| Form of studies |
Master |
| Title of the study programm |
Logistics and Supply Chain Management |
| Title in original language |
Krājumu vadīšanas metožu analīze mazajiem uzņēmumiem: gadījuma izpēte |
| Title in English |
Analysis of Inventory Management Methods for Small Enterprises: A Case Study |
| Department |
12100 Institute of Information Technology |
| Scientific advisor |
Andrejs Romānovs |
| Reviewer |
Jeļena Pečerska |
| Abstract |
Inventory management plays a critical role in controlling and monitoring the flow of raw materials and finished goods. One of the most important decisions that affects the effectiveness of inventory management is inventory policy. Hence, the aim of this research is to evaluate inventory policies that can help an enterprise save money while still meeting customer demand. This paper proposes a number of analytical methods for studying inventory systems. However, Systems with stochastic demand and lead time are extremely complex, making simulation the most realistic method of study, as using analytical methods to model and analyze such complex systems is impractical. In this paper, a discrete event simulation is modeled for a Greek company of fast-moving consumer goods for testing various inventory policies for a single item inventory system which follows continuous review policy (s,Q). The simulation is translated in Python programming language and the results are extracted to EXCEL spreadsheets for further statistical analysis. Many policies produced as results with total inventory costs and service level as the output variables in interest. The study's findings show that the obtained solution will assist decision-makers in achieving cost-effectiveness based on predetermined service level target.
The master thesis contains 81 pages, 14 images, 23 tables, 40 reference sources, and 7 appendices. |
| Keywords |
SIMULATION, INVENTORY MANAGEMENT, MODELING |
| Keywords in English |
SIMULATION, INVENTORY MANAGEMENT, MODELING |
| Language |
eng |
| Year |
2021 |
| Date and time of uploading |
01.06.2021 21:02:51 |
