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Showing papers by "Viliam Makis published in 2001"


Journal ArticleDOI
01 Feb 2001-Infor
TL;DR: The analysis of a preventive replacement policy of the control-limit type for a deteriorating system subject to inspections at discrete points of time is presented, using Cox’s PHM with a Weibull baseline hazard function and time dependent stochastic covariates.
Abstract: The focus of the paper is the optimization of condition-based maintenance decisions within the contexts of physical asset management. In particular, the analysis of a preventive replacement policy of the control-limit type for a deteriorating system subject to inspections at discrete points of time is presented. Cox’s PHM with a Weibull baseline hazard function and time dependent stochastic covariates is used to describe the failure rate of the system. The methods of estimating model parameters and the calculation of the optimal policy are given. The structure of the decision-making software EXAKT is presented. Experience with collecting, preprocessing and using real oil and vibration data is reported.

195 citations


Journal ArticleDOI
TL;DR: In this article, a stochastic dynamic programming approach is taken to obtain the optimal tool replacement times in a flexible manufacturing system, and the optimal schedule is obtained by minimizing the total expected cost over a finite time horizon for a given sequence of operations.
Abstract: In Flexible Manufacturing Systems (FMSs), a cutting tool is frequently used for different operations and on different part types to minimize tool change-overs and the number of tools required, and to increase part-routing flexibility. In such situations, the tools become shared resources and work in job-dependent, changeable and nonhomogeneous conditions. It is well known that the tool failure rate depends on both age and machining conditions and that tool reliability is a function of the duration, machining conditions, and the sequence of the operations in FMS. The objective of this paper is to obtain a schedule of the optimal preventive replacement times for the cutting tools over a finite time horizon in a flexible manufacturing system. We assume that the tool will be replaced either upon failure during an operation or preventively after the completion of each operation, incurring different replacement costs. A standard stochastic dynamic programming approach is taken to obtain the optimal tool replacement times. The optimal schedule is obtained by minimizing the total expected cost over a finite time horizon for a given sequence of operations. A computational algorithm is developed and a numerical example is given to demonstrate the procedure.

41 citations


Journal ArticleDOI
TL;DR: In this paper, the authors study a maintenance model with general repair and two types of replacement: failure and preventive replacement, and show that a generalized repair-cost-limit policy is optimal and the preventive replacement time depends on the virtual age of the system and on the length of the operating time since the last repair.
Abstract: In this paper, we study a maintenance model with general repair and two types of replacement: failure and preventive replacement. When the system fails a decision is made whether to replace or repair it. The repair degree that affects the virtual age of the system is assumed to be a random function of the repair-cost and the virtual age at failure time. The system can be preventively replaced at any time before failure. The objective is to find the repair/replacement policy minimizing the long-run expected average cost per unit time. It is shown that a generalized repair-cost-limit policy is optimal and the preventive replacement time depends on the virtual age of the system and on the length of the operating time since the last repair. Computational procedures for finding the optimal repair-cost limit and the optimal average cost are developed. This model includes many well-known models as special cases and the approach provides a unified treatment of a wide class of maintenance models.

30 citations


Journal ArticleDOI
TL;DR: In this article, the optimal control of a production process subject to a deterministic drift and to random shocks is studied and an algorithm to find the initial setting of the process mean and the resetting time that minimizes the expected average cost per unit time is presented.
Abstract: We study the optimal control of a production process subject to a deterministicdrift and to random shocks. The process mean is observable at discrete points of time after producing a batch and, at each such point, a decision is made whether to reset the process mean to some initial value or to continue with the production. The objective is to find the initial setting of the process mean and the resetting time that minimizes the expected average cost per unit time. It is shown that the optimal control policy is of a control limit type. An algorithm for finding the optimal control parameters is presented.

1 citations