scholarly journals ANALYZE MACHINE MAINTENANCE COST WITH CORRECTIVE METHOD AND PREVENTIVE METHOD TO INCREASE PRODUCTION RESULT

2019 ◽  
Vol 2 (1) ◽  
pp. 1-8
Author(s):  
Chamdan Purnama
Keyword(s):  
Production Process ◽  
Maintenance Cost ◽  
Maintenance Costs ◽  
Machine Maintenance ◽  
Maintenance System ◽  
Preventive Method ◽  
Engine Maintenance ◽  
The Cost ◽  
Corrective Method

The object of research is the engine maintenance system that is on the CV. Fajar Offset. The production process is often disrupted by the high amount of damage, which results in maintenance costs. Machines that often experience damage affect the printed product to be produced. The amount of downtime will affect the profits that will have an effect on the swollen maintenance costs of the budget that has been prepared. The purpose of this study is to analyze the cost of machine maintenance with corrective method and preventive method against increase production result. The results showed that machine maintenance was done by corrective method and preventive method proven to have an effect on increase production result.

Assessing Maintenance Cost for Design or Re-Design of Complex Machinery

2002 ◽  
Author(s):  
Alley Butler ◽  
Dan Baldwin ◽  
Mohit Kashyap
Keyword(s):  
Cost Model ◽  
Open Architecture ◽  
Maintenance Cost ◽  
Preventative Maintenance ◽  
Maintenance Costs ◽  
Time Value Of Money ◽  
Turbine Generators ◽  
System Data ◽  
The Cost

Maintenance costs are often significant for complex machinery, and organizations that are able to accurately assess maintenance costs for complex machinery can design or re-design the machinery to reduce maintenance expenses. This paper provides a review of relevant reliability theory to provide a background for model construction. The maintenance cost model is then developed from a probabilistic perspective, with a hierarchical breakdown of the complex machinery, and with consideration of the time value of money. A framework for the cost model is offered in which the cost of repair and preventative maintenance is considered along with the downtime costs for repair or preventative maintenance. As a proof of concept, maintenance costs for Ship Service Gas Turbine Generators (SSGTG) are developed from the Navy’s OARS (Open Architecture Retrieval System) data. Problems with data quality and heuristic adjustment of the data are discussed, recognizing that work is ongoing to improve the quality of the Navy’s maintenance data. Cognition Corporation’s Cost Advantage software is used for the modeling effort, providing an ability to focus on maintenance cost at any level of detail and to obtain cost roll up, as needed. Conclusions are drawn with respect to the modeling of maintenance costs for complex machinery.

MODEL BIAYA PEMELIHARAAN FASILITAS PADA BANDAR UDARA NGURAH RAI BALI

1970 ◽  
Author(s):  
Reni Dewita ◽  
I G. A. Adnyana Putera ◽  
I G. Putu Suparsa
Keyword(s):  
Linear Regression ◽  
Cost Model ◽  
Regression Equation ◽  
Maintenance Cost ◽  
Quality Level ◽  
Road Maintenance ◽  
Linear Regression Equation ◽  
Maintenance Costs ◽  
Facility Maintenance ◽  
The Cost

Facilities in an airport requires maintenance activity in order to achieve excellent quality level and able to support activities at the airport to avoid negative impacts, which is the declining quality of the facility that can lead to lower levels of the productivity carried out in an airport. Maintenance facilities at Bali's Ngurah Rai airport need the maintenance costs planning. To get proper maintenance actions,  the maintenance costs early stages of planning phase needs to develop a model of facility maintenance costs that can provide the maintenance costs estimates quickly and accurately. To produce a maintenance costs model we should identify the maintenance activities that exist at Ngurah Rai airport. Maintenance costs data used is within the last 5 years (2007-2011). Using the Cost Significant Model methode and the linear regression equation it showed that several of the facility maintenace significantly affect the facility maintenance costs in the Ngurah Rai Airport which is the cost of passenger terminal building maintenance (X6), the cost of runway maintenance (X1), the cost of taxiway maintenance (X2), the cost of air conditioning installation maintenance (X14), the cost of road maintenance (X4), the cost of vehicle parking maintenance (X5), and the cost of navigation and communication equipment maintenance (X10). There is 3  linear regression equation model which is 1) Y = 11873745878,77 + 0,993 X1 + 0,826 X2 + 0,334 X4 + 1,181 X6, 2) Y = -698840481,94 + 1,327 X1 + 1,716 X2 + 5,516 X5+ 3,060 X14, and 3) Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14. After doing the Cost Model Factor (CMF) test to the three linear regression equation, the most accurate equation is linear regression equation Y = 82110363478,07 + 1,013 X1 - 17,223X5 + 22,406 X10 - 12,035 X14 that has the average ratio 0.006% of the actual cost, so it is the best facility maintenance cost model at Bali's Ngurah Rai Airport.

scholarly journals Analisis Pengendalian Kualitas Cacat Produk Kaleng 307 di PT.X Menggunakan Metode Six Sigma

2019 ◽  
Vol 12 (2) ◽  
pp. 52
Author(s):  
Qoyinul Amin ◽  
Dedi Dwilaksana ◽  
Nasrul Ilminnafik
Keyword(s):  
Problem Solving ◽  
Production Process ◽  
Six Sigma ◽  
Raw Materials ◽  
Machine Maintenance ◽  
Sigma Level ◽  
Production Area ◽  
The Right ◽  
Engine Maintenance ◽  
Damaged Materials

Pengendalian kualitas merupakan sebuah teknik yang dapat dilakukan mulai dari tahap sebelum proses produksi hingga proses produksi berakhir. Six sigma merupakan sebuah metodologi terstruktur untuk memperbaiki proses dengan menggunakan statistik dan problem solving tools secara intensif menuju target 3,4 kegagalan per satu juta kesempatan. PT. X bergerak di bidang industri pembuatan kaleng makanan dengan salah satu produknya adalah kaleng tipe two piece cans 307. Berdasarkan informasi perusahaan, pada proses produksi kaleng tipe tersebut seringkali ditemukan produk mengalami cacat yang merugikan perusahaan. Penelitian ini dilakukan untuk mengetahui bagaimana cara yang tepat untuk meminimalkan cacat kaleng tipe tersebut dengan menggunakan metode six sigma. Hasil penelitian diketahui bahwa penyebab utama cacat adalah pekerja kurang teliti, setting clearence dies yang terlalu rapat, dies kemasukan afval, pisau press tumpul, bahan kotor dan rusak, perawatan mesin yang tidak dilakukan secara berkala, area produksi tidak rapi dan bising. Nilai DPMO sebesar 2844 yang dikonversikan kedalam sigma level yakni 4.27. Usulan perbaikan dengan Five-M Checklist meliputi memberikan pelatihan dan memperketat pengawasan kepada pekerja, melakukan setting mesin sesuai prosedur serta ubah clearence dies menjadi 0,24 mm, memperketat pemeriksaan bahan baku kaleng, melaksanakan perawatan mesin sesuai dengan jadwal yang telah ditentukan, menjaga kebersihan dan kerapian area produksi. Quality control is a technique that can be carried out from before the production process until the production process ends. Six sigma is a structured solution to process improvement using statistics and problem solving tools that intensively reach the target of 3.4 recovery per one million opportunities. PT. X is engaged in the industry of making cans with one of its products is a 307 two-piece can. Based on company information, in the production process, cans are found to find products that can save the company. This research was conducted to find out the right way to overcome this type of defect by using the six sigma method. The results of the study are known to be related to the fact that workers do not have meticulous, clear dead settings that are too tight, afval conceded dies, blunt press blades, dirty and damaged materials, machine maintenance that is not officially done, production area is not neat and noisy. The DPMO value is 2844 which is converted into sigma level which is 4.27. Proposed improvements with the Five-M Checklist provide training and tighten supervision to workers, make machine arrangements according to procedures and change clearly to 0.24 mm, tighten inspection of tin raw materials, manage engine maintenance according to agreed schedules, care about cleanliness and neatness production area.

scholarly journals Machine Maintenance Design using Markov Chain Method to Reduce Maintenance Costs

2021 ◽  
Vol 4 (1) ◽  
pp. 6-25
Author(s):  
Akhmad Syakhroni ◽  
Rizka Fajar Adi Darmawan ◽  
Novi Marlyana
Keyword(s):  
Markov Chain ◽  
Cost Savings ◽  
Maintenance Costs ◽  
Machine Maintenance ◽  
Markov Chain Method ◽  
Maintenance Time ◽  
Wheel Loaders ◽  
The Cost ◽  
A Company ◽  
Ready Mix Concrete

PT. XYZ is a company that focuses on construction with ready mix concrete product (cast). The problem faced by the company is that the schedule is not suitable for machine maintenance activities so that it still results in high maintenance costs incurred by the company. By using the markov chain method can plan maintenance time in order to reduce downtime so as to minimize maintenance costs. The results obtained by the proposal for the company are for proposal I it takes 49.78 hours = 50 hours at a cost of Rp. 16,984,605, the cost savings of Rp. 73,545,395 (81.24%). Schedule for each machine such as wheel loaders every 14,009 hours, batching plant machines every 16,604 hours, truck mixer machines every 19,168 hours. Scheduling the second proposal will take 26.62 hours = 27 hours at a cost of Rp. 9,080,664, the cost savings of Rp. 81,449,336 (89.97%). Schedule for every machine such as wheel loaders every 7,490 hours, batching plant machines every 8,877 hours, mixer truck machines every 10,248 hours. Judging from the results obtained, the recommendation given is

ANALISIS PEMELIHARAAN MESIN RIDGER PALIR DI PT GREAT GIANT PINEAPPLE

2018 ◽  
Vol 2 (1) ◽  
Author(s):  
Burhan Nudin ◽  
Keyword(s):  
Preventive Maintenance ◽  
Spare Parts ◽  
High Price ◽  
Maintenance Period ◽  
Preventative Maintenance ◽  
Corrective Maintenance ◽  
Maintenance System ◽  
Maintenance Activities ◽  
Engine Maintenance ◽  
The Cost

Abstract The purpose of this study is to determine the optimization of machine maintenance which is applied by the company (companies), the problems that arise in the maintenance system, and the cost of both preventive maintenance and subsequent corrective maintenance activities, to determine the alternatives that is most optimal. The case study will be conducted in the PT Great Giant Pineapple by focusing the research on Ridger Palir machine. The selection will done in this machine, that is to say, considering terms of maintenance, and the high price of the spare parts. Based on the research results that have been done on PT Great Giant Pineapple, the engine maintenance activities, the general implementation of the engine maintenance, shows the company has been running pretty well, but not yet optimal. Out of the problems found in these, the author tried to find a solution by taking into account the cost efficient in carrying out maintenance and engine solutions to the problem of spare part procurement. Preventive maintenance system may be optimal for the efficiency of the company if the determination of the machine preventative maintenance period is predominant. Machine preventative maintenance period can be optimized with the average, that is, the average treatment which cab conducted once every 6 months. Keywords: maintenance, preventive maintenance, corrective maintenance

scholarly journals Mass Rapid Transit Operation and Maintenance Cost Calculation Model

2020 ◽  
Vol 2020 ◽  
pp. 1-6
Author(s):  
Rahmat Nurcahyo ◽  
F. Farizal ◽  
Bimo M. I. Arifianto ◽  
Muhammad Habiburrahman
Keyword(s):  
Cost Model ◽  
Calculation Model ◽  
Maintenance Cost ◽  
Cost Calculation ◽  
Rapid Transit ◽  
Maintenance Costs ◽  
Operation And Maintenance ◽  
Transit Operation ◽  
The Cost ◽  
Mass Rapid Transit

Mass rapid transit (MRT) is an efficient transportation mode that is urgently needed by a growing city such as Jakarta, Indonesia. However, limited research has attempted to evaluate the system’s current performance through a comprehensive, unit-based calculation of the costs of MRT operation and maintenance. This research aimed to develop a system for calculating and comparing MRT operation and maintenance costs per kilometer per year. The cost model has three components, namely, capital, operation cost, and maintenance cost, which are, respectively, calculated based on their percentage toward total cost. The cost model calculation determined that Jakarta MRT operation and maintenance costs total USD 8.44 million per kilometer per year. This result was compared to other countries’ MRT operations.

scholarly journals ANALISIS KEBIJAKAN PEMELIHARAAN MESIN DALAM RANGKA MEMINIMUMKAN BIAYA PEMELIHARAAN PADA PT PARAMOUNT BED INDONESIA

2018 ◽  
Vol 1 (2) ◽  
pp. 86-93
Author(s):  
Tutus Rully ◽  
Carolina Feronika Putri
Keyword(s):  
Production Process ◽  
Quantitative Data ◽  
Minimum Cost ◽  
Engine Maintenance ◽  
The Cost

ABSTRACTThis study aimed to describe how the engine maintenance performed by PT Indonesia Paramount Bed inminimizing the cost of maintenance pasa press machine. The Research was about on engine maintenance inminimizing the cost of maintenance at PT. Paramount Bed Indonesia by using quantitative data and datasources that used are primary and secondary. The method of analysis that used in the study is the case studymethod. The company has been doing engine maintenance in accordance with the existing theory. But themaintenance of the company is not optimal because pasa production process still occurs frequently stopedengine suddenly. Therefore, companies should evaluate the maintenance periodically to the next productionrun properly and damage to the product that occurs can be less.Keywords: Maintenance of the machine and the Minimum Cost

scholarly journals ANALISIS PEMELIHARAAN MESIN CCO (CRUDE COCONUT OIL) STUDI KASUS PADA PT. SPO AGRO RESOURCES

2020 ◽  
Vol 6 (1) ◽  
pp. 10-19
Author(s):  
Dewi Sartika ◽  
Asngadi Asngadi ◽  
Syamsuddin Syamsuddin
Keyword(s):  
Preventive Maintenance ◽  
Quantitative Methods ◽  
Coconut Oil ◽  
Maintenance Cost ◽  
Maintenance Costs ◽  
Machine Maintenance ◽  
Time Period ◽  
Calculation Results ◽  
Maintenance Activities ◽  
Maintenance Policies

This  study  aims  to  determine  and  analyze  machine  maintenance carried  out  by  PT.  SPO  Agro Resources and to find out whether the presence of preventive maintenance policies can improve the effectiveness  of  time  and  costs.  This  research  uses  qualitative methods  by  describing  maintenance activities carried out by PT. SPO Agro Resources, as well as using quantitative methods in the form of mathematical  statistics  as  a  tool  to  help  decide  policies  to  be taken  at  a  certain  time  period  and efficiency  measurements  using descriptive  percentages.  The  results  showed  preventive  maintenance costs  once  a  month  Rp.138,012,968, - efficiency  value  was  39.63%, preventive  maintenance  costs every two months Rp.196,689,315, - efficiency value was 56.48%, preventive maintenance costs every three months  Rp.  258,731,341, - the  efficiency  value  is  74.29%,  repair maintenance  costs Rp.247,164,000, - the efficiency value is 70.97%. Based on the calculation it is known that the policy that  makes maintenance  costs  efficient  is  maintenance  once  a  month  because this  policy  is  the smallest maintenance cost compared to other policies, where the percentage value is smaller which is 39.63%,  according  to table  2 which  states  if  the  calculation  results  are  below 60%  said  to  be  very efficient. Penelitian  ini bertujuan  untuk  mengetahui  dan  menganalisis pemeliharaan  mesin  yang  dilakukan oleh PT. SPO Agro Resources dan untuk mengetahui apakah dengan adanya kebijakan pemeliharaan pencegahan  dapat  meningkatkan  efektivitas  waktu  dan  biaya. Penelitian  ini menggunakan metode kualitatif dengan menjabarkan aktivitas kegiatan pemeliharaan yang dilaksanakan oleh PT. SPO Agro Resources, serta  menggunakan  metode  kuantitatif  berupa  statistik matematik  sebagai  alat  untuk membantu  memutuskan  kebijakan yang  akan  diambil  pada jangka  waktu  tertentu  dan pengukuran efisiensi  menggunakan deskriptif  presentase.  Hasil  penelitian menunjukkan  biaya pemeliharaan pencegahan sebulan sekali Rp.138.012.968,- nilai efisiensinya 39,63%,  biaya pemeliharaan pencegahan  dua  bulan  sekali  Rp.196.689.315,- nilai  efisiensinya 56,48%,  biaya pemeliharaan pencegahan  tiga  bulan  sekali Rp.258.731.341,- nilai  efisiensinya 74,29%, biaya pemeliharaan perbaikan Rp.247.164.000,- nilai  efisiensinya 70,97%.  Berdasarkan perhitungan diketahui bahwa kebijakan yang mengefisiensikan  biaya pemeliharaan  yaitu pemeliharaan  sebulan  sekali karena kebijakan ini biaya  pemeliharaannya paling  kecil  dibandingkan  dengan  kebijakan yang  lain, dimana nilai  persentasenya  lebih  kecil  yaitu  39,63%, sesuai  dengan tabel  2 yang  menyatakan  apabila  hasil perhitungan di bawah 60% maka dikatakan sangat efisien.

scholarly journals Recent Trends in Maintenance Costs for Façades Due to Air Pollution in the Oslo Quadrature, Norway

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 529 ◽  
Author(s):  
Grøntoft
Keyword(s):  
Air Pollution ◽  
Maintenance Cost ◽  
Response Functions ◽  
Maintenance Costs ◽  
Building Maintenance ◽  
Exposure Response ◽  
Local Air Pollution ◽  
Recent Trends ◽  
Steel Surfaces ◽  
The Cost

This study assesses changes since 1980 in the maintenance cost of the façades of the historical 17th to 19th century buildings of the Oslo Quadrature, Norway, due to atmospheric chemical wear, including the influence of air pollution. Bottom up estimations by exposure–response functions for an SO2 dominated situation reported in the literature for 1979 and 1995 were compared with calculations for the present (2002–2014) multi-pollutant situation. The present maintenance cost, relative to the total façade area, due to atmospheric wear and soiling was found to be about 1.6 Euro/m2 per year. The exposure to local air pollution, mainly particulate matter and NOx gases, contributed to 0.6 Euro/m2 (38%), of which the cost due to wear of renderings was about 0.4 Euro/m2 (22%), that due to the cleaning of glass was 0.2 Euro/m2 (11%), and that due to wear of other façade materials was 0.07 Euro/m2 (5%). The maintenance cost due to the atmospheric wear was found to be about 3.5%, and that due to the local air pollution about 1.1% of the total municipal building maintenance costs. The present (2002–2014) maintenance costs, relative to the areas of the specific materials, due to atmospheric wear are probably the highest for painted steel surfaces, about 8–10 Euro/m2, then about 2 Euro/m2 for façade cleaning and the maintenance of rendering, and down to 0.3 Euro/m2 for the maintenance of copper roofs. These costs should be adjusted with the importance of the wear relative to other reasons for the façade maintenance.

IMPLEMENTASI JOB ORDER COSTING METHOD DALAM PERHITUNGAN HARGA POKOK PRODUKSI MAP

2018 ◽  
Vol 4 (2) ◽  
pp. 43-55
Author(s):  
Ika Yulianti ◽  
Endah Masrunik ◽  
Anam Miftakhul Huda ◽  
Diana Elvianita
Keyword(s):  
Production Process ◽  
Quantitative Data ◽  
Production Cost ◽  
Qualitative Data ◽  
Cost Data ◽  
Method Calculation ◽  
Cost Of Production ◽  
The Right ◽  
The Cost

This study aims to find a comparison of the calculation of the cost of goods manufactured in the CV. Mitra Setia Blitar uses the company's method and uses the Job Order Costing (JOC) method. The method used in this study is quantitative. The types of data used are quantitative and qualitative. Quantitative data is in the form of map production cost data while qualitative data is in the form of information about map production process. The result of calculating the cost of production of the map between the two methods results in a difference of Rp. 306. Calculation using the company method is more expensive than using the Job Order Costing method. Calculation of cost of goods manufactured using the company method is Rp. 2,205,000, - or Rp. 2,205, - each unit. While using the Job Order Costing (JOC) method is Rp. 1,899,000, - or Rp 1,899, - each unit. So that the right method used in calculating the cost of production is the Job Order Costing (JOC) method

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