Proposed Policy Preventive Maintenance Machine Moriseiki NH 4000 DCG Method of Reliability Center Maintenance (RCM) And Risk Based Maintenance (RBM) Case Study PT Pudak Scientific

PT Pudak Scientific is a company engaged in the manufacture of aircraft parts industry. Meeting the precise and timely demand of aerospace parts from customers becomes a major corporate responsibility. However, Loss Revenue often occurs due to engine breakdown. So that cause because the production target is not achieved, the product reject, and the delay of delivery. One of the machines that often experience breakdown is Mori seiki NH4000 DCG. Mori seiki NH4000 DCG is the finishing machine for Blank fork End product. The demand for this part is quite large, making it a tough task for the Mori Seiki NH4000 DCG machine. But because the breakdown of the machine is high enough to cause production targets every month are often not met. In addition, Maintenance activities that have not noticed the characteristics of engine damage, as well as the distribution of historical data of the machine causing less effective and efficient actions resulted in substantial Maintenance costs. Based on the results of risk analysis of Mori Seiki NH4000 DCG engine damage, in terms of performance loss system caused by a large enough that is 3.773% of machine production capacity per year. This figure exceeds the risk acceptance criteria by the company that is 2%. Therefore it is necessary to find the appropriate Maintenance policy for the Mori Seiki NH4000 DCG machine. The approach is to use Reliability Centeres Maintenance and Risk Based Maintenance. Based on the above two approaches obtained the appropriate interval time so that the Maintenance activities more effective and can improve the efficiency of treatment by reducing the cost of care previously Rp167.506.286, - per year, to Rp 96.147.061, - per year. With the policy is expected to reduce engine breakdown and performance loss caused. So the number of risks that arise for the future are within the criteria of acceptance set by the company.   Keywords: Preventive Maintenance, Reliability centered Maintenance, risk based Maintenance, Performance los

ANALYSIS AND SIMULATION OF RELIABILITY IMPROVEMENT IN GEAR PUMP MACHINE USING LIFE CYCLE COST METHOD IN XYZ COMPANY

Abstract. Gear pump machine 51-98P01 is a machine that is available at XYZ company, which functions as a transportation machine for raw materials from one production process. Because of its function, if there is a downtime occurs on the machine, production process will stop operating because the raw material cannot be flowed. Those problems caused a large amount of expenses that company should pay because late of production. Downtime occurs due to several factors, such as failure to components on the machine, age that has exceeded the optimal age limit, and the number of maintenance crew that is not optimal. To solve the problems, the Life Cycle Cost (LCC) method is used to determine the optimum age of the machine and the optimal number of maintenance crew using the Life Cycle Cost (LCC) method. In addition, a calculation of the proposed maintenance time interval is also carried out to achieve a certain reliability value using a simulation of reliability improvement to see the effect of reliability on the total LCC. Based on data processing using the LCC method, it is known that LCC in 2018 is Rp1,333,195,316 while the optimum LCC is Rp.690,180,267 with optimal machine life of six years and the number of crew maintenance is one person. Simulation of reliability improvement that carried out on the gear pump machine components shows a decrease of  total LCC of the machine.Keywords: Downtime, Failure Cost Life Cycle Cost, Maintenance Crew, Reliabilit

OPTIMIZATION OF MACHINE PREVENTIVE MAINTENANCE SCHEDULING USING STEADY STATE GENETIC ALGORITHM

Maintenance management is one of the important factors to support the success of industrial activities. In order for an industry to have a high level of profit. Good maintenance management is needed to minimize costs lost due to the engine failure. Preventive maintenance activities are one of the company's efforts to be able to maintain the life span and engine performance. In conducting preventive maintenance activities, the company wants to maximize machine reliability with minimum costs. The existing maintenance activities implemented by the company are to doing the maintenance every 2 months, but with the implementation of this maintenance policy it still has many obstacles in its implementation. Therefore optimization is needed to overcome this problem, one of the methods proposed to do preventive maintenance scheduling is the steady state genetic algorithm optimization method. On completion, 3 types of fitness functions are used, Fitness function 1 is a fitness function by giving weights to total costs and reliability functions with conditions w1 + w2 = 1. Fitness function 2 is a fitness function that is used by having a given budget limit. While Fitness function 3 is a fitness function that is used to provide required reliability or reliability that the company wants to achieve. The input from the steady state genetic algorithm has 3 components, the time to failure distribution parameter, the cost and budget, and the iteration input from the genetic algorithm. Based on data that has a 2 parameter Weibull distribution with scale parameter lambda = 0.00184 and shape parameter beta = 1.38194. Found 3 preventive maintenance scheduling proposals for 24 months period. The first result using fitness function 1 produced a total cost of 28.66 million rupiahs with a reliability value of 91.78%. The second proposal using fitness function 2 produced a total cost of 29.75 million rupiahs with a reliability value of 92.47%. The third uses using fitness function 3 resulting in a total cost of 30.79 million rupiahs with a reliability value of 92.52%.Keywords: Preventive maintenance, Optimization, Reliability, Total cost, Steady State Genetic Algorithm

Performance Evaluation on Printing Machine Goss Universal Using Reliability Availability Maintainability (RAM) Analysis and Overall Equipment Effectiveness (OEE)

The development of science and technology that has been developed more rapidly at this time, along with the increasing need for information itself. By producing a newspaper every day then the states forced PT Pikiran Rakyat to further improve the smoothness, the effectiveness and efficiency of the printing. One way to measure the performance of machines in general by using OEE and to minimize the possibility of losses to be borne by the company is improving the Reliability, Availability and Maintainability (RAM). By using the data in the form of MTTF (Main Time to Failure) and MTTR (Main Time To Repair) of each subsystem of the printing press. Based on calculations using the method of Overall Equipment Effectiveness, by performing calculations based on three main parameters with a study for eight months or 5760 hours, show that the value of the Availability of 75%, the value of the Performance of 97%, and the value of Quality by 98%, then the system has OEE values of 71.60%. The system has a reliability score of 10.59% at 70 hours based on the analytical approach. Maintainability calculations using modeling reliability block diagram, it is found that the entire unit in the system has a chance to settle down a minimum of 12 hours to be able to function again with a probability of 100% to reach its original state. During the eight-month study, Inherent Availability of the system is 99.52% based on analytical approach and Operational Availability of the system is 73.91%. Keywords—Reliability, Availability, Maintainability, OEE, MTTF, MTT

Maintenance System of Universal Goss Printing Machine based on failure data using RCM and RCS method

Over time a machine will get experience a decrease in reliability, causing the engine to be damaged at the time of operation, thus disrupting the production line. To maintain a machine remains reliable then a good maintenance system is required. In this research, we will use Reliability Centered Maintenance (RCM) and Reliability Centered Spare (RCS) analysis on the critical system of Goss Universal printing machine based on engine failure data. The result of RCM analysis obtained the optimal preventive maintenance schedule and the type of treatment, while based on the RCS analysis obtained spare part needs following the maintenance schedule. With the result of this analysis, is expected where the machine will keep good and will continue to operate without a sudden breakdown under the production schedule's need. Based on RCM analysis for each critical subsystem obtained interval preventive maintenance for transfer roller 127.60 hours, Ink fountain roller 24.45 hours, ink form roller 29.23 hours respectively, and the wash-up device is no scheduled maintenance. For spare parts inventory strategies the result using RCS method are: transfer roller104 units, ink fountain roller requires 32 units, ink form roller 36 units and are holding spare policy required, and a wash-up device no holding spare parts. Keywords— Failure data, Maintenance System, RCM, RC

EVALUATION OF PERFORMANE CINCINATI DOUBLE GANTRY F MACHINE USING RELIABILITY, AVAILABILITY, MAINTAINABILITY, AND SAFETY ANALYSIS IN XYZ COMPANY

PT XYZ operate the machine Cincinati Double Gantry F since 1987. However, during the operating there are problems such as failure of the process that affect the performance of the machine so that the impact on the losses of the company, namely a decrease in revenue. Based on the damage data for the month of January 2016 – December 2018, the subsystem Axis and Electrical Panel & Control is a critical subsystem of the results of the risk matrix with the frequency of the highest damage, namely a total of 33 and 21. Therefore, the necessary steps to reduce losses that occur with conducting research to analyze the value of Reliability, Availability, Maintainability and Safety Analysis (RAMS). The results of the RAM by using the modeling of RBD based on the subsystem selected results obtained value of the reliability a subsystem of the Axis is lower than the Electrical Panel & Control. The time required to restore the subsystem Axis to normal range 1 hour (98%) and subsystems of Electrical Panel & Control ranged from 1 h (96%). Based on the evaluation standard IVARA World Class Maintenance Key Performance Indicators with leading indicators and lagging has reached the target of 95%. The results of research on the safety analysis at the time of the time interval of 16 hours a subsystem of the Axis is lower than on Electrical Panel & Control on the level of Safety Integrity Level However at the time of the time interval 80 hours, a subsystem of the Axis does not reach the target SIL according to standard IEC 61508.Keyword: 1 Cincinati Double Gantry F 2 Reliability Availability Maintainability 3 Safety Analysis, Maintenance Key Performance Indicator 4 SIL 5 IEC 6150

Performance Assessment Based on Reliability of Weaving M251 Machine Using Reliability, Availability & Maintainability (RAM) and Cost of Unreliability (COUR) Methods (Case Study at PT Buana Intan Gemilang)

The textile industry is one of industries that has an important role in the national economy. PT Buana Intan Gemilang (BIG) is one of textile industry in Indonesia which uses Weaving machine to produce motif and sajadah fabrics. The purpose of this research is to analyze the reliability of Weaving M251 machine that has the most damage in 2014. To avoid losses due to machine damage, the reliability, availability and maintainability of the machine need to be improved by using Reliability, Availability & Maintainability (RAM) Analysis method. In addition, the total cost caused by RAM problems can be calculated by using Cost of Unreliability (COUR) method. Based on the evaluation using Reliability Block Diagram (RBD) modeling, it is found that the critical subsystem reliability = 44.36% for 144 working hours and the total repair time that the critical subsystem needs to perform in acceptable operational condition , at least in 1 to 70 hours. There are two different forms of availability that have been calculated, therefore inherent availability = 95,546% which is used as leading indicator, and operational availability = 85,572% which used as lagging indicator. as it is compared, lagging indicator does not meet the performance of leading indicator. The total of unreliability cost when the machine is in active repair time = 39,580,689.02 IDR and within downtime = 135,588,452.13 IDR. Keywords—Cost of Unreliability (COUR), Lagging Indicator, Leading Indicator, Reliability, Availability & Maintainability (RAM) Analysis

Usulan Preventive Maintenance Pada Mesin Komori Ls440 Dengan Menggunakan Metode Reliability Centered Maintenance (Rcm II) Dan Risk Based Maintenance (Rbm) Di PT ABC

PT ABC merupakan Perusahaan cetak dalam skala nasional. Produk yang dihasilkan oleh Perusahaan merupakan buku ajar, majalah, surat kabar, dan lain sebagainya. Kegiatan maintenance yang ada PT ABC terbagi menajadi dua, yaitu preventive maintenance setiap senin dan kamis serta kegiatan corrective maintenance yang dilakukan jika mesin mengalami kegagalan fungsi. Kegagalan fungsi pada mesin Komori masih cukup tinggi. Oleh karena itu, diperlukan kegiatan pecegahaan untuk meningkatkan reliabilitas mesin. Metode yang dilakukan adalah Reliability Centered Maintenance, yaitu dengan menganalisis failure yang terjadi dengan menggunakan analisis Failure Mode and Effect Analysis dan Decision Worksheet. Hasil dari analisis ini merupakan preventive task masing-masing komponen. Sedangkan untuk menganalisis risiko yang diakibatkan jika mesin mengalami gagal fungsi, yaitu dengan metode Risk Based Maintenance. Hasil yang diperoleh dari nilai risiko yang ditanggung Perusahaan ketika mesin mengalami failure, yaitu sebesar Rp965.904.899,36. Berdasarkan hasil pengolahan data pada subsistem kritis diperoleh kesimpulan bahwa enam komponen dilakukan dengan task scheduled on condition, tiga komponen dengan task scheduled restoration, dan enam komponen dengan task scheduled discard. Sedangkan untuk interval waktu dalam pengerjaan preventive maintenance pada komponen tersebut disesuaikan dengan task yang diperoleh. Setelah mendapatkan interval waktu perawatan, kemudian ditentukan biaya perawatan usulan yang dikeluarkan Perusahaan, yaitu sebesar Rp971.567.519,69

Penilaian Risiko, Estimasi Interval Inspeksi, dan Metode Inspeksi pada Hydrocarbon Piping Menggunakan Metode Risk Based Inspection (RBI)

Piping adalah sistem perpipaan yang digunakan untuk mengalirkan fluida dari satu proses ke proses lainnya. Jenis piping yang diteliti adalah Hydrocarbon Piping yaitu sebagai penyalur fluida antara reaktor, regenerator, dan main column pada proses catalytic cracking. Fluida yang mengalir pada Hydrocarbon Piping dapat menyebabkan korosi dan mengakibatkan terjadinya penipisan bahkan kebocoran pipa sehingga menimbulkan dampak yang buruk, baik pada lingkungan, keamanan, keselamatan, dan kerugian biaya. Peralatan bertekanan seperti piping memerlukan program inspeksi agar dapat bekerja dengan baik. Risk Based Inspection (RBI) adalah suatu metode untuk menentukan rencana program inspeksi berdasarkan risiko kegagalan peralatan. Metode RBI yang digunakan adalah RBI Semi-Kuantitatif dengan standar API 581. Tujuan penelitian ini adalah untuk mengetahui tingkatan risiko, estimasi interval inspeksi, dan penentuan metode inspeksi pada piping. Dari hasil penelitian menunjukkan bahwa Hydrocarbon Piping terdiri dari 16% pipa dengan tingkat risiko low dan 84% pipa dengan tingkat risiko medium. Estimasi interval inspeksi dianjurkan tidak melebihi setengah remaining life pipa. Dengan mekanisme kerusakan thinning, metode inspeksi yang dianjurkan ialah profile radiography, UT scans, dan visual examination

Perencanaan Kebijakan Perawatan Mesin Corazza Ff100 Pada Line 3 PT Xyz Dengan Metode Reliability Centered Maintenance (Rcm) II

PT XYZ merupakan produsen yang bergerak dalam bisnis keju. Meskipun telah menerapkan kegiatan preventive maintenance, frekuensi kerusakannya masih tinggi menyebabkan terhambatnya kelancaran proses produksi serta mengindikasikan nilai keandalannya kecil. Oleh karena itu perlu dilakukan analisis kegiatan perawatan yang tepat sesuai dengan karakteristik kerusakan serta interval waktu kegiatan perawatan pada mesin Corazza FF100 dengan analisis Reliability Centered Maintenance (RCM) II yang menekankan pada karakteristik keandalan (reliability). Melakukan identifikasi risiko yang dipetakan dalam risk matrix. Tahapan dalam RCM yaitu pengukuran kualitatif dengan membuat Failure Mode and Effect Analysis (FMEA) untuk mengidentifikasi penyebab serta efek terjadinya kegagalan item. Untuk mengetahui konsekuensi yang ditimbulkan dilakukan klasifikasi berdasarkan Logic Tree Analysis (LTA) kemudian pemilihan tindakan kegiatan perawatan. Tahap selanjutnya yaitu pengukuran kuantitatif dengan melakukan pengumpulan data kerusakan dan data perbaikan untuk mendapatkan interval waktu perawatan. Maintainable item pada mesin Corazza FF100 berjumlah 27. Berdasarkan metode Reliability Centered Maintenance (RCM) didapatkan 67 kegiatan perawatan. Terdapat 17 scheduled discard task, 15 scheduled restoration task, 31 scheduled on condition dan 4 failure finding. Penentuan interval waktu perawatan berdasarkan kebijakan perawatannya dengan mempertimbangkan karakteristik kerusakan dan biaya perawatan