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Volkswagen Technical Development (TE) is responsible for all prototype development and prototype production for the Volkswagen brand and has its own logistics department (TE-Logistics). In the logistics of prototype parts in the automotive industry, new versions of prototype parts (henceforth referred to as updating parts) are repeatedly assembled in finished prototype vehicles. These updating parts are stored in warehouses and provided to an assembly site to ensure a timely assembly of the associated prototype vehicles. As the internal warehouse on the company site is not large enough for the high variety of parts, an additional external warehouse in the logistics network is needed. However, since prototype parts are unique, the allocation of the parts in suitable warehouses is particularly important. Currently, the various warehouses and the short-term demands repeatedly lead to reactive transshipments between the warehouses. To this end, we developed an approach for proactive transshipments based on a machine learning forecast and a mixed-integer linear programming model for planning proactive transshipments of parts between the warehouses to minimize transport costs. The model is based on a probability estimation of future demands to anticipate the expected optimal warehouse. After the model had revealed high improvement potential through a case study with real-world data in terms of costs and availability time compared to the current reactive process, we derived decision rules and developed a rule-based heuristic algorithm that leads to the optimal solution for the industrial use case. We implemented the heuristic with a spreadsheet-based decision support system (DSS) for daily transshipment planning. After successful test implementation, TE-Logistics estimated the annual cost savings for transport to be approximately 10%.

A research method for multi-echelon inventory allocation of civil aircraft spare parts with lateral transshipments and maintenance ratio is proposed in this paper, and the maintenance rate is considered into the inventory model, aiming at the problem of multi-echelon inventory allocation with lateral transshipments for civil aircraft spare parts. Firstly, the principle of the multi-echelon inventory model with lateral transshipments and maintenance ratio is proposed. Then, by considering the fleet availability and the satisfaction ratio as the constraints, a mathematical model is built with the inventory system total cost as the optimization objective. Secondly, the procedure of solving multi-echelon inventory allocation model considering the influence of lateral transshipments and maintenance ratio is discussed based on the marginal analysis method. Finally, some components of Boeing 737 are selected as the research objects, the multi-echelon inventory allocation is investigated by considering lateral transshipments and maintenance ratio. The analysis results in this paper show the best number of multi echelon inventory allocation, the minimum inventory system total cost and the fleet availability are 1.205 million dollars and 0.9909 respectively. Comparing the traditional inventory model without considering lateral transshipments and maintenance ratio, and the model which only considers the maintenance ratio, the results indicate that the model offered in this paper could reduce the total cost of inventory system significantly, and provides theoretical support and method guidance for the accurate allocation of multi echelon inventory optimization for civil aircraft spare parts.