Inventory Risk Decision-Making Techniques Using Customer Behaviour Analysis

Authors

  • Ivan Marc University of Ljubljana, Faculty of Mechanical Engineering, Slovenia
  • Tomaž Berlec University of Ljubljana, Faculty of echanical Engineering, Slovenia

DOI:

https://doi.org/10.5545/sv-jme.2023.577

Keywords:

lean production, customer demand, risk simulation, inventory optimisation

Abstract

More recent research shows the significant impact of accurate demand forecasting on the operation of supply chain system and thus on the performance of the company. Inventories in the production process could represent waste, which results in higher storage costs and consequently a higher product price, which in turn reduces company's competitiveness on the market. Nevertheless, a company must implement a lean production process and consequently carefully control storage and inventory costs. The introduction of a lean production process is closely linked to the risk of stock-outs, and knowledge of this risk in relation to customer habits is therefore a useful piece of information for the line manager's decision-making. This paper will present a mathematical model that relates customer demand for a product to the inventory level in the warehouse or between the work operations of the production process and the risk of potential penalties that arises with the introduction of a lean production process. With this model we can simulate, how to improve the production processes with still acceptable risk, with the goal of achieving a balance between stocks and the leanness of the production process. The paper demonstrates the use of a mathematical model on a concrete example from practice for risk simulation when choosing different production scenarios resulting from changed customer behaviour.

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Published

2023-06-29

How to Cite

Marc, I., & Berlec, T. . (2023). Inventory Risk Decision-Making Techniques Using Customer Behaviour Analysis. Strojniški Vestnik - Journal of Mechanical Engineering, 69(7-8), 317–325. https://doi.org/10.5545/sv-jme.2023.577