A simulation-based model for determining safety inventory at a fixed-time period system

• Main Authors: Kien, L. T. T., Ma'aram, A., Hassan, S. A. H. S., Ngadiman, N. H. A., Kadir, A. Z. A.
• Format: Article
• Language: English
• Published: Blue Eyes Intelligence Engineering and Sciences Publication 2019
• Subjects: TJ Mechanical engineering and machinery
• Online Access: http://eprints.utm.my/id/eprint/90496/1/AzanizawatiMaaram2019_ASimulationBasedModel.pdf; http://eprints.utm.my/id/eprint/90496/; http://dx.doi.org/10.35940/ijitee.L2566.1081219
• Institution: Universiti Teknologi Malaysia

This paper develops a simulation model for determining safety inventory associated with a certain value of cycle service level in a fixed-time period system. The model takes into account actual amount of materials received from suppliers, and deviation from probability distribution of daily forecast demand. Constraints on order size are also embodied into the model. This model was constructed by using Visual Basic Application added in Microsoft Excel. After developing the model, hypotheses testing is employed to verify the model. This model allows identifying safety inventory under uncertain conditions which prohibits from the use of ordinary mathematical formula. The model was locally verified. Stochastic variables including customer demand and supplier’s lead time are assumed to be normally distributed. Independent demand items are considered and backorders are not allowed. Under specific conditions, such as distributions of demand and lead time are normally distributed, and fixed-time period system is being used. This model allows materials planner promptly identifies safety inventory associated with a certain level of cycle service level. Furthermore, planner can perceive the affects of changing input parameters on the amount of safety inventory required. There were very few researches focus on variations of demand and lead time at the same time. In reality, this case usually happens, thus the firms have been facing highly variations form both supplier and customers. Therefore, this paper intends to close this gap by simulating these factors and taken into account for determining safety inventory.