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

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.

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

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

scholarly journals Usulan Pengendalian Kualitas Produksi Benang Carded dengan Metode Six Sigma

2018 ◽  
Vol 4 (1) ◽  
pp. 38
Author(s):  
Abdul Manan ◽  
Firdanis Setyaning Handika ◽  
Ahmad Nalhadi
Keyword(s):  
Production Process ◽  
Failure Mode ◽  
Six Sigma ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Sigma Level ◽  
Mode Effect ◽  
Target Set ◽  
Failure Mode Effect Analysis

A yarn company strives to produce good and quality products, but the production process that is carried out by each person will produce products targeted at a target that has been set at 5%. This study uses the Six Sigma method but only until the improvement stage. The research is to determine the DPMO value and sigma level in the spinning production process, to know what factors cause defects and new parameters to reduce the defect. Based on the results of the study that the DPMO on the type of CD thread in the spinning section is 17,130 and the sigma level is 3,6. The level of sigma that has dominated the Indonesian industry average, but has a defect of 8.7%, the target set at 5%. Damaged and dirty apron, clogged trumpet, and leaky hose are factors that plan defects. Furthermore, with Failure Mode Effect Analysis (FMEA), the highest value of Risk Priority Number (RPN) in tangled defects is that the apron is damaged (140) and clogged trumpet (120), while the highest RPN value is gross dirty, i.e., dirty apron (150) and hose leaking lubricant (120).

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

CYCLOTRON ◽  
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

scholarly journals Analisa Kinerja Mesin Roughing Stand dengan Menggunakan Metode Overall Equipment Effectiveness (OEE) dan Failure Mode Effect Analysis (FMEA)

2017 ◽  
Vol 3 (2) ◽  
pp. 55
Author(s):  
Hasrul Hasrul ◽  
M. Jihan Shofa ◽  
Heru Winarno
Keyword(s):  
Production Process ◽  
Failure Mode ◽  
Historical Data ◽  
Product Formation ◽  
Risk Priority Number ◽  
Steel Product ◽  
Effect Analysis ◽  
Mode Effect ◽  
Potential Failure ◽  
Failure Mode Effect Analysis

The roughing stand machine functions for steel/product formation and the roll has five stands, and from each position has a different turn. In the production process, this machine also experiences obstacles that hinder the process [of production]. This study aims to determine the value of Overall Equipment Effectiveness (OEE) and analysis of the causes of OEE values have not been maximized based on the review of Failure Mode and Effect Analysis (FMEA). The data used are historical data of roughing stand machines during July 2016-December 2016. Based on the data processing performed, the results of the Overall Equipment Effectiveness (OEE) obtained on the Roughing Stand machine purchased at 57.5. The potential failure priority is base on the order of Risk Priority Number (RPN), the screw up non-working item has the most considerable RPN value (56). Regular lubrication is one way to maximize screw up performance..

scholarly journals Analisis Defect dengan Metode Fault Tree Analysis dan Failure Mode Effect Analysis

2019 ◽  
Vol 2 (2) ◽  
pp. 62-72
Author(s):  
Evan Nugraha ◽  
Rini Mulyani Sari
Keyword(s):  
Production Process ◽  
Failure Mode ◽  
Fault Tree ◽  
Fault Tree Analysis ◽  
Analysis Method ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Tree Analysis ◽  
Mode Effect ◽  
Failure Mode Effect Analysis

There was a phenomenon that occurred in garment companies, namely the existence of defect products in the production process. In the sewing process, defects occurred with an average percentage of 6,67% in the first three months of early 2019. This 6,67% was a percentage of disability that exceeded the company percentage limit of 5%, thus disrupting the production process. The primary purposed of analyzing the factors of product defects was to find out the causes and solutions to the company. The Fault Tree Analysis method was used to find out the root caused of product defects. Three main problems caused product defects, namely 1) untidy stitches, 2) stitches that exceeded the specified size, and 3) straightened stitches. By using the Failure Mode Effect Analysis method, the three problems were caused by human error and the absence of a Standard Operating Procedure in the production process. As a solution to problems in the company, the Risk Priority Number value was used. From this study the result obtained 1 Risk Priority Number value is the proposed improvement.

scholarly journals A Case Study on Recall of used Scopes in the Endoscopy Department by using a Failure Mode & Effect Analysis (FMEA) Proactive Risk Management

2020 ◽  
pp. 13-24
Author(s):  
Zuber Mujeeb Shaikh
Keyword(s):  
Risk Management ◽  
Failure Mode ◽  
Failure Modes ◽  
Risk Priority Number ◽  
Effect Analysis ◽  
Mode Effect ◽  
Potential Failure ◽  
Failure Mode Effect Analysis

Failure Mode and Effects Analysis (FMEA) is the process of reviewing as many components, assemblies, and subsystems as possible to identify potential failure modes in a system and their causes and effects. The study revealed that the Risk Priority Number (RPN) was initially 450 and it has decreased to 90 after implementing all the actions in FMEA.

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