Διαδικασία διατήρησης αποθέματος - Συστημική προσέγγιση, χρήση και ανάπτυξη πληροφοριακών συστημάτων σε πραγματική περίπτωση χρήσης για τη βέλτιστη λήψη αποφάσεων
Inventory management - Systemic approach along with software development in real use case for optimal decision making
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Keywords
DCSYM ; VENSIM ; Forio ; R ; Python ; Εφοδιαστική αλυσίδα ; Συστημική ανάλυση ; Διαχείριση αποθεμάτων ; Logistics ; Warehouse managementAbstract
The core idea of this master thesis lies on the identification of a general problem faced by the vast majority of companies that are part of the supply chain as a whole. This particular problem is spotted on the inventory management procedures followed by the above-mentioned companies and affects directly their respective productivity levels. It is commonly accepted that wholesalers, retailers or even production entities cannot effectively forecast demand levels. Furthermore, they cannot put in practice safety -stock or timely restocking procedures. As a result, they suffer losses deriving from overstocking or understocking situations. As we continue, we will provide insight while using systemic and general Data Analytics Tools so as to mitigate such cases.
Firstly, we will provide the hands-on example of ‘’MADOUVALOS BROS SA’’ use case. We will use the DCSYM tool so as to construct the feasible systemic model of the company along with the communication and control flow that preside over its general operation. We will compare the current problematic situation with the potential one that may arise after some inventory management techniques will be conducted.
Secondly, we will use the VENSIM Simulation Software in order to describe another model put together by the interaction of variables which directly affect the stock levels like productivity and distribution etc.
Lastly, we will run through the development and use of a suggested pilot -R application that processes time-series data of orders and general transactions while is meant to forecast future demand of a product let alone the exact amount of stock needed to meet it.
Summarizing, this study provides, highly assisted by a mixture of data analytics tools, real-case analysis of optimal inventory management and general decision making.