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Improving Raw Material Ordening and Production Planning Process

Ghanbarimobarakeh, Mozhdeh (2025)

 
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Ghanbarimobarakeh, Mozhdeh
2025
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-2025052013734
Tiivistelmä
The case company in this thesis was facing challenges in their process of ordering raw materials and planning production. The diversity of products, the price of raw materials and the schedule of some items had created problems such as lack of inventory of the final product, excessive purchase of raw materials and delays in production. The company's existing methods to deal with these challenges were not flexible enough, and this affected speed, responsiveness and ultimately customer dissatisfaction. Therefore, this thesis sought to provide an operational and practical framework for improving these processes.

This study was conducted in four stages with an applied approach and qualitative methods. The first stage was a Current State Analysis, carried out through interviews, observations and also workshops covering key topics and identifying strengths and weaknesses. The findings showed issues with the planning system, communication methods, and inventory and order management. Relevant literature was researched for best practise and a Conceptual Framework was developed based on it.

The first proposed models were later developed into flow charts with the help of members of the production planning and management department and branches, and in collaboration with the plant machinery departments. In the final stage, the revised frameworks and procedures were validated in a training workshop with the company’s senior management team.

The outcome enables the company to achieve operational efficiencies such as minimizing waste and maximizing resource output through on-time delivery of raw material orders at the branch level, better inventory management, and higher forecasting accuracy. It also allows the company to be more responsive to customer and branch orders and the supply chain.
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