In this study, we model the warranty servicing costs under nonrenewing and renewing free repair warranties. We assume nonzero increasing repair times with the warranty cost depending on the length of the repair time. An increasing geometric process is used to model the consecutive repair times. We introduce the generalised alternating renewal process, which is an alternating process with cycles consisting of an item's operational time followed by the corresponding repair time. We derive analytical results for a generalised alternating renewal process with a finite time horizon and use them to evaluate the warranty costs over the warranty period and over the life cycle of the product under the nonrenewing free repair warranty and renewing free repair warranty. Properties of the model are demonstrated through a simulation study and through the application to warranty claims data from an automotive manufacturer.
In this study we model the warranty claims process and evaluate the warranty servicing costs under non-renewing and renewing free repair warranties. We assume that the repair time for rectifying the claims is non-zero and the repair cost is a function of the length of the repair time. To accommodate the ageing of the product and repair equipment, we use a decreasing geometric process to model the consecutive operational times and an increasing geometric process to model the consecutive repair times. We identify and study the alternating geometric process (AGP), which is an alternating process with cycles consisting of the item's operational time followed by the corresponding repair time. We derive new results for the AGP in finite horizon and use them to evaluate the warranty costs over the warranty period and over the life cycle of the product under a non-renewing free repair warranty (NRFRW), a renewing free repair warranty (RFRW) and a restricted renewing free repair warranty (RRFRW(n)). Properties of the model are demonstrated using a simulation study.
Economic development, variation in weather patterns and natural disasters focus attention on the management of water resources. This paper reviews the literature on the development of mathematical programming models for water resource management under uncertainty between 2010 and 2017. A systematic search of the academic literature identified 448 journal articles on water resource management for examination. Bibliometric analysis is employed to investigate the methods that researchers are currently using to address this problem and to identify recent trends in research in the area. The research reveals that stochastic dynamic programming and multistage stochastic programming are the methods most commonly applied. Water resource allocation, climate change, water quality and agricultural irrigation are amongst the most frequently discussed topics in the literature. A more detailed examination of the literature on each of these topics is included. The findings suggest that there is a need for mathematical programming models of large-scale water systems that deal with uncertainty and multiobjectives in an effective and computationally efficient way.
Increasing legislative and societal pressures are requiring manufacturers to operate more sustainably and to take responsibility for the fate of their goods after they have been used by consumers. A hybrid remanufacturing system, in which newly produced and remanufactured used goods are sold on separate markets but also act substitutes for each other, is described and modelled using a semi-Markov decision process. The model provides an optimal policy, which specifies production, remanufacturing and substitution decisions. The model is used to explore the properties of this hybrid remanufacturing system, and in particular, the managerial implications associated with upward and downward substitution.
Fitting models to failure data is an important topic in reliability. The resulting models can be useful both for manufacturers as well as for end-users. In this paper we provide details of some methods from the literature which can be used as a starting point when analysing and fitting models to failure data from repairable items. In particular we focus on obtaining analytical estimates of the intensity of a non-homogeneous Poisson process. We illustrate some of these methods on failure data from the warranty database of a major car manufacturer
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