scholarly journals ANALISIS PEMELIHARAAN MESIN PRODUKSI PADA PT. HAYCARB PALU MITRA

2020 ◽  
Vol 5 (1) ◽  
pp. 61-68
Author(s):  
Nandhika Dwi Putra ◽  
Husein Hi Moh Saleh ◽  
Asngadi Asngadi
Keyword(s):  
Technical Efficiency ◽  
Preventive Maintenance ◽  
Quantitative Methods ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Machine Maintenance ◽  
Time Period ◽  
Preventive Maintenance Policy

 This study aims to determine and analyze the maintenance of production machinery conducted PT. Haycarb Palu Partners and find out whether the policies carried out are efficient. To achieve these objectives, using statistical and mathematical quantitative methods as a tool to help decide the maintenance policy to be taken at a certain time period. The results showed that, using preventive maintenance policy on bucket elevators and rotary screnes, the lowest preventive maintenance cost (minimum) for the bucket elevators machine occurred in the 10th month of Rp.2.994. 200, -, and for the rotary screnes machine the lowest preventive maintenance cost (minimum) at month 9 is Rp.1.398.080.-. Measurement of technical efficiency, maintenance cost policy for bucket elevators machine at month six that is equal to Rp.3.675.500, -, and for maintenance cost during the year is Rp.7.351.000, -. As for rotary screnes machine maintenance cost in the sixth month that is Rp.1.589.387 and for maintenance cost for a year of Rp.3.178.774, -, then PT. Haycarb Palu Partners can implement preventive maintenance that can save costs. Penelitian ini bertujuan untuk mengetahui dan menganalisis pemeliharaan mesin produksi yang dilakukan PT. Haycarb Palu Mitra serta mengetahui apakah kebijakan yang dilakukan sudah efisien. Agar mencapai tujuan tersebut, dengan menggunakan metode kuantitatif statistik dan matematik sebagai alat untuk membantu memutuskan kebijakan pemeliharaan yang akan diambil pada suatu jangka waktu tertentu. Hasil penelitian menunjukkan bahwa, dengan menggunakan metode kebijakan pemeliharaan preventif (preventive maintenance) pada mesin bucket elevators dan mesin screnes rotary, menghasilkan biaya pemeliharaan preventif yang paling rendah (minimum) untuk mesin bucket elevators terjadi pada bulan ke-10 yaitu sebesar Rp.2.994.200,- , dan untuk mesin screnes rotary biaya pemeliharaan preventifnya yang paling rendah (minimum) pada bulan ke-9 yaitu sebesar Rp.1.398.080.-. Pengukuran efisiensi secara teknis, kebijakan biaya pemeliharaan untuk mesin bucket elevators pada bulan ke enam yaitu sebesar Rp.3.675.500,-, dan untuk biaya pemeliharaan selama setahunnya adalah Rp.7.351.000,-. Sedangkan untuk mesin screnes rotary biaya pemeliharaan pada bulan ke enam yaitu sebesar Rp.1.589.387 dan untuk biaya pemeliharaan selama setahunnya sebesar Rp.3.178.774,-, Maka PT. Haycarb Palu Mitra dapat menerapkan pemeliharaan preventif yang dapat mengemat biaya.

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 ON PREVENTIVE MAINTENANCE POLICY FOR WAVE DISSIPATING BLOCKS COVERING CAISSON BREAKWATER

2018 ◽  
pp. 72
Author(s):  
Takao Ota ◽  
Hiroyuki Kawamura ◽  
Yoshiharu Matsumi ◽  
Junji Koyanagi ◽  
Takashi Satow
Keyword(s):  
Mathematical Model ◽  
Preventive Maintenance ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Reliability Engineering ◽  
Coastal Structures ◽  
Service Period ◽  
Caisson Breakwater ◽  
External Forces ◽  
Preventive Maintenance Policy

The infrastructures are required to keep a certain level of performance during the duration of service. Because the performance of the infrastructures including harbor and coastal structures deteriorates due to aging and damage that is caused by the action of external forces, it is necessary to perform appropriate maintenance. Satow et al. (2009) proposed a mathematical model for the preventive maintenance of wave dissipating blocks based on the method of the reliability engineering. They also derived the expected maintenance cost over the in service period and the optimal preventive maintenance policy. In this study, the optimal threshold for preventive maintenance to minimize the expected maintenance cost is determined for the wave dissipating blocks covering caisson breakwater by using the above model.

Optimal Preventive Maintenance Policy Under a Budget Constraint

2008 ◽  
Author(s):  
Inderjeet Singh ◽  
Elmira Popova ◽  
Ernie Kee
Keyword(s):  
Preventive Maintenance ◽  
Real Data ◽  
Integer Program ◽  
South Texas ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Data Set ◽  
Finite Time Horizon ◽  
Preventive Maintenance Policy ◽  
Operating Company

We design an optimal preventive maintenance policy for a system of N items that minimizes the total expected maintenance cost. We assume that the budget for preventive maintenance is limited and constrained. The problem has a finite time horizon and we consider constant inter-preventive maintenance times for every item. The resulting nonlinear optimization problem is reformulated as a binary integer program and computation results are presented on a real data set from South Texas Project Nuclear Operating Company in Bay City, Texas, USA.

scholarly journals Optimizing preventive maintenance policy: A data-driven application for a light rail braking system

2017 ◽  
Vol 231 (5) ◽  
pp. 534-545 ◽  
Author(s):  
Francesco Corman ◽  
Sander Kraijema ◽  
Milinko Godjevac ◽  
Gabriel Lodewijks
Keyword(s):  
Preventive Maintenance ◽  
Data Driven ◽  
Sequential Optimization ◽  
Maintenance Cost ◽  
Light Rail ◽  
Maintenance Policy ◽  
Maintenance Costs ◽  
Braking System ◽  
Optimal Maintenance Policy ◽  
Preventive Maintenance Policy

This article presents a case study determining the optimal preventive maintenance policy for a light rail rolling stock system in terms of reliability, availability, and maintenance costs. The maintenance policy defines one of the three predefined preventive maintenance actions at fixed time-based intervals for each of the subsystems of the braking system. Based on work, maintenance, and failure data, we model the reliability degradation of the system and its subsystems under the current maintenance policy by a Weibull distribution. We then analytically determine the relation between reliability, availability, and maintenance costs. We validate the model against recorded reliability and availability and get further insights by a dedicated sensitivity analysis. The model is then used in a sequential optimization framework determining preventive maintenance intervals to improve on the key performance indicators. We show the potential of data-driven modelling to determine optimal maintenance policy: same system availability and reliability can be achieved with 30% maintenance cost reduction, by prolonging the intervals and re-grouping maintenance actions.

scholarly journals Vulnerability based management of water resources systems

2004 ◽  
Vol 6 (2) ◽  
pp. 133-156 ◽  
Author(s):  
V. K. Kanakoudis
Keyword(s):  
Water Supply ◽  
Preventive Maintenance ◽  
Water System ◽  
Supply System ◽  
Water Supply System ◽  
Maintenance Policy ◽  
Supply Networks ◽  
Water Resources Systems ◽  
Maintenance Schedule ◽  
Preventive Maintenance Policy

Must the water networks be fail-proof or must they remain safe during a failure? What must water system managers try to achieve? The present paper introduces a methodology for the hierarchical analysis (in time and space) of the preventive maintenance policy of water supply networks, using water supply system performance indices. This is being accomplished through a technical–economic analysis that takes into account all kinds of costs referring to the repair or replacement of trouble-causing parts of the water supply network. The optimal preventive maintenance schedule suggested by the methodology is compared with the empirically based maintenance policy applied to the Athens water supply system.

scholarly journals Preventive maintenance policy on leasing by considering the usage rate

2018 ◽  
Vol 204 ◽  
pp. 02016
Author(s):  
Moh. Jufriyanto ◽  
Nani Kurniati ◽  
Ade Supriatna
Keyword(s):  
Preventive Maintenance ◽  
Failure Time ◽  
Equipment Failure ◽  
Maintenance Policy ◽  
Time Duration ◽  
Maintenance Costs ◽  
Operational Conditions ◽  
Penalty Cost ◽  
Usage Rate ◽  
Preventive Maintenance Policy

The needs of the consumers about the functionality of a product and increase maintenance costs of equipment caused the prices of products and treatments to be expensive. Therefore, the company considers the lease rather than buy it. Leasing provides interesting strategy when dealing with expensive equipment. Policy maintenance that is done to the product that has decreased performance. Minimum repair done to fix failed equipment in order to return to operational condition, while imperfect preventive maintenance to improve the operational conditions of the equipment to avoid failure. Time duration for a minimum repair neglected. The lessor will charge a penalty (penalty cost) if the lease equipment failure. Mathematical model built for the minimization cost of maintenance policy. In the final part, the numerical experiment are given to show the maintenance policy taking into account the rate of usage (usage rate) by knowing the minimization the resulting costs.

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