Inventory Grouping and Sensitivity Analysis in Multi-Echelon Spare Part Provisioning Systems

/pdf/dynamism-in-inter-organizational-service-orchestration-an-4b3llwvbtt.pdf

Dynamism in inter-organizational service orchestration:an analysis of the state of the art

Classification methods for problem size reduction in spare part provisioning

Configuring supply chains (SCs) is critical to spare parts retailers’ success, entailing two key aspects: stock deployment into distribution centres (DCs) (i.e. inventory centralisation or decentralisation) and stock supply in each DC (how many spare parts to supply and how often). Given the unpredictability of spare parts demand, stock deployment and supply policies should be regularly reviewed, adapting to fluctuations in customer needs. A viable way to do this is to adopt a multi-criteria ABC criticality classification. However, the multi-criteria ABC criticality classification has often been used to plan stock supply policies in a single DC, but only once to plan spare parts deployment. Nevertheless, the available literature methodology presents major limitations, being not applicable in real companies. Therefore, this paper provides a novel methodology, called SP-LACE, which first reviews the configuration of spare parts SCs based on a multi-criteria criticality classification. Then, allows, for the first time, to evaluate the economic benefits of the reviewed SC configuration. SP-LACE was tested on two case studies and compared with the literature methodology. The results indicate that it provides economic benefits (in terms of total SC cost), overcoming the limitations of the literature methodology and ensuring high service levels. 

A data-driven methodology for the periodic review of spare parts supply chain configurations

The role of prescriptive data and non-linear dimension-reduction methods in spare part classification

In this paper we consider a multi-item, single-location inventory control problem. We look at how to design a generalized ABC classification scheme to minimize the inventory investment costs while satisfying an aggregate fill rate constraint by considering four different aspects of a classification: the classification criteria, the number of classes, the class sizes, and the target fill rate per class. Using multiple alternatives per aspect and considering all combinations, we determine the best combination of those four aspects. The results are measured against the system approach, which specifies a separate target fill rate for each SKU and therefore is optimal but more difficult to manage. We find near-optimal results by applying our approach on empirical data. The most important insight that we generate is that the best class sizes which need to be carefully decided depend on the target aggregate fill rate whereas common used rule of thumbs to determine class sizes may lead to large inventory investment costs.

/pdf/design-of-a-near-optimal-generalized-abc-classification-for-4u35kc643v.pdf

Design of a near-optimal generalized ABC classification for a multi-item inventory control problem

In recent years, control techniques such as dynamic induction control (often referred to as “the pulse”) have shown great potential in increasing wake mixing, with the goal of minimising turbine-to-turbine interaction within a wind farm. Dynamic induction control disturbs the wake by varying the thrust of the turbine over time, which results in a time-varying induction zone. If applied to a floating wind turbine, this time-varying thrust force will, besides changing the wake, change the motion of the platform. In light of the expected movement, this work investigates if applying the pulse to a floating wind turbine yields similar results to that of the pulse applied to bottom-fixed turbines. This is done by considering first the magnitude of motions of the floating wind turbine due to the application of a time-varying thrust force and secondly the effect of these motions on the wake mixing. A frequency response experiment shows that the movement of the floating turbine is heavily frequency dependent, as is the thrust force. Time domain simulations, using a free-wake vortex method with uniform inflow, show that the expected gain in average wind speed at a distance of 5 rotor diameters downstream is more sensitive to the excitation frequency compared to a bottom-fixed turbine with the same pulse applied. This is due to the fact that, at certain frequencies, platform motion decreases the thrust force variation and thus reduces the onset of wake mixing.

The dynamic coupling between the pulse wake mixing strategy and floating wind turbines

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Design of a near-optimal generalized ABC classification for a multi-item inventory control problem

The dynamic coupling between the pulse wake mixing strategy and floating wind turbines