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Ben-Daya, M. and Rahim, M.A. (2001) Integrated Production, Quality & Maintenance Models. In: Rahim, M.A. and Ben-Daya, M., eds., Integrated Models in Production Planning, Inventory, Quality, and Maintenance, Springer, Boston, MA, 3-28.
https://doi.org/10.1007/978-1-4615-1635-4_1

has been cited by the following article:

• TITLE: Study of Optimal Frequency to the Repairable System Due to Failure Finding Interval to Maximize Availability System

  AUTHORS: Emmanuel Hagenimana, Charline Uwilingiyimana, Umuraza Clarisse

  KEYWORDS: Maximization, Failure Interval, Repairable System, Inspection Interval, Availability System, Optimal Inspection

  JOURNAL NAME: Journal of Applied Mathematics and Physics, Vol.11 No.6, June 30, 2023

  ABSTRACT: This research article is based on a study of optimal frequency to the repairable system due to the failure finding interval to maximize as well as minimize the availability of some components devices. We studied together maintenance and corrective actions that carried out item of failure and periodic failure finding designed to check whether a system is still working. The model is proved as well as useful application in detecting the problem related to finding failure tasks of different scheme devices by maximization. The model formulated and the numerical application to the relevant mathematical model have been discussed to demonstrate the article quality. Therefore based on probability analytic development, the optimal maintenance policy is then obtained as solution of an optimization problem in which the maintenance cost rate is the objective function and the risk of corrective maintenance is the constraint function. Finally, the solution to the optimal device in the considered development model has been well adjusted due to derivation to the experimental observation rather than theory which will be taken into consideration in the next applied practical design research related and the system device provided that, the proactive device agreed with using the exponential distribution to the survive distribution function which can not be considered as valid.