Analysis of Spare Parts Demand Forecasting Considering Preventive Maintenance

2013 ◽  
Vol 401-403 ◽  
pp. 2199-2204 ◽  
Author(s):  
Hao Liu ◽  
Jian Min Zhao ◽  
Jin Song Zhao ◽  
Hong Zhi Teng
Keyword(s):  
Weibull Distribution ◽  
Preventive Maintenance ◽  
Empirical Formula ◽  
Demand Forecasting ◽  
Spare Parts ◽  
Replacement Policy ◽  
Maintenance Policy ◽  
Reliability Engineering ◽  
Demand Rate ◽  
Age Replacement

Considering the importance of PM (preventive maintenance) in reliability engineering, the formula is given to calculate spare demand rate for the policies of age replacement policy, minimal maintenance policy and block replacement policy. And average spare demand rate was analyzed for age replacement policy, and an approximate empirical formula with PM interval and parameters of Weibull distribution was given compared to CM(corrective maintenance) and PM. Otherwise, compared to minimal maintenance policy and block replacement policy, the demand rate was analyzed in order to better forecast the spare parts demand.

Stochastic Models in Preventive Maintenance Policies

2014 ◽  
Vol 1016 ◽  
pp. 802-806
Author(s):  
Onur Gölbaşı ◽  
Nuray Demirel
Keyword(s):  
Poisson Process ◽  
Stochastic Models ◽  
Preventive Maintenance ◽  
Operating Cost ◽  
Replacement Policy ◽  
Market Demand ◽  
Imperfect Maintenance ◽  
Maintenance Policy ◽  
Maintenance Policies ◽  
Age Replacement

In recent decades, philosophy behind maintenance has varied consistently due to the changes in complexity of designs, advances in automation and mechanization, adaptation to the fast growing market demand, commercial computation in the sectors, and environmental issues. In mid-forties, simplicity of designs, limited maintenance opportunities, and immaturity of trade culture made enough to performonly fix it when it brokeapproach, i.e. corrective maintenance, after failures. Last quarter of the 21thcentury made essential to constitute more conservative and preventive maintenance policies in order to ensure safety, reliability, and availability of systems with longer lifetime and cost effectiveness. Preventive maintenance can provide an economic saving more than 18% of operating cost of systems. In this basis, various stochastic models were proposed as a tool to constitute a maintenance policy to measure system availability and to obtain optimal maintenance periods. This paper presents a general perspective on common stochastic models in maintenance planning such as Homogenous Poisson Process, Non-Homogenous Poisson Process, and Imperfect Maintenance. The paper also introduces two common maintenance policies, block and age replacement policy, using these stochastic models.

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.

A hybrid preventive maintenance model for systems with partially observable degradation

2020 ◽  
Vol 31 (3) ◽  
pp. 345-365 ◽  
Author(s):  
Maxim Finkelstein ◽  
Ji Hwan Cha ◽  
Gregory Levitin
Keyword(s):  
Preventive Maintenance ◽  
Replacement Policy ◽  
Hybrid Strategy ◽  
Cost Rate ◽  
Shot Noise Process ◽  
Shock Process ◽  
Long Run ◽  
Age Replacement ◽  
Partially Observable ◽  
Maintenance Model

Abstract A new model of hybrid preventive maintenance of systems with partially observable degradation is developed. This model combines condition-based maintenance with age replacement maintenance in the proposed, specific way. A system, subject to a shock process, is replaced on failure or at some time ${T}_S$ if the number of shocks experienced by this time is greater than or equal to m or at time $T>{T}_S$ otherwise, whichever occurs first. Each shock increases the failure rate of the system at the random time of its occurrence, thus forming a corresponding shot-noise process. The real deterioration of the system is partially observed via observation of the shock process at time ${T}_S$. The corresponding optimization problem is solved and a detailed numerical example demonstrates that the long-run cost rate for the proposed optimal hybrid strategy is smaller than that for the standard optimal age replacement policy.

OPTIMAL RANDOM AGE REPLACEMENT FOR AVAILABILITY

2012 ◽  
Vol 19 (05) ◽  
pp. 1250021 ◽  
Author(s):  
JOHN E. ANGUS ◽  
MENG-LAI YIN ◽  
KISHOR TRIVEDI
Keyword(s):  
Preventive Maintenance ◽  
Sufficient Conditions ◽  
Optimal Rate ◽  
Maintenance Policy ◽  
Design Decisions ◽  
System Availability ◽  
Critical Design ◽  
Long Run ◽  
Age Replacement

An age replacement maintenance policy is considered here, in which a system is restored whenever it fails, or ages without failure up to a preventive maintenance epoch (whichever comes first). The duration of the restoration activity is random, and depends on whether it was precipitated by a failure or by a preventive maintenance action. The case where the preventive maintenance epoch is deterministic has been studied previously, and shown to be optimal in a certain sense. Here, we consider the case where the preventive maintenance epoch is randomized, which is more realistic for many systems. The system availability is the long run proportion of time that the system is operational (i.e., not undergoing repair or preventive maintenance). The optimal rate of preventive maintenance to maximize availability is considered, along with sufficient conditions for such an optimum to exist. The results obtained herein are useful to systems engineers in making critical design decisions.

scholarly journals Modeling Spare Parts Demands Forecast under Two-Dimensional Preventive Maintenance Policy

2015 ◽  
Vol 2015 ◽  
pp. 1-9 ◽  
Author(s):  
Qiwei Hu ◽  
Yongsheng Bai ◽  
Jianmin Zhao ◽  
Wenbin Cao
Keyword(s):  
Preventive Maintenance ◽  
Spare Parts ◽  
Two Dimensional ◽  
Maintenance Policy ◽  
Calendar Time ◽  
Maintenance Practice ◽  
Preventive Maintenance Policy ◽  
The Mathematical Model ◽  
Novel Model

In maintenance practice, there is such a situation where the spare parts replacement should be carried out at the scheduling time of calendar or usage for whichever comes first. The issue of two-dimensional preventive maintenance usually was not addressed by traditional methods, and at present, few studies were focused on this very topic. Based on these considerations, this paper presented the two-dimensional preventive policy where replacements of spare parts are based on both calendar time and usage time. A novel model was developed to forecast spare parts demands under two-dimensional preventive maintenance policy, and a discrete algorithm was presented for solving the mathematical model. A case study was given to demonstrate its applicability and validity, and it was showed that the presented model can be used to forecast spare parts demands as well as to optimize spare parts and preventive maintenance jointly.

Control Improvement of the Reactor Protection System

2011 ◽  
Vol 71-78 ◽  
pp. 4199-4202
Author(s):  
Bo Ya Zhao ◽  
Song Yang ◽  
Zhe Zhang ◽  
Ri Sheng Sun
Keyword(s):  
Preventive Maintenance ◽  
Protection System ◽  
Maintenance Policy ◽  
Block System ◽  
Replacement Model ◽  
Optimal Maintenance ◽  
Age Replacement ◽  
Reactor Protection System ◽  
Optimal Maintenance Policy ◽  
Random Failures

In this paper an optimal maintenance policy for a Reactor Protection System (RPS) for a nuclear plant was developed. RPS consists of continuously operating sub-systems that were subject to random failures. A block system diagram for RPS had been proposed that facilitates analyzing of individual sub-systems separately. The proposed maintenance policy is the Age Replacement model, which incorporated both corrective and preventive maintenances. A Markov model was used to optimize the preventive maintenance interval of those sub-systems whose failure and repair rates were exponentially distributed. Finally, a sensitivity analysis had been performed and recommendations for maintaining the required RPS availability have been suggested.

scholarly journals Research on Inventory Strategy of Spare Parts Based on Demand Rate

2021 ◽  
Vol 1910 (1) ◽  
pp. 012038
Author(s):  
Junbao Geng ◽  
Shuhuan Wei ◽  
Zhangjian Wei
Keyword(s):  
Spare Parts ◽  
On Demand ◽  
Demand Rate ◽  
Inventory Strategy

On classes of life distributions based on the mean time to failure function

2021 ◽  
Vol 58 (2) ◽  
pp. 289-313
Author(s):  
Ruhul Ali Khan ◽  
Dhrubasish Bhattacharyya ◽  
Murari Mitra
Keyword(s):  
Damage Model ◽  
Replacement Policy ◽  
Time To Failure ◽  
Mean Time To Failure ◽  
Moment Convergence ◽  
Life Distributions ◽  
Cumulative Damage Model ◽  
The Mean ◽  
Age Replacement ◽  
Mean Time

AbstractThe performance and effectiveness of an age replacement policy can be assessed by its mean time to failure (MTTF) function. We develop shock model theory in different scenarios for classes of life distributions based on the MTTF function where the probabilities $\bar{P}_k$ of surviving the first k shocks are assumed to have discrete DMTTF, IMTTF and IDMTTF properties. The cumulative damage model of A-Hameed and Proschan [1] is studied in this context and analogous results are established. Weak convergence and moment convergence issues within the IDMTTF class of life distributions are explored. The preservation of the IDMTTF property under some basic reliability operations is also investigated. Finally we show that the intersection of IDMRL and IDMTTF classes contains the BFR family and establish results outlining the positions of various non-monotonic ageing classes in the hierarchy.

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