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Optimizing inventory to improve customer satisfaction : a case study of spare parts business.

Maisuradze, Veronika (2026)

 
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Maisuradze, Veronika
2026
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
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Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202604146474
Tiivistelmä
Efficient inventory management of spare parts is crucial in the mining and tunneling industry, where long lead times and equipment failure can seriously affect customers’ operations. The goal of the master’s thesis is to determine main problems in spare parts inventory management in the case Company X, a manufacturer of equipment for the mining and tunneling industry, and to suggest practical improvement actions, which are meant to minimize stockouts, surplus inventory and customer dissatisfaction.

The study is conducted using a qualitative case study approach, which is based on semi-structured interviews with inventory specialists and industry experts at the case Company X. The interviews were used to determine main causes of inventory difficulties, which include inaccurate demand forecasting related to limitations of the previous ERP system, unreliable forecast information from subsidiaries, incorrect lead times in the system, and communication gaps in spare parts replacement processes. These problems contribute to low stock and challenges in handling rush orders.

Based on the identified problems, the thesis suggests a few practical recommendations to improve spare parts inventory management. The proposed measures concentrate on enhancing forecasting reliability, increasing accuracy of lead time data, improving internal communication processes and utilizing technological solutions to support inventory decision-making. The suggested recommendations are aimed at improving customer service by lowering stock-out risks and reducing lead time variability. The outcomes of this thesis give practical insights for Company X. The recommendations were validated by the industry expert and will serve as a basis for future implementation.
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