scholarly journals Análise de falhas e efeitos na preparação e dispensação de quimioterápicos

2020 ◽  
Vol 19 (2) ◽  
pp. 68-108
Author(s):  
Priscila Cumba de Abreu Costa ◽  
Vilani Medeiros de Araújo Nunes ◽  
Isac Davidson Santiago Fernandes Pimenta ◽  
Thiago Da Silva Bezerra ◽  
Grasiela Piuvezam ◽  
...  
Keyword(s):  
High Risk ◽  
Failure Mode ◽  
Failure Modes ◽  
Drug Dose ◽  
Output Window ◽  
Effect Analysis ◽  
Reference Center ◽  
Chemotherapy Drugs ◽  
Outpatient Unit ◽  
Causes Of Failure

Objetivo: Realizar un Análisis Multimodal de fallas y efectos para identificar prospectivamente los riesgos relacionados a la fase de la preparación y dispensación de medicamentos quimioterápicos en una unidad ambulatoria de un centro de referencia en oncología. Métodos: Se utilizaron las seis primeras etapas del Análisis Multimodal de fallas y Efectos: identificar las situaciones peligrosas y montar un equipo; definir el proceso a ser analizado describiendo gráficamente; aplicar lluvia de ideas buscando identificar modos de fallas; priorizar los modos de fallas y realizar análisis de riesgos; identificar las causas potenciales de los modos de fallo y volver a dibujar el proceso. Resultados: Se identificaron diecisiete modos de falla, siendo dos clasificados como de alto riesgo: cambiar la ventana de salida del medicamento y cálculo erróneo de la dosis de medicamento intratecal. Conclusiones: Se identificaron los posibles modos de falla que se relacionaban al proceso analizado, además, fue posible definir causas potenciales para la existencia de esos riesgos. Aim: Conduct a Failure Mode and Effect Analysis (FMEA) to prospectively identify the risks related to the preparation and dispensation of chemotherapy drugs at an outpatient unit of a reference center in oncology. Methods: The first six stages of Failure Mode and Effect Analysis were used to identify dangerous situations and assemble a team; define the process to be analyzed and describe it graphically; apply a host of ideas to identify failure modes; prioritize failure modes and conduct risk analysis; identify potential causes of failure modes and redesign the process. Results: Seventeen failure modes were identified, two of which were classified as high risk: changing the output window for the drug and miscalculating the intrathecal drug dose. Conclusions: The possible failure modes related to the process analyzed were identified; in addition, it was possible to define potential causes of these risks.

scholarly journals Identifikasi Potensi Modus Kegagalan Yang Dapat Menghambat Kelancaran Proses Pelayanan Rawat Jalan Menggunakan Failure Mode Effect Analysis (FMEA) Di Rumah Sakit BM Jakarta Barat

2020 ◽  
Vol 8 (2) ◽  
pp. 105-113
Author(s):  
Achmaddudin Sudiro
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Outpatient Service ◽  
Outpatient Services ◽  
Effect Analysis ◽  
Outpatient Unit ◽  
Mode Effect ◽  
Potential Failure ◽  
Fmea Method ◽  
Failure Mode Effect Analysis

Outpatient services hosted by the hospital have never been absent from public visits. In fact, every year an outpatient visitor is always increasing. This research intends to identify potential failure mode that can  inhibit of every flow of service in the outpatient care unit using the Failure Mode Effect Analysis (FMEA) method. Qualitative research plan using an observation survey approach and in-depth interviews with the outpatient service head Coordinator conducted in February 2020 on the hospital outpatient unit service process. The results of this study Indicate the potential failure mode that has the value of the RPN above the value of cut off point 180 as many as six out of ten failure modes. Firstly, the check is not on schedule (360), secondly, the patient lags a turn call order Check (270), third, Specific drug failure is not available (245), fourth, general patient protests with the price of the drug (224), fifth, the patient is void to poly (196), the sixth patient registrant online missed sequence number queue (180). Based on the results of the research, hospitals are expected to follow up with the results of this research by conducting a redesign of the process that occurs today using the FMEA to maintain service quality.

scholarly journals Perencanaan Perawatan Mesin Pump 107 Dengan Metode Reability Centered Maintenance (RCM) di PT. Petrokimia Gresik

2018 ◽  
Vol 1 (02) ◽  
pp. 33-38
Author(s):  
Rezza Wira Utomo
Keyword(s):  
Service Life ◽  
Failure Mode ◽  
Failure Rate ◽  
Failure Modes ◽  
Treatment Method ◽  
Maintenance Scheduling ◽  
Effect Analysis ◽  
Mean Time ◽  
Working Efficiency ◽  
Causes Of Failure

PT. Petrokimia Gresik is one of the largest fertilizer companies in Indonesia, locatedin Gresik, East Java. The pump 107 engine on the Ammonia unit is often damaged due to itslargest size compared to other types of pumps, as well as the result of carrying thick orconcentrated fluid (bluish black) so that it is heavy for the drainage process. The purpose ofthis study is to plan and recommend the proposed treatment method on the pump enginebased on the method used to improve the working efficiency of the pumping machine 107and determine the failure mode and diagnosis of the effects of failure modes that occur in thecomponent. The method used is the Reability Centered Maintenance (RCM) method whichis expected to be able to produce maintenance or maintenance scheduling that is increasinglydirected so that it can improve the performance and efficiency of the engine, reduce repaircosts, and extend the service life of the machine itself. From this study, the results are in theform of Faliure Model And Effect Analysis (FMEA), FMEA table preparation is carried outbased on component function data and maintenance reports which can then be determined byvarious failures resulting in malfunction. From the compilation of FMEA, it can be seenwhat the causes of failure are and what impacts they have caused. Next, the value of MeanTime Between Failure (MTBF) pump 107-JA is 15,829 hours, pump 107-JB is 43,764 hoursand pump 107-JCM is 19,578 hours. Maintainability M (t) or Mean Time to Repair (MTTR)value on pump 107-JA is 2,914 hours, pump 107-JB is 3,411 hours, and pump 107-JCM is3,1 hours, Availability A (t) value is pump 107-JA at 84.44%, pump 107-JB at 92.76% andpump 107-JCM at 86.31%. The last one is found that the failure rate of pump 107-JA is0.063172, pump 107-JB is 0.02284 and pump 107-JCM is 0.051.

Failure mode and effect analysis (FMEA) to improve collaborative project-based learning: Case study of a Study and Research Path in mechanical engineering

2021 ◽  
pp. 030641902199904
Author(s):  
Elena Bartolomé ◽  
Paula Benítez
Keyword(s):  
Active Learning ◽  
Failure Mode ◽  
Mechanical Engineering ◽  
Failure Modes ◽  
Collaborative Study ◽  
Project Based Learning ◽  
Educational Process ◽  
Effect Analysis ◽  
Questions And Answers

Failure Mode and Effect Analysis (FMEA) is a powerful quality tool, widely used in industry, for the identification of failure modes, their effects and causes. In this work, we investigated the utility of FMEA in the education field to improve active learning processes. In our case study, the FMEA principles were adapted to assess the risk of failures in a Mechanical Engineering course on “Theory of Machines and Mechanisms” conducted through a project-based, collaborative “Study and Research Path (SRP)” methodology. The SRP is an active learning instruction format which is initiated by a generating question that leads to a sequence of derived questions and answers, and combines moments of study and inquiry. By applying the FMEA, the teaching team was able to identify the most critical failures of the process, and implement corrective actions to improve the SRP in the subsequent year. Thus, our work shows that FMEA represents a simple tool of risk assesment which can serve to identify criticality in educational process, and improve the quality of active learning.

Fuzzy risk assessment for electro-optical target tracker

2016 ◽  
Vol 33 (6) ◽  
pp. 830-851 ◽  
Author(s):  
Soumen Kumar Roy ◽  
A K Sarkar ◽  
Biswajit Mahanty
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Linear Equations ◽  
Mode Analysis ◽  
Failure Behavior ◽  
Membership Functions ◽  
Design And Development ◽  
Effect Analysis ◽  
Content Type ◽  
Criticality Analysis

Purpose – The purpose of this paper is to evolve a guideline for scientists and development engineers to the failure behavior of electro-optical target tracker system (EOTTS) using fuzzy methodology leading to success of short-range homing guided missile (SRHGM) in which this critical subsystems is exploited. Design/methodology/approach – Technology index (TI) and fuzzy failure mode effect analysis (FMEA) are used to build an integrated framework to facilitate the system technology assessment and failure modes. Failure mode analysis is carried out for the system using data gathered from technical experts involved in design and realization of the EOTTS. In order to circumvent the limitations of the traditional failure mode effects and criticality analysis (FMECA), fuzzy FMCEA is adopted for the prioritization of the risks. FMEA parameters – severity, occurrence and detection are fuzzifed with suitable membership functions. These membership functions are used to define failure modes. Open source linear programming solver is used to solve linear equations. Findings – It is found that EOTTS has the highest TI among the major technologies used in the SRHGM. Fuzzy risk priority numbers (FRPN) for all important failure modes of the EOTTS are calculated and the failure modes are ranked to arrive at important monitoring points during design and development of the weapon system. Originality/value – This paper integrates the use of TI, fuzzy logic and experts’ database with FMEA toward assisting the scientists and engineers while conducting failure mode and effect analysis to prioritize failures toward taking corrective measure during the design and development of EOTTS.

Risk Evaluation Approach in Failure Mode and Effect Analysis of Automotive Headlamp Assembly

2014 ◽  
Vol 564 ◽  
pp. 72-76
Author(s):  
Shukriah Abdullah ◽  
Aziz Abdul Faieza
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Assessment Tool ◽  
Action Plan ◽  
Technical Problem ◽  
Assembly Process ◽  
Preventive Action ◽  
Effect Analysis ◽  
Evaluation Approach ◽  
Process Failure

Headlamp assembly entailed a complex assembly process and error in assembled can result in technical problem and higher reject rate at the end of the assembly process. A study has been conducted, in one of the automotive headlamp assembly in Malaysia, where there are numerous defect detected during the assembly process, such as metal spacing missing, wrong model housing, wrong sticker affix, wrong orientation with a total of 80% defects detected. Currently the headlamps are assembled with no dimensional control, results in high physical nonconformity product. The main objective of this project is to identify potential failure in headlamp assembly process. The approach used was risk assessment tool which is Process Failure Mode and Effect. This work also developed the corrective action plan for accurate ranking of Failure Modes by Risk Priority Number-based method and implement it to the process assembly. The result showed that there was increased of 5% in preventive action and 4% increment of the detection action

Failure Mode and Effect Analysis (FMEA) for Enhancing Reliability of Water Tube Boiler in Thermal Power Plant

2016 ◽  
Vol 8 (02) ◽  
pp. 79-86
Author(s):  
Kapil Dev Sharma ◽  
Shobhit Srivastava
Keyword(s):  
Power Plant ◽  
Failure Mode ◽  
Thermal Power Plant ◽  
Failure Modes ◽  
Thermal Power ◽  
Effect Analysis ◽  
Water Tube ◽  
Potential Failure ◽  
Fmea Method ◽  
Continuous Power

Failure mode and effect analysis is one of the QS-9000 quality system requirement supplements, with a wide applicability in all industrial fields. FMEA is the inductive failure analysis instruments which can be defined as a methodical group of activities intended to recognize and evaluate the potential failure modes of a product/ process and its effects with an aim to identify actions which could eliminate or reduce the chance of the potential failure before the problem occur. The purpose of this paper is to evaluate the FMEA research and application in the Thermal Power Plant Industry. The research will highlight the application of FMEA method to water tubes (WT) in boilers with an aim to find-out all the major and primary causes of boiler failure and reduce the breakdown for continuous power generation in the plant. Failure Mode and Effect Analysis technique is applied on most critical or serious parts (components) of the plant which having highest Risk Priority Number (RPN). Comparison is made between the quantitative results of FMEA and reliability field data from real tube systems. These results are discussed to establish relationships which are useful for future water tube designs.

Cost consequence of failure in failure mode and effect analysis

2017 ◽  
Vol 34 (8) ◽  
pp. 1318-1342 ◽  
Author(s):  
Jeff Guinot ◽  
John W. Sinn ◽  
M. Affan Badar ◽  
Jeffrey M. Ulmer
Keyword(s):  
Failure Mode ◽  
Failure Modes ◽  
Cost Data ◽  
Ordinal Scale ◽  
Automotive Application ◽  
Manufacturing Cost ◽  
Potential Cost ◽  
Effect Analysis ◽  
Content Type ◽  
Cost Consequence

Purpose The purpose of this paper is to investigate the possibility of including the cost consequence of failure in the a priori risk assessment methodology known as failure mode and effect analysis (FMEA). Design/methodology/approach A model of the standard costs that are incurred when an electronic control module in an automotive application fails in service was developed. These costs were related to the Design FMEA ranking of the level of severity of the failure mode and the probability of its occurrence. Monte Carlo simulations were conducted to establish the average costs expected for each level of severity at each level of occurrence. The results were aggregated using fuzzy utility sets into a nine-point ordinal scale of cost consequence. The criterion validity of this scale was assessed with warranty cost data derived from a case study. Findings It was found that the model slightly underestimated the warranty costs that accrued, but the fit could be improved with adjustments dictated by actual usage conditions. Research limitations/implications Cost data used in the simulations were derived from government and academic surveys, analyses, and estimates of the manufacturing cost structure; and nominal costs for various quality issues experienced by Tier 2 automotive electronics supplier. Specificity is lacking. The sample size and the type of the failure modes used to validate the model are constrained by the number and type of products which have had demonstrable performance concerns over the past three years, with cost data available to the authors. The power of the validation is limited. The validation is considered a screening assessment. Practical implications This work relates the characterization of risk with its potential cost and develops a scaling instrument to allow the incorporation of cost consequence into an FMEA. Originality/value A ranking scale was developed that related severity and occurrence rank scores to a cost consequence rank that keys to a cost of quality figure (given as percent of sales) that would accompany a realization of the failure mode.

scholarly journals Analisa defect produk sheet area corrugator 301 menggunakan metode SPC dan FMEA di PT Indah Kiat

2020 ◽  
Vol 12 (3) ◽  
pp. 332
Author(s):  
Evan Mandala Putra ◽  
Sri Mukti Wirawati ◽  
Pugy Gautama
Keyword(s):  
Process Control ◽  
Production Process ◽  
Statistical Process Control ◽  
Failure Mode ◽  
Failure Modes ◽  
Uneven Surface ◽  
Statistical Process ◽  
Effect Analysis ◽  
Product Defect ◽  
Fmea Method

This study aims to analyze defects in the sheet production process in the 301 Corrugator area by analyzing the total number of sheets produced and the number of sheets that have been damaged over a certain period of time using the Statistical Process Control (SPC) method and Failure Modes and Effect Analysis (FMEA). Based on the research results, there are 6 defects, namely untidy cuts, wrinkled sheets, uneven surface, curved sheets, uneven sides, loose sheet layers. The most dominant defect is uneven surface, which is 185.141 Kg or 60%. Based on the value of the RPN table, the product defect that has the highest value is the loose sheet layer with an RPN value of 245 from the calculation stage of the RPN value, a suggestion is made to reduce defects resulting from the loose sheet layer. From the stage of making improvements, the company should prioritize and focus on the types of disabilities and types of disabilities that have the highest RPN ranking when using the Failure Mode and Effect Analysis (FMEA) method.

scholarly journals A Proactive Risk Assessment Through Healthcare Failure Mode and Effect Analysis in Pediatric Surgery Department

2020 ◽  
Vol 11 (3) ◽  
Author(s):  
Yasamin Molavi-Taleghani ◽  
Hossein Ebrahimpour ◽  
Hojjat Sheikhbardsiri
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Pediatric Surgery ◽  
Failure Modes ◽  
Cross Sectional Study ◽  
Related Factors ◽  
Cross Sectional ◽  
Effect Analysis ◽  
Acceptable Risks ◽  
Surgery Department

Background: Patient safety is the first step to improve the quality of care. Objectives: Therefore, the present study aimed to examine the risk assessment of processes in a pediatric surgery department using the Health Failure Mode and Effect Analysis (HFMEA) in 2017 - 2018. Methods: In this research, a mixed-method design (qualitative action and quantitative descriptive cross-sectional study) was used to analyze failure mode and their effects. The nursing errors in the clinical management model were used to classify failure modes, and the theory of inventive problem solving was used to determine a solution for improvement. Results: According to the five procedures selected by the voting method and their rating, 25 processes, 48 sub-processes, and 218 failure modes were identified with HEMEA. Eight risk modes (3.6%) were found as non-acceptable risks and were transferred to the decision tree. The main root causes (hazard score ≥ 4) were as follows: Technical-related factors (14.34%), organizational-related factors (31.9%), human-related factors (45.3%), and other factors (7.6%). Conclusions: The HFMEA method is very effective in identifying the possible failure of treatment procedures, determining the cause of each failure mode, and proposing improvement strategies.

Sign in / Sign up

Export Citation Format

Share Document