihood of occurrence, detection, and severity. A risk priority number (RPN) was calculated. An interventional plan was designed according to the highest RPNs. Thereafter, we compared the percentage of completed computer-based documented consultations before and after the intervention. The team identified 3 main categories of failure modes that reached the highest RPNs: initiation of consultation by a junior staff physician without senior approval, failure to document the consultation in the computerized patient registry, and asking for consultation on the telephone. An interventional plan was designed, including meetings to update knowledge of the consultation request process, stressing the importance of approval by a senior physician, training sessions for closing requests in the patient file, and reporting of telephone requests. The number of electronically documented consultation results and recommendations significantly increased (75%) after intervention. FMEA is an important and efficient tool for improving the consultation process in an academic medical center.

75 A Proactive Risk Assessment of Electronic Blood Product Ordering

Transfusion of blood components is a complex multidisciplinary process from provider order, to blood bank processing, to administration. Errors at any of these points can result in great harm to the patient. Given the complexity and high-risk process of blood ordering, one of our 2016 quality and patient safety (QPS) goals was to conduct a proactive risk assessment (PRA) for blood product ordering using failure modes and effects analysis (FMEA) methodology. The scope for this project included electronic routine order of all blood products through the point of pickup for all locations, excluding the operating rooms, where the electronic order system is not used. The steps prior to the order (type and screen [T&S] specimen collection and testing) and the steps following product pickup (transfusion of the product) were outside of the scope of this project. The FMEA tool was used to identify possible failure modes to reduce these risks. Initially, the clinical systems engineers (CSEs) from the QPS department conducted interviews and observations of the process. Subsequently, two interdisciplinary teams (East Campus and West Campus), comprising key stakeholders from each step of the electronic blood ordering process, were formed and led by the CSEs. The PRA consisted of creating a process map, identifying potential failure modes for each sub-step, assigning a risk score to each potential failure mode, and identifying the potential failure effects and causes. Failure modes were scored for three indicators: severity (S), likelihood of occurrence (O), and probability of detection (D). A risk priority number (RPN) was calculated by multiplying S by O by D. For those failure modes with RPN ≥81, mitigation strategies were developed by the interdisciplinary teams. The East Campus identified 54 failure modes (30 with RPN≥81), and the West Campus identified 103 failure modes (34 with RPN≥81). Potential causes of these failures revealed a wide range, including human error (eg, incorrect patient selected), interdisciplinary communication (eg, inaccurate identification of contact information), IT/equipment (eg, multiple IT systems interfaces), and process issues (eg, lack of transfusion history). Risk mitigation strategies include an enhanced order entry set with logic-based alerts and a streamlined pickup process. In addition, a nursing task list is being developed to facilitate pre-transfusion processes. Finally, a transfusion dashboard is being designed to improve the access of ordering providers to relevant information (eg, transfusion history, transfusion reactions, relevant labs, and T&S status). FMEA is useful for proactively addressing risks for a highly complex process, such as blood product ordering, to identify issues and improve the process. The ultimate goal of this FMEA is to improve quality and patient safety, by preventing transfusion delays and erroneous blood product administration.

Failure Mode and Effect Analysis (FMEA) may enhance implementation of clinical practice guidelines: An experience from the Middle East.

Implementation of clinical practice guidelines (CPGs) has been shown to reduce variation in practice and improve health care quality and patients' safety. There is a limited experience of CPG implementation (CPGI) in the Middle East. The CPG program in our institution was launched in 2009. The Quality Management department conducted a Failure Mode and Effect Analysis (FMEA) for further improvement of CPGI. This is a prospective study of a qualitative/quantitative design. Our FMEA included (1) process review and recording of the steps and activities of CPGI; (2) hazard analysis by recording activity-related failure modes and their effects, identification of actions required, assigned severity, occurrence, and detection scores for each failure mode and calculated the risk priority number (RPN) by using an online interactive FMEA tool; (3) planning: RPNs were prioritized, recommendations, and further planning for new interventions were identified; and (4) monitoring: after reduction or elimination of the failure mode. The calculated RPN will be compared with subsequent analysis in post-implementation phase. The data were scrutinized from a feedback of quality team members using a FMEA framework to enhance the implementation of 29 adapted CPGs. The identified potential common failure modes with the highest RPN (≥ 80) included awareness/training activities, accessibility of CPGs, fewer advocates from clinical champions, and CPGs auditing. Actions included (1) organizing regular awareness activities, (2) making CPGs printed and electronic copies accessible, (3) encouraging senior practitioners to get involved in CPGI, and (4) enhancing CPGs auditing as part of the quality sustainability plan. In our experience, FMEA could be a useful tool to enhance CPGI. It helped us to identify potential barriers and prepare relevant solutions.

A Knowledge Based FMEA to Support Identification and Management of Vehicle Flexible Component Issues

The objective of this research is to develop a knowledge-based approach of performing Failure Modes and Effects Analysis (FMEA) on flexible vehicle components. A three-step knowledge discovery and data mining process is used to develop a set of rules. This set provides decision support to engineers while they perform FMEA on flexible vehicle components. The first step is where traditional FMEAs are performed on flexible components. In the second step, a decision tree algorithm (J48) is used to extract rules from the collected data. The third step involves manual post-processing of the rules extracted by the decision tree algorithm. Finally, the set of rules is implemented in a knowledge-based FMEA tool that can be used to provide decision support to engineers while they perform FMEAs on flexible components. The tool is used to identify and review quality issues within a complete vehicle. The top ten issues identified from the FMEA are submitted to design and manufacturing engineers for detailed evaluations.

Practical aspects of the use of FMEA tool in clinical laboratory risk management

INTRODUCTION: This paper presents the failure modes and effects analysis (FMEA) tool in a clinical laboratory through the introduction of new technology for blood gas and serum ionized calcium in multi-parameter analyzers such as Point of Care Testing (POCT). OBJECTIVE: To present FMEA as a tool for risk managing and improvement with the introduction of new technologies in a public laboratory. METHODS: The change of multiparameter gas analyzer type POCT was defined and described as a process. Subsequently, the criteria were presented to the risk assessment and its quantification. We studied the failure modes that might occur in this process. We established three action plans involving improvements to be made in the technological change. FMEA was applied in two stages: at the beginning of the project and after the implementation of the proposed measures. RESULTS: The first plan involved administrative measures related to the bidding process; the second preventive action involved the possibility of which supplier would win the bid by studying the efficiency of the analyzer and its impact on productivity; the third set of actions was directed to improvements in the relationship with the clinical staff in order to minimize occasional complaints. The last actions referred to employing new employees to meet the growing demand. CONCLUSION: FMEA proved to be a reliable tool for performance improvement, which proactively identifies, prioritizes and mitigates patient risks.

Drug Shortages: Process for Evaluating Impact on Patient Safety

Purpose Drug shortages can seriously impact patient safety. The objective of this study was to develop safety assessment checklists for use during a drug shortage, whether the same drug is available or an alternative is required. Methods A failure modes and effects analysis (FMEA) was conducted following the Institute for Healthcare Improvement's FMEA tool. Each step of the medication use process was reviewed for the potential impact of a shortage-related event. The likelihood of occurrence, likelihood of detection, and severity of potential harm were determined and rated by a multidisciplinary team. To supplement the results of the FMEA, a survey focusing on the perception of patient safety during a drug shortage was developed and sent to various e-mail lists. These data were used to develop the safety assessment checklists. Results Common safety concerns associated with drug shortages in multiple areas of the medication use process include possible look-alike sound-alike issues and delays in patient care. The FMEA and survey results noted that unfamiliarity with an alternative agent was a high vulnerability during a shortage where an alternative is required. The potential for incorrect doses was the greatest concern during a shortage where the same drug is available, but in a different concentration or presentation. Conclusion Drug shortages create patient safety risks. Safety assessment checklists for use when the same drug is available and when an alternative is required during a drug shortage were developed to aid institutions in preventing patient safety impacts.

Combining Service Blueprint and FMEA for Service Design

This paper aims at combining the service blueprint and Failure Modes and Effects Analysis (FMEA) to assist service designers in designing a failure-free service system. In the proposed approach, a blueprint of a service system should be, first, developed to identify the potential fail points and failure modes for both front office and back office service activities. Based on the blueprint, the FMEA tool is then applied to prioritise the critical potential failure modes of the service system and take the required actions to ensure service design performance. An example of a hypermarket service system was used to demonstrate the proposed approach. The example not only identifies the most likely failure modes but also provides the effects and possible causes for each of the most critical failure modes. This implies that the actions to prevent these failures from occurring should be the main focus in the service design stage of the example company. Some managerial implications are also provided.