JOURNAL ARTICLE
Optimized Economic Production Quantity Inventory Model with Weibull Decay, Dynamic Holding Cost Under Varied Demand Scenario and Demand Series Analysis.
Published In: Journal of Advanced Manufacturing Systems, 2025, v. 24, n. 1. P. 203 1 of 3
Database: Business Source Ultimate 2 of 3
Authored By: Nand, Atma 3 of 3
Abstract
This paper presents a sophisticated modification of the economic production quantity (EPQ) model. It incorporates Weibull-distributed progressive deterioration, dynamic holding costs, variable demand, and strong strategies for effectively handling shortages and backlogs. Targeting products that have a short-term expiration but can still be stored for a long time without significant deterioration, the model aims to increase production quantities while lowering overall variable expenses. The extended EPQ model utilizes Maclaurin series approximations to solve ordinary differential equations, effectively capturing the dynamics of inventory under three different demand patterns. The focus of this handle's situations when the demand for a product changes in a predictable manner over time and considers the likelihood of defective goods during the manufacturing process. This approach provides useful insights for optimizing inventory management and production planning in the manufacturing of goods that are used up or consumed. The usefulness of the model is confirmed in the study through the use of two illustrative instances. Additionally, sensitivity analysis is utilized to suggest potential areas for additional investigation. [ABSTRACT FROM AUTHOR]
Additional Information
- Source:Journal of Advanced Manufacturing Systems. 2025/03, Vol. 24, Issue 1, p203
- Document Type:Article
- Subject Area:Economics
- Publication Date:2025
- ISSN:0219-6867
- DOI:10.1142/S0219686725500106
- Accession Number:181864756
- Copyright Statement:Copyright of Journal of Advanced Manufacturing Systems is the property of World Scientific Publishing Company and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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