Matthieu van der Heijden

On the availability of a k-out-of-N system given limited spares and repair capacity under a condition based maintenance strategy

This paper considers a k-out-of-N system with identical, repairable components. Maintenance is initiated when the number of failed components exceeds some critical level. After a possible set-up time, all failed components are replaced by spares. A multi-server repair shop repairs the failed components. The system availability depends on the spare part stock level, the maintenance policy and the repair capacity. We present a mathematical model supporting the trade-off between these three parameters. We present both an exact and an approximate approach to analyse our model. In some numerical experiments, we provide insight on the impact of repair capacity, number of spares and preventive maintenance policy on the availability.

On the interaction between maintenance, spare part inventories and repair capacity for a k-out-of-N system with wear-out

In this paper we consider a k-out-of-N system with identical, repairable components under a condition-based maintenance policy. Maintenance consists of replacing all failed and/or aged components. Next, the replaced components have to be repaired. The system availability can be controlled by the maintenance policy, the spare part inventory level, the repair capacity and repair job priority setting. We present two approximate methods to analyse the relation between these control variables and the system availability. Comparison with simulation results shows that we can generate accurate approximations using one of these models, depending on the system size.

Multi-echelon inventory control in divergent systems with shipping frequencies

We consider inventory control in a two-echelon divergent network, consisting of a central depot and multiple (non-identical) local warehouses. Past research has shown that (R, S) order-up-to control rules for this system type can easily be obtained using a decomposition approach, where the derivation of the order-up-to level S is separated from the derivation of the rationing parameters. We show that a similar approach can be used to solve models including different shipment frequencies at the two levels. For example, a central depot receives replenishment orders every four weeks, while replenishment orders to several local warehouses are shipped weekly. In this way, inventory imbalance can be reduced compared to immediate shipment to the local warehouses after goods receipt by the central depot. A method is presented to determine the control parameters such that target fill rates for the local warehouses are obtained. Extensive experimentation with the model shows that the stock reduction is relatively small for identical holding costs throughout the network. Then the largest reduction (6.6%) is obtained in case of frequent resupply in the downstream part of the network. Different shipment frequencies appear to be more useful if central holding costs are (considerably) less than local holding costs.

Dynamic one-way traffic control in automated transportation systems

In a project on underground freight transportation using Automated Guided Vehicles, single lanes for traffic in two directions are constructed to reduce infrastructure investment. Intelligent control rules are required to manage vehicle flows such, that collision is avoided and waiting times are minimised. In contrast to standard traffic control at intersections, these control rules should take into account significant driving times along the single lane (in our application up to 8 min). Whereas periodic control rules are often applied in traffic theory, we focus on adaptive rules such as look-ahead heuristics and dynamic programming algorithms. Numerical experiments show that our control rules reduce waiting times by 10–25% compared to a straightforward periodic rule. Dynamic programming yields the best results in terms of mean waiting times.

Estimating stock levels in periodic review inventory systems

Calculating the mean physical stock in a simple periodic review inventory system seems to be straightforward. However, the standard approximate expressions appear to yield inaccurate results, especially for low service levels. Low service levels are frequently encountered at intermediate nodes in cost-optimal solutions for multi-echelon systems. In this note, we present an improved approximate method that is both simple and accurate.

Last time buy decisions for products sold under warranty

Manufacturers supplying products under warranty need a strategy to deal with failures during the warranty period: repair the product or replace it by a new one, depending on e.g. age and/or usage of the failed product. An (implicit) assumption in virtually all models is that new products to replace the failed ones are immediately available at given replacement costs. Because of the short life cycles of many products, manufacturing may be discontinued before the end of the warranty period. At that point in time, the supplier has to decide how many products to put on the shelf to replace failed products under warranty that will be returned from the field (the last time buy decision). This is a trade-off between product availability for replacement and costs of product obsolescence. In this paper, we consider the joint optimization of repair-replacement decisions and the last time buy quantity for products sold under warranty. We develop approximations to estimate the total relevant costs and service levels for this problem, and show that we can easily find near-optimal last time buy quantities using a numerical search. Comparison to discrete event simulation results shows an excellent performance of our methods.

Modeling of capacitated transportation systems for integral scheduling

Motivated by a planned automated cargo transportation network, we consider transportation problems in which the finite capacity of resources (such as vehicles, docks, parking places) has to be taken into account. For such problems, it is often even difficult to construct a good feasible solution. We present a flexible modeling methodology which allows to construct, evaluate, and improve feasible solutions. This new modeling approach is evaluated on instances stemming from a simulation model of the planned cargo transportation system.

Additive Manufacturing and Its Impact on the Supply Chain

Additive Manufacturing (AM) is rapidly gaining interest as a highly innovative manufacturing technology, having many advantages over more conventional manufacturing methods. These advantages include the ability to produce very complex structures that are relatively easily customized to specific user requirements. The fact that AM services become affordable for small companies or even for consumers offers possibilities for decentralized manufacturing, downstream in the supply chain. In addition, AM allows for high degrees of flexibility, both in product design and manufacturing, as a result of using smart CAD systems that may be based on accurate scanning technologies. The ability to work with low setup times and costs and to largely eliminate work in progress inventories while maintaining a high degree of supply chain responsiveness makes AM a promising alternative for low-volume, high-value items. In this chapter, we outline the basics of AM technologies, after which we discuss at a more advanced level its impact on the supply chain. Next, we turn to spare parts delivery in after-sales service supply chains; these slow moving parts are often mentioned as ideal candidates for AM. In a state-of-the-art report, we provide a methodology for the identification of spare parts that may appear promising candidates for the application of AM. We conclude with a field study conducted at a service provider in the aerospace industry.