Age replacement policy in the case of no data: the effect of Weibull parameter estimation

Abstract

Age replacement is a common maintenance policy when wear-out failures occur, and it is characterised by periodic replacement of components. Data on time to failure (TTF), often modelled with the Weibull function, are necessary for estimating optimal replacement intervals to minimise the total maintenance costs. In many cases, such as new components, new machines or new installations, no TTF data are available, so the Weibull parameters and optimal replacement interval cannot be estimated. To overcome this problem, these parameters can be assessed from the experience of the maintenance engineers and technicians. The aim of this study is investigating the relationship between the error in parameter estimation and additional maintenance costs related to this error. Analysis of variance (ANOVA) and multifactorial analysis are carried out for investigating the influence of these estimations on the final costs. Economic decision maps are introduced for supporting maintenance engineering in defining the maintenance policy with minimal additional cost in the case of no data being available. The analysis shows that, when no data are available, the application of the age replacement policy can result in a global savings of more than 50% compared with corrective maintenance.

Optimal Periods of Conducting Preventive Maintenance to Reduce Expected Downtime and Its Impact on Improving Reliability

“…e importance of the reliability deals with the probability of a particular system performing a particular job for a specific period under the working conditions for which the system is designed. By studying the reliability of the systems, the performance and efficiency of these systems can be evaluated to delineate the type and size of production and improve it through the development of engineering designs for these systems [8][9][10][11].…”

Determination of Lathe Component Replacement Interval Using Age Replacment Method

“…Under this replacement policy, a unit or facility will be replaced at its age or at the time of failure. The age replacment method is a replacement policy when there is damage to components due to wear and tear on the system which is characterized by periodic component replacement (Sgarbossa et al, 2019). The Age replacment method is a method that performs preventive replacement on the age of the component of the facility or system that is being used and if there is damage to the component it will be reset to zero or to the beginning of the component's life (Ramadhan et al, 2016).…”

“…The time pattern of the damage is described in the form of a Weibull distribution. The Weibull distribution is one of the most popular probability functions used to describe the lifetime of a system failure event and this distribution can be used to estimate optimal maintenance time intervals and relative costs (Sgarbossa et al, 2019). The Weibull distribution is the most widely used distribution in determining the time of damage, because this distribution is either used for the increasing rate of damage or decreasing the rate of damage (Pamungkas, 2014).…”

Approaches to Dealing With Missing Data in Railway Asset Management

“…If only a small sample of data is missing, the record could be entered into the NoSQL database with a flag including the infilled asset ID. The Age Replacement Model [83] (see Figure 3) can then be run to check for consistent results with missing data presented. If the output of the Age Replacement model is inconsistent, one could be unable to measure trends or provide predictions for the time to failure of the asset under maintenance.…”