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

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).

2017 ◽  
Vol 3 (2) ◽  
pp. 55
Author(s):  
Hasrul Hasrul ◽  
M. Jihan Shofa ◽  
Heru Winarno

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..


2019 ◽  
Vol 2 (2) ◽  
pp. 62-72
Author(s):  
Evan Nugraha ◽  
Rini Mulyani Sari

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.


Jurnal IPTEK ◽  
2020 ◽  
Vol 4 (2) ◽  
Author(s):  
Ni Made Sudri ◽  
Yenny Widianty ◽  
Anissa Fernanda

Perbaikan Desain sistem Industri Tekstil dengan Six Sigma dan FMEA untuk peningkatan mutu proses. Six Sigma merupakan metoda peningkatan kualitas secara terus menerus ,dengan cara meminimalkan jumlah cacat. FMEA (Failure Mode Effect Analysis) alat dipergunakan untuk bantu penentuan tindakan yang sesuai , penghilangan mode kegagalan secara prioritas. Selanjutnya tahapan improve untuk penentuan faktor paling berpengaruh terhadap terjadinya cacat warna, supaya pengaruh dari factor gangguan jadi minimum. Apabila fungsi kontrol dilakukan dan factor penyebab cacat tidak muncul lagi akan terjadi peningkatan nilai sigma. Hasil analisa FMEA diperoleh factor temperature mesin dan material yang paling berpengaruh terhadap terjadinya cacat warna, dengan nilai RPN masing –masing 210 dan 120, Hasil perhitungan Six Sigma terjadi peningkatan nilai sigma darikondisi awal sebesar 3,78 sigma menjadi 4,93 sigma, atau terjadipeningkatan kemampuan proses 1,15 sigma. Usulan perbaikan menggunakan DOE (design of experiment) agar cacat warna tidak muncul disarankan dengan seting alat control suhu mesin thermosol dan pencampuran bahan kimia NaCl dioptimalkan. Kata Kunci : Six Sigma, FMEA, DOE


2020 ◽  
Vol 1 (1) ◽  
pp. 31-44
Author(s):  
Iskandar Zulkarnaen ◽  
Daonil ◽  
Akbar Supriadi

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


Author(s):  
Bramantio Andananta Chrisna Putra

Industrial development in Indonesia is growing rapidly. This should be balanced with the application of good HA safety risk management to workplace hazard risks. As in PT. X Lumajang Regency, in its production process has great potential hazard. One of them is in the cane knife tool at Gilingan Station that has been damaged in operation and has an employee accident impact. Therefore, to prevent the occurrence of recurrence of risk assessment, including hazard identification, risk assessment and hazard control. The purpose of this study is to conduct risk assessment using the method of failure mode effect analysis (FMEA) on the Cane Knife production process tool in PT. X Lumajang District. This research is descriptive research. The target of this research is sugar production process at PT. X with the informant is 1 person Quality Control (QC), 1 person production operators and 1 supervisor. The results show that there are 6 (six) failure modes that occur in the cane knife tool. Based on the Risk Priority Number (RPN), the highest failure mode occurs is a broken clutch string. While for risk control, quite enough. This is because there have been risk control efforts include technical control that is the installation of safety valve, administrative control is the application of SOP for workers and personal protective equipment. But for personal protective equipment only safety helmet, for other companies do not provide. The conclusion that can be drawn is the need for better risk control, especially on the damage that occurred on the clutch rope broken tool cane knife.Keywords: cane knife, failure mode effect analysis, risk assessment


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.


2021 ◽  
Vol 6 (4) ◽  
pp. 1-6
Author(s):  
Nuur Apriliani Rahayu ◽  
Sugeng Santoso

PT. Elastis Reka Aktif including companies engaged in manufacturing made from rHDPE (recycling High Density Polyethylene). The problem that often occurs is that the achievement of the Not Good Key Point Indicator exceeds the tolerance given by management by 1%. Therefore, improvements were made using the Six Sigma method and the Failure Mode Effect Analysis method in order to get the priority of improvement targets. The first improvement proposal given to the company is for RPN 280, namely the material characteristics are not homogeneous by proposing a re-design of the silo which is in the pelletizing process and the fourth is RPN 252 where the roll takeup and winder positions are not parallel, namely by providing area boundaries in order to minimize the position not being aligned. parallel. After providing a proposal for each potential problem and socializing it to the production side, it is hoped that it can reduce the reject rate in the blowing process.


2017 ◽  
Vol 3 (2) ◽  
pp. 67
Author(s):  
Ikhsan Wicaksono ◽  
Tri Joko Wibowo ◽  
M. Jihan Shofa

Loss on a working system is one of the causes of the cost of the process to swell. The loss that reaches more than 450 tons/month on a cooling water system at a chemical company in the Serang area causes the company's expenses to swell. This study aims to determine the cause of cooling water wash as a basis for process improvement by using Six Sigma and Failure Mode Effect Analysis (FMEA). Data analysis results showed that cooling water loss is too little backwash filter duration, service filter duration is not optimum, and flow unreadable side stream. Improvements by increasing the length of the backwash, raising the service time of the sand filter to every two days, and cleaning the rotameter can increase the sigma value from 3.5 to 4.5.


2020 ◽  
Vol 20 (2) ◽  
pp. 67
Author(s):  
Mansur Budi Yahman ◽  
Dharma Widada ◽  
Anggiarini Profita

ABSTRACT UD Sido Muncul factory is a rice milling business that produces rice for consumed which in its production is inseparable from the risk. These risks cause a disruption in the production process and also cause losses such as the cessation of the production process so that it cannot meet demand. To manage the risks that occur, the Fuzzy Failure Mode Effect Analysis (Fuzzy FMEA) and Analytical Hierarchy Process (AHP) methods are used. The risk identification use the production process flow in general, namely raw material (input), production (process), and finished product (output) factors. From the results of FMEA fuzzy data processing, a total of 25 risks and priority risks from each factor were found, those are; the risk of competing rice buyers (894) very high; the risk of damage to the prime mover 883 very high, and the risk of competing suppliers of rice (748) high-very high. To mitigate the risks priority, 7 alternative strategies were developed. The priority mitigation strategies were chosen for each risk factor; the partnership building strategy (0.731) for input risk factors; routine engine maintenance strategies (0.637) for process risk factors and the product quality maintenance strategy (0.637) for output risk factors.   Keywords: Risk Management, Production Processes Risk, Mitigation Strategy, Fuzzy FMEA, AHP   ABSTRAK Pabrik UD Sido Muncul merupakan usaha penggilingan padi yang memproduksi beras siap konsumsi yang didalam produksinya tidak terlepas dari adanya risiko. Risiko tersebut menyebabkan terganggunya proses produksi dan menyebabkan kerugian seperti terhentinya proses produksi sehingga tidak dapat memenuhi permintaan. Untuk dapat mengelola risiko yang terjadi digunakan metode Fuzzy Failure Mode Effect Analysis (Fuzzy FMEA) dan Analytical Hierarchy Process (AHP). Identifikasi risiko menggunakan alur proses produksi secara umum yaitu faktor bahan baku (input), proses produksi (process), dan produk jadi (output). Dari hasil pengolahan data fuzzy FMEA didapatkan total 25 risiko dan risiko prioritas dari setiap faktor yaitu risiko pesaing pembeli padi (894) very high, risiko kerusakan pada motor penggerak utama 883 very high, dan risiko pesaing supplier beras (748) high-very high. Untuk memitigasi risiko prioritas maka dikembangkan 7 alternatif strategi. Adapun strategi mitigasi prioritas yang terpilih untuk setiap faktor risiko yaitu strategi menjalin kemitraan (0,731) untuk faktor risiko input, strategi pemeliharaan mesin secara rutin (0,637) untuk faktor risiko process dan strategi menjaga kualitas produk (0,637) untuk faktor risiko output.   Kata kunci: Manajemen Risiko, Risiko Proses Produksi, Strategi Mitigasi, Fuzzy FMEA,  AHP


Author(s):  
Zuber Mujeeb Shaikh

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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