Maintenance optimization for marine mechanical systems

2019 ◽  
Vol 234 (2) ◽  
pp. 446-462
Author(s):  
David Kimera ◽  
Fillemon Nduvu Nangolo
Keyword(s):  
Mechanical System ◽  
Expert Knowledge ◽  
Mechanical Systems ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Maintenance Costs ◽  
Cost Rate ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy ◽  
Marine Vehicle

This article proposes a stochastic technique for determining the optimal maintenance policy for marine mechanical systems. The optimal maintenance policy output includes the average maintenance cost rate, maintenance interval and the performance thresholds for the three marine mechanical system classifications. The purpose of this study is to optimize maintenance, maintenance interval and performance thresholds based on maintenance and reliability data of the marine mechanical systems. Performance threshold and maintenance interval are used as the decision variables to determine the optimal maintenance policy. A stochastic model based on probability analysis is developed to trigger the maintenance action for mechanical systems. The model is later coded in MATLAB. Maintenance and failure data for a marine vehicle were statistically fitted using ReliaSoft, from which a three-parameter Weibull distribution best fitted all the mechanical system classifications. Model inputs were based on both the maintenance data and expert knowledge of the maintenance crew. Based on a 20-year marine vehicle life span, the optimal maintenance costs for plant and machinery are relatively the same. The model predicted annual total maintenance cost of US$183,029.24 is 11.11% more than the maintenance cost derived from experts’ threshold of US$164,726. Marine vehicle machinery presents a higher maintenance interval of 3.23 years compared to 2.92 years for marine vehicle plants. It was observed that for the performance thresholds greater than 84.54%, there is an insignificant difference between the plant and machinery maintenance costs. Sensitivity analysis results suggest there is little justification that changing maintenance costs will have an impact on the performance threshold [Formula: see text] and maintenance interval [Formula: see text]. A maintenance interval of 3 years results in a lower total annual maintenance cost deviation of 2.66% from the optimal total annual maintenance cost.

scholarly journals Evaluasi Manajemen Perawatan dengan Metode Reliability Centered Maintenance (RCM) II pada Mesin Cane Cutter 1 dan 2 di Stasiun Gilingan PG Meritjan - Kediri

Rekayasa ◽  
2017 ◽  
Vol 10 (2) ◽  
pp. 99
Author(s):  
Cahyo Purnomo Prasetyo
Keyword(s):  
Maintenance Cost ◽  
Repair Cost ◽  
Maintenance Policy ◽  
Work Safety ◽  
Maintenance Costs ◽  
Reliability Centered Maintenance ◽  
Optimal Maintenance ◽  
Critical Components ◽  
Optimal Maintenance Policy ◽  
Production Target

<p>Penelitian ini bertujuan untuk menentukan kebijakan perawatan optimal yang dapat mengurangi biaya perbaikan (repair cost) dan biaya konsekwensi operasional (operational consequence cost). Metode yang diterapkan pada penelitian ini adalah Reliability Centered Maintenance (RCM) II. Penelitian ini difokuskan pada mesin Cane Cutter 1 dan 2 dengan pertimbangan beberapa aspek yaitu : pengaruh kegagalan terhadap pencapaian target produksi, resiko keselamatan kerja dan biaya perawatan yang akan ditimbulkan. Dari hasil penelitian dapat diketahui bahwa komponen kritis pada mesin Cane Cutter 1 dan 2 adalah : Pisau dan Baut Pisau. Perawatan yang dilakukan untuk mengantisipasi dan mengatasi kegagalan yang terjadi pada komponen mesin tersebut adalah proactive task yang meliputi : scheduled restoration task dan scheduled discard task. Rata-rata penurunan biaya perawatan total yang didapatkan dengan mengurangkan ‘biaya total pada interval perawatan awal’ dan ‘biaya total pada interval perawatan optimal’ adalah 14,82 %.</p><p>Kata Kunci: cane cutter, downtime, pabrik gula.</p><p><strong> </strong></p><p><strong>ABSTRACT</strong></p><p><em>This research aims to determine the optimal maintenance policy which could reduce repair cost and operational consequence cost. The methods which applied in this research is Reliability Centered Maintenance (RCM) II. This research focuses on Cane Cutter 1 and 2 machines by considering several aspects, such as and effect of any failure on production target achievement, work safety risk and maintenance cost which might be caused by the critical condition. The result showed that some critical components at the Cane Cutter 1 and 2 machines were : Blade and Blade Bolt. The maintenance which could be done to anticipate and deal with any failure occurring in the machine components was called proactive task comprising : scheduled restoration task and scheduled discard task. The average reduction in total maintenance costs which was obtained by subtracting ‘total costs at initial maintenance interval’ and ‘total costs at optimal maintenance interval’ amounted to 14,82 %.</em></p><p><em>Keywords: cane cutter, downtime, sugar factory</em></p>

scholarly journals Optimal Maintenance Policy for Offshore Wind Systems

Energies ◽  
2021 ◽  
Vol 14 (19) ◽  
pp. 6082
Author(s):  
Vincent F. Yu ◽  
Thi Huynh Anh Le ◽  
Tai-Sheng Su ◽  
Shih-Wei Lin
Keyword(s):  
Electricity Market ◽  
System Reliability ◽  
Market Price ◽  
Offshore Wind ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Maintenance Costs ◽  
Multi Objective Programming ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Employing maintenance threshold plays a critical step in determining an optimal maintenance policy for an offshore wind system to reduce maintenance costs while increasing system reliability. Considering the limited works on this topic, we propose a two-stage procedure to determine the optimal maintenance thresholds for multiple components of an offshore wind power system in order to minimize maintenance costs while achieving the highest possible system reliability. First, using genetic algorithms, a dynamic strategy is developed to determine the maintenance thresholds of individual components where the cost of maintenance and the rate of failure are critical. Then, fuzzy multi-objective programming is applied to find the system’s optimal maintenance threshold considering all components. A variety of factors including weather conditions, system reliability, power generation losses, and electricity market price are carefully considered to enhance the system’s reliability and reduce the costs of maintenance. When maintenance threshold results are compared, component-wise versus system-wise, an average system savings of 1.19% for maintenance cost is obtained while the system reliability is increased by 1.62% on average.

Availability analysis and maintenance optimization for multiple failure mode systems considering imperfect repair

2021 ◽  
pp. 1748006X2110127
Author(s):  
Qingan Qiu ◽  
Baoliang Liu ◽  
Cong Lin ◽  
Jingjing Wang
Keyword(s):  
Failure Modes ◽  
Maintenance Cost ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Availability Analysis ◽  
Long Run ◽  
Optimal Maintenance ◽  
Maintenance Policies ◽  
Periodic Inspections

This paper studies the availability and optimal maintenance policies for systems subject to competing failure modes under continuous and periodic inspections. The repair time distribution and maintenance cost are both dependent on the failure modes. We investigate the instantaneous availability and the steady state availability of the system maintained through several imperfect repairs before a replacement is allowed. Analytical expressions for system availability under continuous and periodic inspections are derived respectively. The availability models are then utilized to obtain the optimal inspection and imperfect maintenance policy that minimizes the average long-run cost rate. A numerical example for Remote Power Feeding System is presented to demonstrate the application of the developed approach.

Sequential imperfect preventive maintenance policy with random maintenance quality under reliability limit

2011 ◽  
Vol 225 (8) ◽  
pp. 1926-1935 ◽  
Author(s):  
Z Wang ◽  
J Yang ◽  
G Wang ◽  
G Zhang
Keyword(s):  
Failure Rate ◽  
Preventive Maintenance ◽  
Average Cost ◽  
Numerical Control ◽  
Maintenance Policy ◽  
Cost Rate ◽  
Proposed Model ◽  
Optimal Maintenance ◽  
Average Cost Rate ◽  
Optimal Maintenance Policy

To determine the optimal maintenance number for a system with random maintenance quality in infinite time horizon, a sequential imperfect preventive maintenance model considering reliability limit is proposed. The proposed model is derived from the combination of the Kijima type virtual age model and the failure rate adjustment model. Maintenance intervals of the proposed model are obtained through an iteration method when both failure rate increase factor and maintenance restoration factor are random variables with a uniform distribution. The optimal maintenance policy is presented by minimizing the long-run average cost rate. A real numerical example for the failures of numerical control equipment is given to demonstrate the proposed model. Finally, a discussion is presented to show how the optimal average cost rate depends on the different cost parameters. The results show that in order to satisfy the practical requirements of high reliability, it is necessary and worthwhile to consider the system's reliability limit in preventive maintenance practice.

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 Optimizing Maintenance Planning in the Production Industry Using the Markovian Approach

2012 ◽  
Vol 9 (2) ◽  
pp. 46
Author(s):  
B Kareem ◽  
HA Owolabi
Keyword(s):  
Cost Minimization ◽  
Production Equipment ◽  
Maintenance Cost ◽  
Maintenance Planning ◽  
Maintenance Policy ◽  
Transition Matrices ◽  
Operational Life ◽  
Optimal Maintenance ◽  
Markovian Approach ◽  
Optimal Maintenance Policy

Maintenance is an essential activity in every manufacturing establishment, as manufacturing effectiveness counts on the functionality of production equipment and machinery in terms of their productivity and operational life. Maintenance cost minimization can be achieved by adopting an appropriate maintenance planning policy. This paper applies the Markovian approach to maintenance planning decision, thereby generating optimal maintenance policy from the identified alternatives over a specified period of time. Markov chains, transition matrices, decision processes, and dynamic programming models were formulated for the decision problem related to maintenance operations of a cable production company. Preventive and corrective maintenance data based on workloads and costs, were collected from the company and utilized in this study. The result showed variability in the choice of optimal maintenance policy that was adopted in the case study. Post optimality analysis of the process buttressed the claim. The proposed approach is promising for solving the maintenance scheduling decision problems of the company. 

Comparative Analysis of Existing and Optimal Maintenance Policy of Water Borehole Schemes in South Eastern States of Nigeria

2021 ◽  
Vol 18 (1) ◽  
pp. 43-50
Author(s):  
M.C. Nwachukwu ◽  
J.C. Agunwamba ◽  
B.C. Okoro ◽  
C.N. Mama
Keyword(s):  
Comparative Analysis ◽  
Preventive Maintenance ◽  
Current Practice ◽  
Maintenance Cost ◽  
Operational Cost ◽  
Submersible Pump ◽  
Maintenance Policy ◽  
South Eastern ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

A study optimising maintenance cost of water borehole schemes in South Eastern states of Nigeria (Abia, Anambra, Ebonyi, Enugu and Imo States) was carried out. Data was collected from 260 boreholes spread across all local government areas in the states. Optimisation results showed that for boreholes (submersible pumps) pumping once per day, the optimal preventive maintenance frequency and resulting savings in cost are 2 and ₦521,076 for Abia; 2 and ₦783,963 for Anambra; 2 and ₦458,242 for Ebonyi; 2 and ₦740,964 for Enugu; 2 and ₦605,187 Imo. For boreholes pumping twice per day, the optimal preventive maintenance frequency and resulting savings in cost are 5 and ₦1,896,301 for Abia; 4 and ₦3,692,655 for Anambra; 5 and ₦786,913 for Ebonyi; 4 and ₦4,187,161 for Enugu; 4 and ₦2,477,609 for Imo; and for boreholes pumping thrice per day; 8 and ₦2,798,330 for Abia; 7 and ₦8,372,862 for Anambra; 7 and ₦6,485,293 for Ebonyi; 10 and ₦4,014,240 for Enugu; 10 and ₦6,021,503 for Imo; with no downtime as opposed to the wasteful current practice of no preventive maintenance with downtime of up to 12 months or more. As a recommendation for a borehole scheme, there should be a check on the type of submersible pump and generator capacity as the choice made directly affects the total operational cost.

Maintenance Decision-Making Under the Cost Criterion and the Competing Risks Approach

2017 ◽  
Vol 9 (1) ◽  
pp. 32-48 ◽  
Author(s):  
Rima Oudjedi Damerdji ◽  
Myriam Noureddine
Keyword(s):  
Decision Making ◽  
Competing Risks ◽  
Preventive Maintenance ◽  
Optimal Operation ◽  
Maintenance Cost ◽  
Delay Model ◽  
Maintenance Policy ◽  
Optimal Maintenance ◽  
Maintenance Decision ◽  
Optimal Maintenance Policy

The definition of an appropriated maintenance policy appears essential to avoid the system failures and ensure its optimal operation, while taking into account the criteria of availability and costs. This article deals with a maintenance decision-making for a system subject to two competing maintenance actions, corrective and preventive maintenance. To define this situation of dependent competing risks, the Alert Delay model seems well suited because it involves the notion of a delivered alert before system failure in order to perform preventive maintenance. This paper proposes an approach including both an extension of the Alert Delay model where the considered system follows an exponential distribution, and the total maintenance cost assessment of the system. These two concepts provide an aid decision-making to select the optimal maintenance policy based on the minimal cost. The proposed approach is validated in a computer system localized in a real industrial enterprise.

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