Work Accident Analysis on the project at PT. X based on the Failure Mode & Effect Analysis (FMEA) Method

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.

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Integration of Statistical Quality Control (SQC) and Failure Mode Effect Analysis (FMEA) Method of Tea Product Packaging

IOP Conference Series Earth and Environmental Science ◽

10.1088/1755-1315/709/1/012055 ◽

2021 ◽

Vol 709 (1) ◽

pp. 012055

Author(s):

M A L Rucitra ◽

J Amelia

Keyword(s):

Quality Control ◽

Failure Mode ◽

Statistical Quality Control ◽

Product Packaging ◽

Effect Analysis ◽

Statistical Quality ◽

Mode Effect ◽

Fmea Method ◽

Failure Mode Effect Analysis

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Analisis Pengendalian Mutu pada Proses Produksi Pembuatan Kecap Menggunakan Metode Fault Tree Analysis (FTA) dan Metode Failure Mode Efect Analysis (FMEA)

Journal of Industrial and Engineering System ◽

10.31599/jies.v1i1.177 ◽

2020 ◽

Vol 1 (1) ◽

pp. 31-44

Author(s):

Iskandar Zulkarnaen ◽

Daonil ◽

Akbar Supriadi

Keyword(s):

Failure Mode ◽

Fault Tree ◽

Fault Tree Analysis ◽

Soy Sauce ◽

Risk Priority Number ◽

Effect Analysis ◽

Tree Analysis ◽

Mode Effect ◽

Fmea Method ◽

Failure Mode Effect Analysis

ABSTRACT Analysis of Quality Control in the Production Process of Making Soy Sauce Using the Fault Tree Analysis (FTA) Method and the Failure Mode Effect Analysis (FMEA) Method. PT XYZ is an industrial company that produces soy sauce and soy sauce for instant noodle seasoning. In an effort to maintain product quality, the writer tries to analyze every problem of reject burn, reject divert, organoleptic reject, and contaminated reject that exceeds the company standard of 0.50% based on histogram data for May 2018 - April 2019, it is found that organoleptic reject is the highest failure and the main problem is discussed using the fault tree analysis (FTA) method to analyze the root cause of failure, and the failure mode effect analysis (FMEA) method for weighting the severity, occurance and detection values in each of these three issues each problem is calculated to obtain a risk priority number (RPN) value ). From this data, it will be known that the root of the problem is the steam engine temperature value of 144 is the highest value of rpn, and the writer tries to give a proposal to improve the previous total reject 244,425 kg percentage 0.65% and after 69,284 kg percentage 0.36% with the cost before the total repair is Rp. 881,840,120 and after Rp.255,474,078 succeeded in reducing rejects below the standard while reducing costs for Rp.626,366,042. Keyword : Reject, Soy Sauce, FTA, FMEA ABSTRAK Analisis Pengendalian Mutu Pada Proses Produksi Pembuatan Kecap Menggunakan Metode Fault Tree Analysis (FTA) dan Metode Failure Mode Effect Analysis (FMEA). PT XYZ merupakan perusahaan industri yang menghasilkan produk kecap manis dan kecap asin untuk bumbu mie instant. Dalam upaya mempertahankan kualitas produk penulis berusaha untuk menganalisa setiap permasalahan reject gosong, reject divert, reject organoleptik, dan reject terkontaminasi yang melebihi standar perusahan 0,50% berdasarkan data histogram periode mei 2018 – april 2019 didapatkan reject organoleptik menjadi kegagalan tertinggi dan masalah utama yang dibahas dengan menggunakan metode fault tree analysis (FTA) untuk menganalisa akar penyebab kegagalan, dan metode failure mode effect analysis (FMEA) untuk pembobotan nilai severity, occurance dan detection di dalam ketiga hal tersebut setiap permasalah tersebut dihitung hingga mendapatkan nilai risk priority number (RPN). Dari data tersebut selanjutnya akan diketahui akar permasalahan tersebut adalah mesin steam suhu nilai 144 merupakan nilai rpn tertinggi, selanjutnta penulis mencoba memberikan usulan perbaikan sebelumnya total reject 244.425 kg persentase 0.65% dan sesudah 69.284 kg persentase 0.36% denga biaya sebelum perbaikan total Rp. 881.840.120 dan sesudah Rp.255.474.078 berhasil menurunkan reject dibawah standar sekaligus menurunkan biaya pengeluran sebesar Rp.626.366.042. Kata Kunci : Reject, Kecap, FTA, FMEA

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Analisa Studi Keandalan Sistem Distribusi 20 KV di PT. PLN (PERSERO) UPJ Mojokerto Menggunakan Metode FMEA (FAILURE MODE EFFECT ANALYSIS)

CYCLOTRON ◽

10.30651/cl.v3i1.4304 ◽

2020 ◽

Vol 3 (1) ◽

Author(s):

Aang Fras Setiawan ◽

Titiek Suheta

Keyword(s):

Failure Mode ◽

System Reliability ◽

Distribution System ◽

Reliability Index ◽

Effect Analysis ◽

Supply And Distribution ◽

Mode Effect ◽

Fmea Method ◽

Major Equipment ◽

Failure Mode Effect Analysis

ABSTRAK - Keandalan sistem distribusi merupakan kemampuan sistem untuk memberikan suatu pasokan tenaga listrik yang cukup dengan kualitas memuaskan. Peningkatan kebutuhan tenaga listrik, menuntut tingkat keandalan yang lebih tinggi dalam penyediaan dan penyaluran dayanya. Tujuan penelitian ini adalah untuk menghitung tingkat keandalan sistem distribusi 20 kV pada UPJ Mojokerto dengan metode Failure Mode Effect Analysis (FMEA), di mana nilai dari indeks kegagalan dari setiap peralatan utama sistem distribusi diperhitungkan untuk mencari nilai indeks keandalan sistem secara menyeluruh. Studi kasus dilakukan di PT. PLN (persero) UPJ Mojokerto guna melihat pengaruh dari jumlah serta lokasi penempatan sectionalizer di sepanjang jaringan terhadap indeks keandalan sistem. Hasil analisa pada penyulang Gading didapatkan nilai SAIFI berdasarkan metode FMEA adalah 3,80237 dan simulasi sebesar 3,8174 sedangkan untuk nilai SAIDI adalah 11,9697 dan 12,1197. Dan untuk penyulang Bangsal nilai SAIFI berdasarkan metode FMEA sebesar 6,82974 dan simulasi sebesar 6,4743 sedangkan nilai SAIDI adalah 13,9370443 dan 14,5671. Nilai SAIFI dan SAIDI pada penyulang Gading dan Bangsal belum mencapai nilai standart yang di tetapkan oleh PT. PLN (persero), maka perlu di tingkatkan guna mencapai keandalan sistem distribusi yang baik. Kata Kunci : Keandalan, Sistem Distribusi, SAIDI, SAIFI, FMEA ABSTRACT - Reliability of a distribution system is the ability of the system to provide a sufficient supply of electric power with satisfactory quality. Increased demand for electricity, demands a higher level of reliability in the supply and distribution of power. The purpose of this study was to calculate the reliability level of the 20 kV distribution system at UPJ Mojokerto using the Failure Mode Effect Analysis (FMEA) method, where the value of the failure index of each major equipment distribution system was calculated to find the overall system reliability index value. Case studies conducted at PT. PLN (Persero) UPJ Mojokerto to see the effect of the number and location of the placement of sectionalizers along the network against the system reliability index. The results of analysis on Ivory feeders obtained SAIFI values based on the FMEA method were 3.80237 and the simulation was 3.8174 while those for SAIDI values were 11.9697 and 12.1197. And for Bangsal feeders, the SAIFI value based on the FMEA method is 6.82974 and the simulation is 6.4743 while the SAIDI values are 13.9370443 and 14.5671. The value of SAIFI and SAIDI for Ivory feeders and Bangsal has not yet reached the standard value set by PT. PLN (Persero), it needs to be improved in order to achieve good distribution system reliability. Keywords: Reliability, Distribution System, SAIDI, SAIFI, FM

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Application of Failure Mode Effect Analysis for Improved Scheduling in Maintenance of Machines

International Journal of Innovative Technology and Exploring Engineering - Special Issue ◽

10.35940/ijitee.e3025.049620 ◽

2020 ◽

Vol 9 (6) ◽

pp. 895-899

Keyword(s):

Failure Mode ◽

Work Flow ◽

Risk Priority Number ◽

Effect Analysis ◽

Mode Effect ◽

Lathe Machine ◽

Complete Failure ◽

Fmea Method ◽

Effective Analysis ◽

Failure Mode Effect Analysis

Maintenance of machines is crucial measures in order to have stable and improved work flow. Any kind of failure might result in complete failure of the machine. Hence it becomes essential to identify the vulnerable failures that might occur in the components of any machine. The present work is carried out in order to improve the scheduling in maintenance of a lathe machine. Different components of the machine are studied in this research. “Failure mean effective analysis (FMEA)” method is applied to identify the failures associated with the components of the machine. Risk priority number is calculated based on which the components are provided with ranks. The rank signifies the flow of maintenance for all the components. The results reveal that the flexure bearing needs the least maintenance as it has the highest rank.

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Improving Failure Mode & Effect Analysis (Fmea) Method Using Discrete Event Simulation

10.30707/etd2021.20210719070603154175.100 ◽

2021 ◽

Author(s):

Adil Abdukeyum

Keyword(s):

Failure Mode ◽

Discrete Event Simulation ◽

Discrete Event ◽

Effect Analysis ◽

Event Simulation ◽

Mode Effect ◽

Fmea Method ◽

Failure Mode Effect Analysis

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Machine Optimization of SNK HF Fabrication Plant in PT. Komatsu Indonesia with FMEA Method and Overall Equipment Effectiveness (OEE)

Journal of Technomaterials Physics ◽

10.32734/jotp.v3i2.6635 ◽

2021 ◽

Vol 3 (2) ◽

pp. 83-88

Author(s):

Titus Argarino ◽

Melya Dyanasari Sebayang ◽

Bantu Hotsan Manullang

Keyword(s):

Production Process ◽

Failure Mode ◽

Effect Analysis ◽

Important Thing ◽

Mode Effect ◽

Machine Parts ◽

Fmea Method ◽

Failure Mode Effect Analysis ◽

Production Facilities

The effectiveness of a machine is an important thing in the production process; the losses that arise can cause time losses and hamper the process, especially in vital production facilities. The SNK HF machine is a machine with category A or critical with the highest damage occurring throughout 2019–2020. Analysis of the condition of the machine’s effectiveness in this study was done by using the overall equipment effectiveness (OEE) method, namely by knowing the conditions of availability, performance and quality. The results of the OEE analysis are followed by a failure mode effect analysis (FMEA) to overcome the problems that occur. The condition of machine damage and the availability of machine parts are the factors that most affect the decrease in the effectiveness of the SNK HF machine.

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Risk analysis of cutting system under intuitionistic fuzzy environment

Reports in Mechanical Engineering ◽

10.31181/rme200101162k ◽

2020 ◽

Vol 1 (1) ◽

pp. 162-173

Author(s):

Dinesh Kumar Kushwaha ◽

◽

Dilbagh Panchal ◽

Anish Sachdeva ◽

◽

...

Keyword(s):

Risk Assessment ◽

Failure Mode ◽

Thermal Power ◽

Failure Detection ◽

Engineering System ◽

Effect Analysis ◽

Intuitionistic Fuzzy ◽

Mode Effect ◽

Cutting System ◽

Failure Mode Effect Analysis

Failure Mode Effect Analysis (FMEA) is popular and versatile approach applicable to risk assessment and safety improvement of a repairable engineering system. This method encompasses various fields such as manufacturing, healthcare, paper mill, thermal power industry, software industry, services, security etc. in terms of its application. In general, FMEA is based on Risk Priority Number (RPN) score which is found by product of probability of Occurrence (O), Severity of failure (S) and Failure Detection (D). As human judgement is approximate in nature, the accuracy of data obtained from FMEA members depend on degree of subjectivity. The subjective knowledge of members not only contains uncertainty but hesitation too which in turn, affect the results. Fuzzy FMEA considers uncertainty and vagueness of the data/ information obtained from experts. In order to take into account, the hesitation of experts and vague concept, in the present work we propose integrated framework based on Intuitionistic Fuzzy- Failure Mode Effect Analysis (IF-FMEA) and IF-Technique for Order Preference by Similarity to Ideal Solution (IF-TOPSIS) techniques to rank the listed failure causes. Failure cause Fibrizer (FR) was found to be the most critical failure cause with RPN score 0.500. IF-TOPSIS has been implemented within IF-FMEA to compare and verify ranking results obtained by both the IF based approaches. The proposed method was presented with its application for examining the risk assessment of cutting system in sugar mill industry situated in western Uttar Pradesh province of India. The result would be useful for the plant maintenance manager to fix the best maintenance schedule for improving availability of cutting system.

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