Inventory Modeling: A Five Step Approach
D Thamaraiselvi1, Shanmukha Sai Ganesh Sripada2, Pisupati Srinivasa Pranav3
1Dr. D Thamaraiselvi, Assistant Professor, Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India.
2Shanmukha Sai Ganesh Sripada*, B.E Student, Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India.
3Pisupati Srinivasa Pranav, B.E Student, Department of Computer Science and Engineering, Sri Chandrasekharendra Saraswathi Viswa Mahavidyalaya, Kanchipuram, India.
Manuscript received on February 27, 2022. | Revised Manuscript received on March 07, 2022. | Manuscript published on March 30, 2022. | PP: 45-48 | Volume-11, Issue-4, March 2022 | Retrieval Number: 100.1/ijitee.C98020311422 | DOI: 10.35940/ijitee.C9802.0311422
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: Inventory is the array of finished goods, spares, raw materials, and other substances required in the production of the finished goods and it is a major asset to a typical manufacturing company. When utilized properly, it can yield great profits for an organization and when not managed in an optimized way, it can incur big losses. There are various methods for inventory control, some of them being JIT (just in time inventory), cross-docking, and cycle counting. But these methods never yielded dividends to companies in getting control over their inventories. Therefore the need for proper inventory models to help maintain optimal stock keeping in mind the specific constraints of each company/organization is essential, say the least. This paper presents a generic version of an inventory model for raw materials, finished goods, and spares in a stock-keeping unit (SKU) where the overall stock is considered as a dependent variable and it is expressed as a function of various parameters or independent variables such as seasonality, demand and lead times ( to name a few). The model allows the prediction of inventory levels of raw materials, finished goods, and spare parts of the machinery with a very high degree of accuracy and can subject the predictive model to various sensitivity and scenario analyses thus being able to gauge the opportunities and risks involved. As a result, there will be all-around improvements in vendor performance, procurement of raw material, handling the finished goods, and spare stocks resulting in an optimized environment in the inventory.
Keywords: Demand Forecasting, Inventory Coverage Ratio, Inventory Modeling, Predictive Modeling
Scope of the Article: Predictive Analysis