Machinery/Service System Scheduled Replacement Time Determination: A Combine Weighted Aggregated Sum Product Assessment, Additive Ratio Assessment and Age Replacement Model Approach

2018 ◽  
Vol 10 (1) ◽  
Author(s):  
Ikuobase Emovon ◽  
◽  
Chinedum Ogonna Mgbemena ◽  
Keyword(s):  
Service System ◽  
Replacement Model ◽  
Time Determination ◽  
Product Assessment ◽  
Age Replacement ◽  
Replacement Time ◽  
Model Approach

scholarly journals Delayed Age Replacement Policy with Uncertain Lifetime

2015 ◽  
Vol 2015 ◽  
pp. 1-6 ◽  
Author(s):  
Xueyan Li ◽  
Chunxiao Zhang
Keyword(s):  
Time Span ◽  
Replacement Policy ◽  
Infinite Time ◽  
Uncertainty Distribution ◽  
Uncertain Variables ◽  
Optimal Replacement ◽  
Replacement Model ◽  
Age Replacement ◽  
Uncertain Distribution ◽  
Replacement Time

This paper considers the delayed age replacement policy, in which the lifetimes of all units are assumed to be uncertain variables, and the lifetime of the first unit has an uncertainty distribution which is different from the others. A delayed age replacement model which is concerned with finding the optimal replacement time to minimize the expected cost is developed. In the policy, the optimal replacement time is irrelevant to the uncertain distribution of lifetime of the first unit over the infinite time span.

scholarly journals Preventive maintenance pada mesin die casting dengan age replacement model untuk peningkatan reliabilitas mesin

2020 ◽  
Vol 12 (1) ◽  
pp. 1
Author(s):  
Andriani Andriani ◽  
Ikhsan Romli
Keyword(s):  
Preventive Maintenance ◽  
Die Casting ◽  
Casting Machine ◽  
Engine Performance ◽  
Cost Savings ◽  
Distribution Patterns ◽  
Distribution Data ◽  
Time Data ◽  
Replacement Model ◽  
Age Replacement

In an industry, the maintenance department plays a very important role in ensuring the smooth production process. The method of machine maintenance with preventive maintenance is a strategy that can be used to repair existing machines. This is related to proper and regular maintenance can improve engine performance and reduce the level of engine damage which will increase the continuity of production activities. In the die casting division of PT Astra Honda Motor in the observation on the die casting machine 07 there were 45 times damage to the ladle component and 11 times the damage to the auto spray component. These two components are critical components of the 07 die casting machine. After testing the compatibility index and the good compatibility of the damage time data and repair time data to obtain distribution data distribution patterns, obtain the tablespoon component MTTF assessment results of 107,833 hours and auto spray components amounting to 314,226 hours. Whereas the MTTR value of the spoon component is 0.385 hours and the auto spray component is 0.766 hours. The next step is to look for critical component replacement time intervals with the age replacement model, to further review whether it is related to increased reliability, decrease in total downtime, and cost savings before preventive maintenance is carried out and after preventive maintenance is carried out.

scholarly journals Replacement Model for Street Lighting Systems

2021 ◽  
Vol 40 (1) ◽  
pp. 49-55
Author(s):  
A.M. Usman ◽  
Y.A. Adediran ◽  
A.O. Otuoze ◽  
O.O. Mohammed ◽  
O.S. Zakariyya
Keyword(s):  
Field Survey ◽  
Optimal Time ◽  
North Central ◽  
Street Lighting ◽  
Maintenance Costs ◽  
Optimal Replacement ◽  
Replacement Model ◽  
Lighting Systems ◽  
The University ◽  
Replacement Time

Replacing failed bulbs of streetlights in a location can be very tasking and expensive if the optimal time for replacement is not determined. In this paper, a model has been developed that helps to establish the optimal time for the replacement of streetlight bulbs. Burnt-out bulbs are replaced individually when they fail, and group replacement is carried out on all bulbs after a specified time. The costs for both individual replacement and group replacement are determined. The developed model was applied to locally sourced data from a field survey of a streetlight installation at the University of Ilorin, Ilorin, North-central Nigeria. The model gave the optimum replacement time of burnt-out bulbs as the eighteenth week when applied to the data used in this work. The optimum replacement time will be dependent on the dataset used. This makes the developed model useful in establishing the optimal replacement time of any stochastically failing items that are in large quantities. The model will help to reduce maintenance costs for facility managers.

Effective Optimization of Statistical Decisions for Age Replacement Problems under Parametric Uncertainty

2017 ◽  
pp. 1-16
Author(s):  
N. A. Nechval ◽  
K. N. Nechval
Keyword(s):  
Original Problem ◽  
Decision Rules ◽  
Parametric Uncertainty ◽  
Statistical Technique ◽  
Unknown Parameters ◽  
Sample Statistic ◽  
Invariant Embedding ◽  
Replacement Model ◽  
Statistical Decisions ◽  
Age Replacement

In this chapter, an innovative model for age replacement is proposed. The costs included in the age replacement model are not assumed to be constants. For effective optimization of statistical decisions for age replacement problems under parametric uncertainty, based on a past random sample of lifetimes, the pivotal quantity averaging (PQA) approach is suggested. The PQA approach represents a simple and computationally attractive statistical technique. In this case, the transition from the original problem to the equivalent transformed problem (in terms of pivotal quantities and ancillary factors) is carried out via invariant embedding a sample statistic in the original problem. The approach allows one to eliminate unknown parameters from the problem and to find the better decision rules, which have smaller risk than any of the well-known decision rules. Unlike the Bayesian approach, the proposed approach is independent of the choice of priors. For illustration, numerical examples are given.

scholarly journals Failure-Correlated Opportunity-based Age Replacement Models

2019 ◽  
Vol 27 (02) ◽  
pp. 2040008
Author(s):  
Tadashi Dohi ◽  
Hiroyuki Okamura
Keyword(s):  
Arrival Time ◽  
Failure Time ◽  
Unit System ◽  
Hazard Gradient ◽  
Age Replacement ◽  
The Cost ◽  
Bivariate Copula ◽  
Bivariate Probability ◽  
Vector Valued ◽  
Replacement Time

In this paper, we extend the existing opportunity-based age replacement policies by taking account of dependency between the failure time and the arrival time of a replacement opportunity for one-unit system. Based on the bivariate probability distribution function of the failure time and the arrival time of the opportunity, we focus on two opportunity-based age replacement problems and characterize the cost-optimal age replacement policies which minimize the relevant expected costs, with the hazard gradient, which is a vector-valued bivariate hazard rate. Through numerical examples with the Farlie–Gumbel–Morgenstern bivariate copula and the Gaussian bivariate copula having the general marginal distributions, we investigate the dependence of correlation between the failure time and the opportunistic replacement time on the age replacement policies.

Forecasted Inflation Based Block Replacement Model Using Stochastic Process

2014 ◽  
Vol 592-594 ◽  
pp. 2716-2722
Author(s):  
B. Srinivas ◽  
S. Gajanana ◽  
K. Hemachandra Reddy
Keyword(s):  
Interest Rates ◽  
Present Model ◽  
Entire Group ◽  
Cyclical Fluctuation ◽  
Optimal Replacement ◽  
Replacement Model ◽  
The Individual ◽  
The Cost ◽  
Replacement Time ◽  
The Ideal

The replacement problems are concerned with the situation that arises on decrease in the efficiency of the item, failure or breakdown. The problem of replacement is to identify the best policy to determine the ideal replacement time which is most economical. Group replacement model is applicable to the items that fail completely on usage and the result is group replacement age for the entire group of items in the system irrespective of whether they are functioning or not. The present paper proposes intermediate states i.e., minor repair and major repair states in between functioning and irreparable breakdown states. In addition, higher order Markov chains are used in generating the probabilities of items which are falling in different states. In order to consider money value, macro-economic variable, inflation is considered in this model. In the present model, real interest rates are calculated using forecasted inflation for future periods. Future period values of inflation are predicted by using the forecasting technique and a regression model with trigonometric function. These methods are used to accommodate cyclical fluctuation in the prices of items/inflation. The optimal replacement age is the time bucket in which the average cost of the individual replacement, repair and the cost of the items is minimum.

RELIABILITY PROPERTIES OF MEAN TIME TO FAILURE IN AGE REPLACEMENT MODELS

2010 ◽  
Vol 17 (01) ◽  
pp. 15-26 ◽  
Author(s):  
G. ASHA ◽  
N. UNNIKRISHNAN NAIR
Keyword(s):  
Residual Life ◽  
Stochastic Orders ◽  
Mean Residual Life ◽  
Time To Failure ◽  
Mean Time To Failure ◽  
Replacement Model ◽  
The Mean ◽  
Age Replacement ◽  
The Relationship ◽  
Mean Time

In this article some properties of the mean time to failure in an age replacement model is presented by examining the relationship it has with hazard (reversed hazard) rate and mean (reversed mean) residual life functions. An ordering based on mean time to failure is used to examine its implications with other stochastic orders.

Functional Estimation for a Multicomponent Age Replacement Model

1999 ◽  
Vol 19 (1-2) ◽  
pp. 135-156 ◽  
Author(s):  
Pierre L'Ecuyer ◽  
Benoit Martin ◽  
Felisa J. Vázquez-Abad
Keyword(s):  
Functional Estimation ◽  
Replacement Model ◽  
Age Replacement

scholarly journals Penentuan Interval Waktu Penggantian Komponen Kritis Pada Mesin Volpack Menggunakan Metode Age Replacement

2017 ◽  
Vol 16 (2) ◽  
pp. 92
Author(s):  
Yanuar Yuda Prawiro
Keyword(s):  
Cost Savings ◽  
Solenoid Valve ◽  
Time Interval ◽  
Preventive Replacement ◽  
Replacement Method ◽  
Schedule Interval ◽  
Age Replacement ◽  
Engine Components ◽  
A Company ◽  
Replacement Time

CV. Cool Clean is a company engaged in packing tissue. During this time the company only perform corrective action that causes disruption of the production process due to frequent damage of a sudden the engine components volpack. In this study used a model of preventive replacement that can reduce downtime and costs. The method used to obtain the schedule interval a critical component is age replacement method. Seal heater obtained replacement time interval of 30 days with a 22% reduction in downtime. Replacement interval for knife foil is 26 days with a 27% reduction in downtime. Replacement interval for solenoid valve is30 days with a 29% reduction in downtime. Replacement interval forOring seal is 18 days with a 29% reduction in downtime. Replacement interval for needle bearing is 62 days with a 25% reduction in downtime. Results of this study also showed that by applying age replacement can save costs for seal heater Rp. 974.000 or 23%. Knife foil cost savings of Rp. 1.251.409 or 22%. Solenoid valve cost savings of Rp.546.539 or 24%. Oring seal cost savings of Rp. 350.096 or 26%. And needle bearing cost savings of Rp. 196.712 or 26%.

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