Herausforderung in der Ersatzteilbeschaffung für die Anlageninstandhaltung

Abstract

In industrial manufacturing, spare parts management plays a central role in maintaining production. Particularly in engine production, as at BMW Motoren GmbH, the failure of a production system can lead to considerable disruption and high losses. Thus, it is essential to ensure the punctual procurement and availability of spare parts to reduce production downtimes and optimize equipment availability. This bachelor thesis deals with the challenges of spare parts procurement for plant maintenance. One focus is on the problem of demand forecasts, cooperation with suppliers and ensuring the quality of spare parts master data. Due to the erratic and irregular demand for spare parts, it is difficult to create precise demand forecasts, which can lead to excess or incorrect stocks. Supply problems, in particular the lack of required spare parts, can lead to plant downtime, which can cost the automotive industry millions. This bachelor thesis is divided into three parts. Starting with an introduction to spare parts management, the three areas of maintenance, spare parts procurement and warehousing are discussed, along with their objectives and strategies. The second part of this thesis then deals with the challenges in spare parts procurement and shows the consequences of inadequate forecasts, poor cooperation with suppliers and poor data quality. Finally, methods are presented based on researched solution approaches in order to get a grip on the challenges and thus ensure efficient and effective spare parts procurement. In addition, Power BI-solutions are presented that were implemented as part of an internship at BMW Motoren GmbH to optimize spare parts procurement. This bachelor thesis makes it clear that the challenges in spare parts procurement should not be underestimated, as supply problems and high costs can be the result. It is therefore essential to implement customized forecasting methods for spare parts, a distinctive supplier management and an effective master data quality management. These measures are crucial to ensure efficient and reliable spare parts procurement. Ultimately, these measures contribute to increased plant availability and increased competitiveness.

Date of Award	2024
Original language	German (Austria)
Supervisor	Reinhard Tockner (Supervisor)