scholarly journals Optimal Cost-Effective Maintenance Policy for a Helicopter Gearbox Early Fault Detection under Varying Load

2017 ◽  
Vol 2017 ◽  
pp. 1-16
Author(s):  
Xin Li ◽  
Jing Cai ◽  
Hongfu Zuo ◽  
Huaiyuan Li
Keyword(s):  
Fault Detection ◽  
Markov Model ◽  
Remaining Useful Life ◽  
Replacement Policy ◽  
Detection Methods ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Bayesian Control ◽  
Early Fault Detection ◽  
Optimal Maintenance Policy

Most of the existing fault detection methods rarely consider the cost-optimal maintenance policy. A novel multivariate Bayesian control approach is proposed, which enables the implementation of early fault detection for a helicopter gearbox with cost minimization maintenance policy under varying load. A continuous time hidden semi-Markov model (HSMM) is employed to describe the stochastic relationship between the unobservable states and observable observations of the gear system. Explicit expressions for the remaining useful life prediction are derived using HSMM. Considering the maintenance cost in fault detection, the multivariate Bayesian control scheme based on HSMM is developed; the objective is to minimize the long-run expected average cost per unit time. An effective computational algorithm in the semi-Markov decision process (SMDP) framework is designed to obtain the optimal control limit. A comparison with the multivariate Bayesian control chart based on hidden Markov model (HMM) and the traditional age-based replacement policy is given, which illustrates the effectiveness of the proposed approach.

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 NARX NETWORK BASED DATA-DRIVEN ALGORITHM FOR DETECTION OF TRAY FAULTS IN NONLINEAR DYNAMIC DISTILLATION COLUMN

2020 ◽  
Vol 82 (5) ◽  
Author(s):  
Syed Ali Ammar Taqvi ◽  
Haslinda Zabiri ◽  
Lemma Dendena Tufa ◽  
Fahim Uddin ◽  
Syeda Anmol Fatima ◽  
...  
Keyword(s):  
Fault Detection ◽  
Process Monitoring ◽  
Nonlinear Dynamic ◽  
Distillation Column ◽  
Fault Detection And Diagnosis ◽  
Data Driven ◽  
Detection Methods ◽  
Maintenance Cost ◽  
Monitoring And Control ◽  
Process Industries

Efficient monitoring of highly complex process industries is essential for better management, safer operations and high-quality production. Timely detection of various faults helps to improve the performance of the complex industries, prevent various unfavorable consequences and reduce the maintenance cost. Fault Detection and Diagnosis (FDD) for process monitoring and control has been an active field of research for the past two decades. Distillation columns are inherently nonlinear, and thus to have an accurate and robust performance, the fault detection methods should be based on nonlinear dynamic methods. The paper presents a robust data-driven fault detection approach for realistic tray upsets in the distillation column. The detection of tray faults in the distillation column is conducted by Nonlinear AutoRegressive with eXogenous Input (NARX) network with Tapped Delay Lines (TDL). Aspen Plus® Dynamic simulation has been used to generate normal and faulty datasets. The study shows that the proposed method can be used for the detection of tray faults in distillation column for dynamic process monitoring. The performance of the proposed method has been evaluated by the Missed Detection Rate (MDR) and the Detection Delay (DD).

scholarly journals Early Fault Detection by Vibration Measurement

2021 ◽  
Vol 10 (5) ◽  
pp. 358-365
Author(s):  
D. H. Omar ◽  
M. H. Belal ◽  
F. R. Gomaa
Keyword(s):  
Fault Detection ◽  
Experimental Studies ◽  
Vibration Monitoring ◽  
Vibration Measurement ◽  
Maintenance Cost ◽  
Rotating Machine ◽  
Analysis Technique ◽  
Measurement Devices ◽  
Early Fault Detection ◽  
Monitoring Devices

Early fault detection by using vibration monitoring devices could help industries to avoid sudden stoppage of the machine, thus reduces machine downtime and maintenance cost to save time and money. Early fault detection by using vibration measurement devices are very useful for determining the condition of rotating elements and its analysis. In this paper, experimental studies were performed to predict misalignment faults in rotating machine which is connected with simple rigid coupling. The vibration is collected by using Micro log data collector. From results, we can easily predict misalignment in rotating machine using spectrum analysis technique.

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 A Maintenance Cost Study of Transformers Based on Markov Model Utilizing Frequency of Transition Approach

Energies ◽  
2018 ◽  
Vol 11 (8) ◽  
pp. 2006 ◽  
Author(s):  
Muhammad Yahaya ◽  
Norhafiz Azis ◽  
Amran Mohd Selva ◽  
Mohd Ab Kadir ◽  
Jasronita Jasni ◽  
...  
Keyword(s):  
Markov Model ◽  
Transition Probabilities ◽  
Prediction Interval ◽  
Transition States ◽  
Maintenance Cost ◽  
Maintenance Policy ◽  
Cost Study ◽  
Policy Model ◽  
Transition Approach ◽  
Year 2013

In this paper, a maintenance cost study of transformers based on the Markov Model (MM) utilizing the Health Index (HI) is presented. In total, 120 distribution transformers of oil type (33/11 kV and 30 MVA) are examined. The HI is computed based on condition assessment data. Based on the HI, the transformers are arranged according to its corresponding states, and the transition probabilities are determined based on frequency of a transition approach utilizing the transformer transition states for the year 2013/2014 and 2012/2013. The future states of transformers are determined based on the MM chain algorithm. Finally, the maintenance costs are estimated based on future-state distribution probabilities according to the proposed maintenance policy model. The study shows that the deterioration states of the transformer population for the year 2015 can be predicted by MM based on the transformer transition states for the year 2013/2014 and 2012/2013. Analysis on the relationship between the predicted and actual computed numbers of transformers reveals that all transformer states are still within the 95% prediction interval. There is a 90% probability that the transformer population will reach State 1 after 76 years and 69 years based on the transformer transition states for the year 2013/2014 and 2012/2013. Based on the probability-state distributions, it is found that the total maintenance cost increases gradually from Ringgit Malaysia (RM) 5.94 million to RM 39.09 million based on transformer transition states for the year 2013/2014 and RM 37.56 million for the year 2012/2013 within the 20 years prediction interval, respectively.

Opportunistic maintenance (OM) as a new advancement in maintenance approaches

2014 ◽  
Vol 20 (2) ◽  
pp. 98-121 ◽  
Author(s):  
Hasnida Ab-Samat ◽  
Shahrul Kamaruddin
Keyword(s):  
Current Trend ◽  
Replacement Policy ◽  
Practical Significance ◽  
Clear Understanding ◽  
Maintenance Policy ◽  
Opportunistic Maintenance ◽  
Content Type ◽  
Research Areas ◽  
Optimal Maintenance ◽  
Optimal Maintenance Policy

Purpose – This paper reviews the literature on opportunistic maintenance (OM) as new advance maintenance approach and policy. The purpose of this paper is to conceptually identify common principle and thereby provide absolute definition, concept and characteristics of this policy. Design/methodology/approach – A conceptual analysis was conducted on various literatures to clarify a number of principle and concepts as a method for understanding information on OM. The analysis involves the process of separating the compound terms used in the literatures into a few parts, analyse them and then recombining them to have more clear understanding of the policy. Findings – The paper discussed the maintenance approach, genealogy, principle, concept and applications of OM both in numerical analysis and real industry. OM policy is developed based on combination of age replacement policy and block replacement policy and in practical; OM is applied as the combination of corrective maintenance which is applied when any failure occurred, with preventive maintenance (PM) – a planned and scheduled maintenance approach to prevent failure to happen. Any machine shutdown or stoppages due to failure is the “opportunity” to conduct PM even though it is not as planned. The characterization of OM was provided in order to present its theoretical novelty for researchers and practical significance for industries. Practical implications – To date, there is no publication that reviews the OM in-depth and provides clear understanding on the topic. Therefore, this paper aims to show lineage of OM and the current trend in researches. This discussion will pave the way of new research areas on this optimal maintenance policy. Clear definition and principle of OM provided in this paper will trigger interest in its practicality as well as aid industries to understand and conduct OM in operation plant. Originality/value – This paper discussed the available literature about OM in various perspectives and scopes for further understanding of the topic by maintenance management professionals and researchers. Therefore, OM can be widely studied and applied in real industry as it is an effective and optimal maintenance policy.

Prognostics and Health Monitoring of Electro-Hydraulic Systems

2017 ◽  
Author(s):  
Damoon Soudbakhsh ◽  
Anuradha M. Annaswamy
Keyword(s):  
Fault Detection ◽  
Health Monitoring ◽  
Industrial Applications ◽  
Remaining Useful Life ◽  
Maintenance Cost ◽  
Hydraulic Systems ◽  
Multiple Sources ◽  
Redundant Actuators ◽  
Component Failures ◽  
Prognostics And Health Monitoring

Electro-Hydraulic Systems (EHS) are commonly used in many industrial applications. Prediction and timely fault detection of EHS can significantly reduce their maintenance cost, and eliminate the need for redundant actuators. Current practice to detect faults in the actuators can miss failures with combination of multiple sources. Missed faults can result in sudden, unforeseen failures. We propose a fault detection technique based on Multiple Regressor Adaptive Observers (MRAO). The results were evaluated using a two-stage servo-valve model. The proposed MRAO can be used for on-line fault detection. Therefore, we propose a health monitoring approach based on the trend of the identified parameters of the system. Using the history of identified parameters, normal tear and wear of the actuator can be distinguished from the component failures to more accurately estimate the remaining useful life of the actuator.

scholarly journals A study on an optimal replacement policy for a deteriorating system under partial product process

10.26524/cm65 ◽  
2020 ◽  
Vol 4 (1) ◽  
Author(s):  
Govindaraju P ◽  
Rajendiran R
Keyword(s):  
Explicit Expression ◽  
Average Cost ◽  
Replacement Policy ◽  
Partial Product ◽  
Maintenance Policy ◽  
Optimal Replacement ◽  
Optimal Replacement Policy ◽  
Optimal Maintenance ◽  
Random Shocks ◽  
Optimal Maintenance Policy

In this paper, we consider an optimal maintenance policy for a reparable deteriorating system subject to random shocks. For a reparable deteriorating system, the repair time by a partial product process and the failure mechanism by a generalized δshock process. Develop an explicit expression of the ling run average cost per unit time under N policy is studied.

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.

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