Enhance maintenance problem recognition techniques and its application to palm oil mills

This paper discusses the application of enhanced maintenance problem recognition techniques. The main contribution of this study is the proposed combined techniques, namely snapshot model, failure mode, effect and criticality analysis (FMECA), Pareto analysis, and decision analysis by using information technology (IT). The snapshot model is part of the maintenance modelling technique while FMECA, Pareto analysis, and decision analysis are part of maintenance reliability techniques. Each of the techniques and the proposed combined techniques is explained. The case study used for this enhanced technique was the palm oil mills maintenance problem. The result and possible further enhancement is also discussed

Enhanced maintenance problem recognition techniques and its application to palm oil mills

This paper discusses the application of enhanced maintenance problem recognition techniques. The main contribution of this study is the proposed combined techniques, namely snapshot model, failure mode, effect and criticality analysis (FMECA),Pareto analysis, and decision analysis by using information technology (IT). The snapshot model is part of the maintenance modelling technique while FMECA, Pareto analysis, and decision analysis are part of maintenance reliability techniques.Each of the techniques and the proposed combined techniques is explained. The case study used for this enhanced technique was the palm oil mills maintenance problem. The result and possible further enhancement is also discussed

Failure mode & effect analysis for improving data veracity and validity

Failure Mode & Effect Analysis (FMEA) is a method that has been used to improve reliability of products, processes, designs, and software for different applications, including electronics manufacturing. In this paper we propose a modification of this method to extend its application for data veracity and validity improvement. The proposed DVV-FMEA method is based on engineering features and in addition, provides transparency and understandability of the data and its pre-processing, making it reproducible and trustful

Integrating Failure Mode Effect Analysis into the Medical Device Approval Process

Medical devices that utilize computer software are becoming common place in today’s health care environment. Device failures can have life threatening consequences. The medical device approval process issued by the FDA should enhance the software testing requirements. In this paper we suggest that Failure Mode Effect Analysis (FEMA) should be a standard component in the testing of software in medical devices that can have life threatening consequences

Optimalisasi Perawatan Mesin Press dengan Metode Failure Mode Effect Analysis (FMEA)

Sistem perawatan yang dilakukan selama ini adalah bersifat breakdown maintenance yaitu pemeliharaan yang dilakukan setelah mesin mengalami kerusakan. Sistem ini belum memberikan data akurat kapan suatu mesin atau komponen mengalami kerusakan, sehingga strategi yang tepat untuk menjaga mesin tetap beroperasi adalah menentukan interval waktu perawatan yang optimal.Hasil analisis yang dilakukan dengan menggunakan metode Failure Mode Effect Analysis (FMEA) maka didapat komponen kritis pada Mesin Screw Press yaitu Komponen Worm Screw, Besi Shaft dan Press Cage diperoleh waktu penggantian Komponen Worm Screw 32 hari, Besi Shaft 68 hari, Press Cage 48 hari pada Mesin Screw Press 1 ; untuk Mesin Screw Press 2 Komponen Worm Screw 52 hari, Besi Shaft 128 hari, Press Cage 52 hari ; untuk Mesin Screw Press 3 Komponen Worm Screw dilakukan penggantian selama 56 hari, Besi Shaft 104 hari, Press Cage 64 hari ; untuk Mesin Screw Press 4 pada Komponen Worm Screw dilakukan penggantian selama 56 hari, Besi Shaft 72 hari, Press Cage 74 hari. Untuk Mesin Screw Press 5 pada Komponen Worm Screw dilakukan penggantian selama 50 hari, Besi Shaft 80 hari, Press Cage 92 ; hari dan untuk Mesin Screw Press 6 pada Komponen Worm Screw dengan interval waktu penggantian selama 52 hari, Besi Shaft 72 hari dan Press Cage 58 hari. Kata Kunci: FMEA, MTTF, MTTR, Downtime, Age Replacemen

Failure Mode Effect Analysis in Turning of Mild Steel Under MQL Condition

FMEA was commonly used to improve production quality by reducing workplace failures and preventing them from happening. Nowadays, tool failures are the most common problems that can be found in the machining practice. Hence, FMEA was used to reduce tool failure occurrence and improve the production quality. In this paper, FMEA analysis was done for a turning process of mild steel. Several turning operations were done, and the failure mode and failure effect were identified. Then, the tool failure effect was studied, and the causes were generated using the Ishikawa diagram. The occurrence, severity, and detection rating were assigned, and the Risk Priority Number (RPN) was generated. FMEA Risk Matrix was used to help provide a visual aid for classifying and categorizing the level of risk. The highest risk was then identified from the highest RPN value, and the cause and prevention methods were generated for each failure effect cause. This study can be used as a guide or reference in the turning process practice for a more effective process. &nbsp

Failure Mode Effect Analysis in Turning of Mild Steel Under MQL Condition

FMEA was commonly used to improve production quality by reducing workplace failures and preventing them from happening. Nowadays, tool failures are the most common problems that can be found in the machining practice. Hence, FMEA was used to reduce tool failure occurrence and improve the production quality. In this paper, FMEA analysis was done for a turning process of mild steel. Several turning operations were done, and the failure mode and failure effect were identified. Then, the tool failure effect was studied, and the causes were generated using the Ishikawa diagram. The occurrence, severity, and detection rating were assigned, and the Risk Priority Number (RPN) was generated. FMEA Risk Matrix was used to help provide a visual aid for classifying and categorizing the level of risk. The highest risk was then identified from the highest RPN value, and the cause and prevention methods were generated for each failure effect cause. This study can be used as a guide or reference in the turning process practice for a more effective process. &nbsp

Perbaikan Proses Delivery Dokumen Maintenance C-Check Pesawat dengan Metode CCFE, FMEA, dan PICA (Studi Kasus di PT. GMF Aeroasia Tbk.)

PT. GMF Aeroasia, Tbk is a company engaged in aircraft maintenance services. The aircraft maintenance lead time is regulated according to the agreement set forth in the agreement in the form of a work order, when the maintenance process takes place there is almost always a delay when working on the aircraft, both in terms of physical work or delivery of documents. These problems are several forms of waste, where waste is any activity that does not provide added value. Therefore, the purpose of this study is to identify the type of waste and determine the factors that cause waste in the delivery process of aircraft c-check maintenance documents. The method used in this study used a fishbone chart, cause failure mode effect, failure mode and effects analysis and problem identification and corrective action. Fishbone chart and cause failure mode effect are used to find waste that causes delay in document delivery, then analyzed using failure mode and effects analysis, three causes of the highest delay were found, namely stamps on incomplete documents (RPN 16), waiting for customer approval (RPN 16) and material certificates not available (RPN 12). Corrective Action was prepared as a recommendation to improve the delivery process for aircraft c-check maintenance documents. By knowing the types of waste and the factors causing waste in the delivery process of aircraft c-check maintenance documents at PT. GMF Aeroasia Tbk is expected to reduce waste and fulfill customer satisfaction. Keywords: Lead Time, Waste, Delay Delivery of Documents, Cause Failure Mode Effect Method, Corrective Actio

Upaya Penurunan Produk Cacat Pada Proses Painting Unit CN113R Dengan Metode Failure Mode Effect Analysis (FMEA)

Abstract PT.SGMW Motor Indonesia is a company which is engaged in the automotive field, especially in cars assembly with Wuling as its brand in Indonesia and the product called CN113R. In an effort to maintain product quality, PT.SGMW seeks to minimize the number of defects in each inspection unit. In order to attract large Indonesian market, the company needs to improve the quality of the product which are produced. From data collection conducted at PT. SGMW at Type Approval phase (TA) from February to March 2017, it was found that Sanding Mark defect is the biggest defect type that happened in PT.SGMW that is equal to 24% and this happened at painting process. Then in the next stage, after brainstorming process with related parties in the Paintshop Department to find out the main cause of Sanding Mark defect which is then shown through a fishbone diagram. To find out the improvement priority or follow-up to the causes described in fishbone diagram, I use 5W + 2 H method. In the next step, an improvement analysis is done using Failure Mode Effect Analysis (FMEA) method. after that, by the RPN result which is obtained, the most potential failure mode as the cause of the defect that must be handled immediately. From the observation results obtained the highest defect value is sanding mark. One of the causes of the highest Risk Priority Number (RPN) value in the Elpo sand section is because of the used of the orbital sender is tilted and angled. After the improvement, it can decrease the defect from 449 findings down to 297 findings, and lower repair cost from Rp. 142,863,718 to Rp 94,500,054. Keywords: Failure Mode Effect Analysis, Defect, Cost Of Poor Quality Abstrak PT.SGMW Motor Indonesia merupakan perusahaan yang bergerak pada bidang otomotif, khususnya dalam perakitan mobil dengan merk Wuling di Indonesia dengan produk yang diberi nama CN113R. Dalam upaya mempertahankan kualitas produk. PT.SGMW berusaha untuk meminimasi jumlah kecacatan dalam setiap unit inspeksinya, agar dapat menarik pasar bangsa Indonesia yang besar perusahaan tersebut perlu meningkatkan kemampuan dari segi kualitas produk yang dihasilkan. Dari pengumpulan data yang dilakukan di PT. SGMW pada fase Type Approval (TA) dari bulan Februari sampai dengan Maret 2017, didapatkan bahwa cacat Sanding Mark merupakan jenis cacat terbesar yang terjadi di PT.SGMW yaitu sebesar 24% dan hal ini terjadi pada proses pengecatan Lalu pada tahap berikutnya setelah dilakukan proses brainstorming dengan pihak terkait di dalam Department Paintshop untuk mencari penyebab utama cacat Sanding Mark yang kemudian hasilnya ditampilkan melalui diagram fishbone. Untuk mengetahui prioritas perbaikan atau tindak lanjut terhadap penyebab ~penyebab yang dipaparkan dalam diagram fishbone maka digunakanlah metode 5W + 2 H. Pada tahap selanjutnya, dilakukan analisis perbaikan dengan menggunakan metode Failure Mode Effect Analysis (FMEA), setelah itu melalui hasil RPN yang didapatkan, modus kegagalan potensial yang paling utama sebagai penyebab terjadinya kecacatan yang harus segera ditangani. Dari hasil pengamatan tersebut di peroleh nilai defect tertinggi adalah sanding mark. Salah satu penyebab nilai Risk Priority Number (RPN) tertinggi di bagian Elpo sand adalah karena metode penggunaan orbital sender miring dan menyudut. Setelah dilakukan perbaikan sehingga dapat menurunkan defect dari 449 temuan turun menjadi 297 temuan, dan menurunkan biaya repair dari Rp. 142.863.718 menjadi Rp 94.500.054. Kata kunci: Failure Mode Effect Analysis, Defect, Cost Of Poor Quality Reference: Ansori, N., & Mustajib, M. I. (2013). Sistem Perawatan Terpadu (IMS). Yogyakarta: Graha Ilmu. Abdul Aziz, Uzer (2017). Analisis Defect Burry Pada Produk Part Holder Wire Dengan Metode Failure Mode Effect Analisys (FMEA) Di PT.PSC .Universitas Bhasysangkara Jakarta, Jakarta. Fahmi, I. (2014). MAnajemen Produksi dan Operasi. Bandung: Alfabeta. Gasperz, V. (2012). All-In-One Management Tool Book. PT Gramedia Pustaka Utama. Gasperz, V (2014). Pedoman Implementasi Program SIX SIGMA Terintegrasi Dengan ISO 9001:2000, MBNQA, dan HACCP. Jakarta. PT. Gramedia Pustaka Utama. Ginting,Rosnani (2007). Sistem Produksi, Edisi Pertama, Graha ilmu Yogyakarta Indri Parwati, Cyrilla (2016). Analisis Pengendalian Kualitas produk STeel Pipes Dan Tubulars dengan Menggunakan Metode Failure Mode Effect Analisys (FMEA) Di PT.Dwi Sumber Arca Waja Batam.. Jurusan Tehnik Industri Institut Sains & Teknologi AKPRIND Yogyakarta. Jaifandra Maradika, Yogi (2016). Analisis KegagalanProses produksi Pipe Collar dengan Menggunakan Metode Failure Mode Effect Analisys (FMEA) Di PT.Bannex Indonesia. Universitas Bhasysangkara Jakarta, Jakarta. Kurniawan, F. (2013). Teknik dan Aplikasi Manajemen Perawatan Industri. Yogyakarta. PT. Graha Ilmu. Yamit, Z. (2013). Manajemen Kualitas Produk dan Jasa. Yogyakarta. Ekonisi

Evaluasi Distributed Control System pada PLTU dengan Failure Mode, Effect and Criticaly Analysis (FMECA)

Steam power plants (PLTU) are power plants that have the largest percentage of power plants owned by PLN. The main controller in a PLTU usually uses a Distributed Control System (DCS). The reliability of DCS in a PLTU must be maintained properly so that the power plant does not experience a control failure that causes the PLTU to stop suddenly. DCS PLTU Sebalang Unit 1 has used the FMEA method to determine its maintenance strategy, but the FMEA has not defined the function of the equipment, functional failure, the effect of failure, and criticality analysis (CA) of the equipment. failure mode prioritization has not been carried out. With the FMECA conducted in this study, the priority of the failure mode can be carried out effectively so that the priority determination of DCS maintenance can be carried out. Results of the FMECA that have been carried out, it is known that the failure that occurs in the DCS CPU has the highest RPN value (140). The maintenance strategy obtained from the FMECA results is preventive maintenance (PM), namely: 1) checking the power supply voltage, 2) checking the communication status, idle time status, load and CPU status, and maintenance run to failure (RTF) CPU replacement if there is damage to the CPU. FCS CPUs