IDENTIFIKASI RISIKO KESELAMATAN KERJA DENGAN METODE FMEA DI UD. BAROKAH JAYA KUSEN

2021 ◽  
pp. 20-24
Author(s):  
Permadi Gilang Prasetyo ◽  
Agustian Suseno ◽  
Asep Erik Nugraha
Keyword(s):  
Risk Priority Number

UD. Barokah Jaya sering mengalami permasalahan Keselamatan dan Kesehatan Kerja (K3) terkait dengan potensi kecelakaan kerja di proses produksinya, serta membutuhkan solusi berupa prioritas dalam menangani masalah potensi bahaya tersebut, dikarenakan terbatasnya sumberdaya dan cara untuk pengendalian potensi tersebut. Metode FMEA menjadi solusi yang tepat dalam hal prioritas masalah tersebut dengan nilai Risk Priority Number (RPN) sebagai indikator priorita. Hasil penelitian menunjukan dari hasil identifikasi risiko dengan metode FMEA didapat 8 potensi kecelakaan kerja dengan nilai RPN tertinggi sebesar 210 yang diperoleh oleh potensi kecelakaan kerja “tangan terluka akibat alat pemotong kayu” dan upaya pengendalian berupa training dari segi manusia, pembelian APD untuk RPN tertinggi dari segi metode, pembuatan WIP dari segi material, penggantian komponen mesin dari segi mesin, dan dilakukan relayout dan 5R dari segi lingkungan.

A Systematized FMEA Practice for Magnet Relays

2010 ◽  
Vol 146-147 ◽  
pp. 757-769
Author(s):  
Ching Ming Cheng ◽  
Wen Fang Wu ◽  
Yao Hsu
Keyword(s):  
New Product Development ◽  
Failure Modes ◽  
New Product ◽  
Risk Priority Number ◽  
Detection Model ◽  
Regulation Function ◽  
Potential Failure ◽  
Weighting Rule ◽  
Rating Criterion

The Design Failure Modes and Effects Analysis (DFMEA) are generally applied to risk management of New Product Development (NPD) through standardization of potential failure modes and effect-ranking of rating criterion with failure modes. Typical 1 to 10 of effect-ranking are widely weighed the priority of classification, that framing effects and status quo senses might cause decision trap happening thus. The FMEA follows considerable indexes which are including Severity, Occurrence and Detection, and need be associated with difference between every two failures individually. However, we suspect that a more systematic construction of the analysis by which failure modes belong is necessary in order to make intellectual progress in this area. Two ways of such differentiation and construction are improvable effect-ranking and systematized indexes; here we resolve for attributes of failures with classification, maturity and experiance of indexes according to an existing rule. In Severity model, the larger differentiation is achieved by separating indexes to the classification of the Law & Regulation, Function and Cosmetic. Occurrence model has its characteristic a reliable ranking indexwhich assists decisionmakers to manage their venture. This is the model most closely associate with product maturity by grouping indexes to the new, extend and series product. Detection model offers a special perspective on cost; here the connections concerned with phase occasion of the review, verification and validation. Such differentiations will be proposed and mapped with the Life Cycle Profile (LCP) to systematize FMEA. Meanwhile, a more reasonable Risk Priority Number (RPN) with the new weighting rule will be worked out for effect-ranking and management system will be integrated systematiclly

VIKOR power law-based customer-oriented FMEA with complete unique risk priority numbers

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Randula L. Hettiarachchi ◽  
Pisut Koomsap ◽  
Panarpa Ardneam
Keyword(s):  
Case Studies ◽  
Power Law ◽  
Design Methodology ◽  
Service Sector ◽  
Failure Modes ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Content Type ◽  
Industrial Sectors ◽  
Inherent Problem

PurposeAn inherent problem on risk priority number (RPN) value duplication of traditional failure modes and effect analysis (FMEA) also exists in two customer-oriented FMEAs. One has no unique value, and another has 1% unique values out of 4,000 possible values. The RPN value duplication has motivated the development of a new customer-oriented FMEA presented in this paper to achieve practically all 4,000 unique values and delivering reliable prioritization.Design/methodology/approachThe drastic improvement is the result of power-law and VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). By having all three risk factors in a power-law form, all unique values can be obtained, and by applying VIKOR to these power-law terms, the prioritization is more practical and reliable.FindingsThe proposed VIKOR power law-based customer-oriented FMEA can achieve practically all 4,000 unique values and is tested with two case studies. The results are more logical than the results from the other two customer-oriented FMEAs.Research limitations/implicationsThe evaluation has been done on two case studies for the service sector. Therefore, additional case studies in other industrial sectors will be required to confirm the effectiveness of this new customer-oriented RPN calculation.Originality/valueAchieving all 1,000 unique values could only be done by having experts tabulate all possible combinations for the traditional FMEA. Therefore, achieving all 4,000 unique values will be much more challenging. A customer-oriented FMEA has been developed to achieve practically all 4,000 unique risk priority numbers, and that the prioritization is more practical and reliable. Furthermore, it has a connection to the traditional FMEA, which helps explain the traditional one from a broader perspective.

Reliability loss–oriented product assembling quality risk modeling approach based on reliability–quality–reliability chain

2020 ◽  
Vol 234 (10) ◽  
pp. 1355-1366 ◽  
Author(s):  
Yihai He ◽  
Anqi Zhang ◽  
Fengdi Liu ◽  
Xiao Han ◽  
Di Zhou
Keyword(s):  
System Reliability ◽  
Process Variations ◽  
Risk Modeling ◽  
Risk Priority Number ◽  
Product Reliability ◽  
Modeling Approach ◽  
Quality Risk ◽  
Work First ◽  
Fusion Framework ◽  
Operational Data

Assembling variations caused by assembling system reliability degradation are the root causes of poor-assembled product reliability, and the reliability loss is the barometer of assembling quality risks. However, few studies have integrated reliability loss with assembling quality risk analysis. Therefore, a modeling approach of assembling quality risk regarding product reliability loss is expounded in this work. First, the assembling quality risk is divided into systematic, exterior, and interior risks, and a formation mechanism of assembling quality risk is presented. Second, the fusion framework of big operational data in assembling is described, an assembling reliability–quality–reliability chain is established, and the parameters of the chain constitute assembling system reliability ( R), assembling process quality ( Q), and assembled product reliability ( R). Third, on the basis of the reliability–quality–reliability chain, the risk priority number is adopted to quantify the assembling quality risk, which is extended by quantifying the undetectable rate of the assembling system, the occurrence possibility of process variations, and the product reliability loss. Finally, an assembling quality risk of a circuit maintenance cover of a car is conducted to validate the effectiveness and advancement of the presented approach. The result shows that the proposed method can systematically quantify the assembling quality risk.

scholarly journals Observational Study of Medication Error in Outpatient Pharmacy RSUP Dr. Hasan Sadikin Bandung

2017 ◽  
Vol 15 (2) ◽  
pp. 210
Author(s):  
Viki Hestiarini ◽  
Lia Amalia ◽  
Eni Margayani
Keyword(s):  
Medication Error ◽  
Medication Errors ◽  
Drug Information ◽  
Data Entry ◽  
Care Process ◽  
Analysis Method ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Root Cause ◽  
Cause Of Failure

Medication error can occur at all stages, starting from prescribing, dispensing and administration of drugs. This study aims to assess the medication errors that occur in the pharmaceutical care process and analyze the cause of failure using the root cause analysis method, to improvement action and decrease the incidence of medication errors. The data were completeness prescription, frequency of dispensing error and completeness of drug information. The number of sample was 1100 prescriptions Prescribing errors were found the potential injury 15.69±11.51% and near missed error 0.5±0.55%. At dispensing stage, occur 427 incidences (9.71%), consist of two incidences (0.04%) for validation assessment regulations, 224 incidences (5.09%) of data entry, 113 incidences (2.57%) of retrieval of drugs, 19 incidences (0.43%) of fi ll in drugs, 69 incidences (1.57%) of fi nal check. At dispensing stage, near missed 330 incidences (7.51%) of near missed and 97 incidences (2.21%) of potential injury. Failure mode and effect analysis calculate of risk priority number, the drug retrieval (RPN 210) and data entry (RPN 126) were analyzed root cause of the analysis for man, material, method, facility and environment.

scholarly journals Risk analysis of production process for food SMEs using FMEA method: a case study

2021 ◽  
Vol 331 ◽  
pp. 02010
Author(s):  
Prima Fithri ◽  
Muhammad Rafi ◽  
Pawenary ◽  
A. S. Prabuwono
Keyword(s):  
Human Resources ◽  
Production Process ◽  
Critical Value ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Increase Productivity ◽  
Fmea Method ◽  
Bread Production ◽  
A Company

The increasing development of the industry makes every industry have to compete with other competitors to gain an edge. The advantages of competition are influenced by several factors, one of which is good human resource management. Where if a company has good human resources, it will increase profits indirectly and can increase productivity. This research discusses case studies about the potential dangers of IKM Heppy Bakery’s potential dangers that can harm workers in bread production. The method used is Failure Mode And Effect Analysis (FMEA). Later, the data will be filled and given a rating distinguished into three parts: severity, occurrence, and detection. The data were obtained through questionnaires given to 3 workers at IKM Heppy Bakery and filled in rating values based on the provisions that have been given to the questionnaire. This Value helps determine the Risk Priority Number (RPN) obtained from multiplication between severity, occurrence, and detection. After processing the RPN multiplication data, the highest RPN value was obtained by 193 with the danger factor of the operator overheating and dehydrating due to high temperatures. Furthermore, the calculation of critical Value was obtained by 109. Based on the critical Value obtained seven hazard factors above the critical value, these seven hazard factors need to be improved so that workers do not avoid accidents when conducting the production process.

scholarly journals STUDY OF POSSIBILITIES OF JOINT APPLICATION OF PARETO ANALYSIS AND RISK ANALYSIS DURING CORRECTIVE ACTIONS

2020 ◽  
Vol 4 ◽  
pp. 22-24
Author(s):  
Volodymyr Haievskyi
Keyword(s):  
Continuous Improvement ◽  
Traditional Method ◽  
Quality Management System ◽  
Corrective Action ◽  
Risk Priority Number ◽  
Risk Area ◽  
Pareto Chart ◽  
Pareto Analysis ◽  
Joint Application ◽  
Corrective Actions

Continuous improvement in the quality management system is based on corrective action. Corrective actions require the identification of priority defects that require priority elimination of the causes of occurrence. The traditional method of prioritization can be considered a Pareto chart, built by the number of identified inconsistencies. This technique makes it possible to prioritize the most frequently detected defects. However, defects that are rare can significantly outweigh those that are often encountered in their consequences. The defect risk is a complex indicator that simultaneously takes into account both the number of detected defects and their impact. Failure Mode and Effects Analysis (FMEA) can be used to quantify risk. This technique allows to determine the risk priority number (RPN), taking into account the number of detected defects (O), the consequences of the appearance of a defect (S) and the possibility of timely detection of a defect or cause before the onset of undesirable consequences (D). The priority number of risks numerically characterizes the risks of a defect and can be used as a criterion for determining priority defects. Based on the values of the priority number of risks, a Pareto chart can be built and defects that form 80% of the risk area can be identified. These defects require urgent corrective action. According to the data taken from production, it is shown that the Pareto analysis by the priority number of risks gives results that differ from the analysis by the number of identified inconsistencies. Application of the proposed approach will allow introducing risk-oriented methods into the procedures for carrying out corrective actions. This will make it possible to direct the resources of the enterprise to eliminate the causes of defects that are actually detected and can have the most significant consequences for consumers of products

МЕТОД ОЦІНКИ РИЗИКІВ У ВИРОБНИЧІЙ ЛАБОРАТОРІЇ МОЛОКОПЕРЕРОБНИХ ПІДПРИЄМСТВІ НА ОСНОВІ LEAN

2021 ◽  
pp. 35-39
Author(s):  
Ю.І. Сеник
Keyword(s):  
Failure Mode ◽  
Risk Priority Number ◽  
Effect Analysis

У роботі розглянуто застосування модифікованого до системи ощадливого виробництва методу оцінки ризиків FMEA для виробничих лабораторій молокопереробних підприємств. Описано алгоритм реалізації failure mode and effect analysis та вказано основні принципи розрахунку S (значимість потенційних збоїв у роботі), O (ймовірність виникнення збою у роботі), D (ймовірність виявлення збою) та RPN (risk priority number). Розглянуто два основні недоліки класичного підходу методики FMEA та для їх усунення використано модифікацію, запропоновану Rapinder Sawhney та ін., яка полягає у використанні інтегрального показника «значення оцінки ризиків». Для аналізу ризиків виробничої лабораторії згідно з модифікованою методикою FMEA вибрано окремий шаблон таблиці, представлений у тексті статті. Він містить як елементи FMEA, так і спосіб вирішення критичних показників згідно з принципами LEAN. Такий підхід до роботи лабораторії є вкрай важливим, адже саме від оперативності та точності проведених досліджень залежатиме можливість уникнення прямих утрат для підприємства та випуску безпечної та якісної продукції.

scholarly journals Identifying preventive maintenance guideline for a combine harvester with application of failure mode and effect analysis technique

2020 ◽  
Vol 319 ◽  
pp. 01004
Author(s):  
Voraya Wattanajitsiri ◽  
Rapee Kanchana ◽  
Surat Triwanapong ◽  
Kittipong Kimapong
Keyword(s):  
Risk Assessment ◽  
Failure Mode ◽  
Preventive Maintenance ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Analysis Technique ◽  
Combine Harvester ◽  
A Chain ◽  
Near Future

The objective of this research was to study a risk assessment of the rice combine harvester using FMEA technique implementation and suggested the procedures to maintain the parts of the rice combine harvester by analyzing the causes of risk assessment of FMEA. The FMEA was also applied to specify failure causes and effects that occurred in the rice harvester. The obtained data were calculated for a risk priority number (RPN) and then sorted to be a descending order. The high RPN part was analyzed for the causes and effects and then suggested a preventive maintenance in near future. The results revealed that the highest RPN of 576 was found when a chain surface was considered and also showed the maximum risk among the considered parts in the rice combine harvester. While, the lowest RPN of 144 was found when a rice sieve part was considered but this RPN was still higher than that of 100 RPN which was required to specify the preventive maintenance.

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