Analysing divergent logistic networks with local (R, S) inventory control

This paper deals with divergent logistic networks where the inventory at each node is controlled using a periodic review strategy with order-up-to level. An approximate method is presented to analyse the network performance (service levels, mean physical stock). The method is tested on a range of 2-echelon and 3-echelon networks by comparison to results from Monte Carlo simulation. We conclude that the approximation accuracy is sufficient for global network design in many practical situation

Contact nucleation: in situ and ex situ observations of surface damaging

To investigate the damaging done to a crystal surface potassium dihydrogen phosphate, KDP and potassium hydrogen phthalate, KAP) due to a crystal-rod contact, both ex situ and in situ experiments were performed and the impact sites studied either using an interference contrast microscope or a scanning electron microscope. An ex situ contact (performed in air) causes subsurface cracks and the breakage of small fragments (KDP) or the removal of thin plates (KAP) from the surface. In the former case the fragments have thicknesses roughly corresponding to the height of macrosteps present on the surface. Contacts during growth on KAP produced secondary nuclei; the crystal size distribution of these nuclei displays a log-normal behaviour

Modeling Stochastic Lead Times in Multi-Echelon Systems

In many multi-echelon inventory systems, the lead times are random variables. A common and reasonable assumption in most models is that replenishment orders do not cross, which implies that successive lead times are correlated. However, the process that generates such lead times is usually not well defined, which is especially a problem for simulation modeling. In this paper, we use results from queuing theory to define a set of simple lead time processes guaranteeing that (a) orders do not cross and (b) prespecified means and variances of all lead times in the multiechelon system are attained

A Minimum Cost Flow model for Level of Repair Analysis

Given a product design and a repair network for capital goods, a level of repair analysis determines for each component in the product (1) whether it should be discarded or repaired upon failure and (2) at which location in the repair network to do this. In this paper, we show how the problem can be modelled as a minimum cost ow problem with side constraints. Advantages are that (1) solving our model requires less computational effort than solving existing models and (2) we achieve a high model exibility, i.e., many practical extensions can be added. Furthermore, we analyse the added value of modelling the exact structure of the repair network, instead of aggregating all data per echelon as is common in the literature. We show that in some cases, cost savings of over 7% can be achieved. We also show when it is sufficient to model the repair network by echelons only, which requires less input data

Level of Repair Analysis: A Generic Model

Given a product design and a repair network, a level of repair analysis (lora) determines for each component in the product (1) whether it should be discarded or repaired upon failure and (2) at which echelon in the repair network to do this. The objective of the lora is to minimize the total (variable and fixed) costs. We propose an ip model that generalizes the existing models, based on cases that we have seen in practice. Analysis of our model reveals that the integrality constraints on a large number of binary variables can be relaxed without yielding a fractional solution. As a result, we are able to solve problem instances of a realistic size in a couple of seconds on average. Furthermore, we suggest some improvements to the lora analysis in the current literature

Practical extensions to the level of repair analysis

The level of repair analysis (lora) gives answers to three questions that are posed when deciding on how to maintain capital goods: 1) which components to repair upon failure and which to discard, 2) at which locations in the repair network to perform each type of repairs, and 3) at which locations in the network to deploy resources, such as test equipment. The goal is to achieve the lowest possible life cycle costs. Various models exist for the lora problem. However, these models tend to be restrictive in that specic business situations cannot be incorporated, for example, having repair equipment with a capacity restriction or the occurrence of unsuccessful repairs.We discuss and model various practically relevant extensions to an existing minimum cost \ud ow formulation for the lora problem. We show the added value of these model renements in an extensive numerical experiment

An efficient model formulation for level of repair analysis \ud

Given a product design and a repair network, a level of repair analysis (LORA)\ud determines for each component in the product (1) whether it should be discarded or repaired\ud upon failure and (2) at which echelon in the repair network to do this. The objective of\ud the LORA is to minimize the total (variable and fixed) costs. We propose an IP model that\ud generalizes the existing models, based on cases that we have seen in practice. Analysis of\ud our model reveals that the integrality constraints on a large number of binary variables can\ud be relaxed without yielding a fractional solution. As a result, we are able to solve problem\ud instances of a realistic size in a couple of seconds on average. Furthermore, we suggest some\ud improvements to the LORA analysis in the current literatur

An optimal approach for the joint problem of level of repair analysis and spare parts stocking

We propose a method that can be used when deciding on how to maintain capital goods, given a product design and the layout of a repair network. Capital goods are physical systems that are used to produce products or services. They are expensive and technically complex and have high downtime costs. Examples are manufacturing equipment, defense systems, and medical devices