A condition-based maintenance policy for multi-component systems with a high maintenance setup cost

Condition-based maintenance (CBM) is becoming increasingly important due to the development of advanced sensor and ICT technology, so that the condition data can be collected remotely. We propose a new CBM policy for multi-component systems with continuous stochastic deteriorations. To reduce the high setup cost of maintenance, a joint maintenance interval is proposed. With the joint maintenance interval and control limits of components as decision variables, we develop a model for the minimization of the average long-run maintenance cost rate of the systems. Moreover, a numerical study on a case of a wind power farm consisting of a large number of non-identical components is performed, including a sensitivity analysis. At last, our policy is compared to a corrective-maintenance-only policy

Efficient heuristics for two-echelon spare parts inventory systems with an aggregate mean waiting time constraint per local warehouse

This paper presents solution procedures for determining close-to-optimal stocking policies in a multi-item two-echelon spare parts inventory system. The system we consider consists of a central warehouse and a number of local warehouses, and there is a target for the aggregate mean waiting time per local warehouse. We develop four different heuristics and derive a lower bound on the optimal total cost. The effectiveness of each heuristic is assessed by measuring the relative gap between the heuristic’s total cost and the lower bound. The results of the computational experiments show that a greedy procedure performs most satisfactorily. It is accurate as indicated by relatively small gaps, easy to implement, and furthermore, the computational requirements are limited. The computational efficiency can be increased by using Graves’ approximate evaluation method instead of an exact evaluation method, while the results remain accurate

Maintenance optimization for a Markovian deteriorating system with population heterogeneity

We develop a partially observable Markov decision process model to incorporate population heterogeneity when scheduling replacements for a deteriorating system. The single-component system deteriorates over a finite set of condition states according to a Markov chain. The population of spare components that is available for replacements is composed of multiple component types that cannot be distinguished by their exterior appearance but deteriorate according to different transition probability matrices. This situation may arise, for example, because of variations in the production process of components. We provide a set of conditions for which we characterize the structure of the optimal policy that minimizes the total expected discounted operating and replacement cost over an infinite horizon. In a numerical experiment, we benchmark the optimal policy against a heuristic policy that neglects population heterogeneity

The European Union, borders and conflict transformation: the case of Cyprus

Much of the existing literature on the European Union (EU), conflict transformation and border dynamics has been premised on the assumption that the nature of the border determines EU intervention and the consequences that flow from this in terms of EU impact. The article aims to transcend this literature through assessing how domestic interpretations influence EU border transformation in conflict situations, taking Cyprus as a case study. Moreover, the objective is to fuse the literature on EU bordering impact and perceptions of the EU’s normative projection in conflict resolution. Pursuing this line of inquiry is an attempt to depart from the notion of borders being constructed solely by unidirectional EU logics of engagement or bordering practices to a conceptualization of the border as co-constituted space, where the interpretations of the EU’s normative projections by conflict parties, and the strategies that they pursue, can determine the relative openness of the EU border