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A Computational Model for Determining Levels of Factors in Inventory Management Using Response Surface Methodology

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  • Chia-Nan Wang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan)

  • Thanh-Tuan Dang

    (Department of Industrial Engineering and Management, National Kaohsiung University of Science and Technology, Kaohsiung 80778, Taiwan
    Department of Logistics and Supply Chain Management, Hong Bang International University, Ho Chi Minh 72320, Vietnam)

  • Ngoc-Ai-Thy Nguyen

    (School of Manufacturing Systems and Mechanical Engineering, Sirindhorn International Institute of Technology, Thammasat University, Pathum Thani 12121, Thailand)

Abstract

Inventory management plays a critical role in balancing supply availability with customer requirements and significantly contributes to the performance of the whole supply chain. It involves many different features, such as controlling and managing purchases from suppliers to consumers, keeping safety stock, examining the amount of product for sale, and order fulfillment. This paper involves the development of computational modeling for the inventory control problem in Thailand. The problem focuses on determining levels of factors, which are order quantity, reorder point, target stock, and inventory review policy, using a heuristic approach. The objective is to determine the best levels of factors that are significantly affected by their responses to optimize them using the response surface methodology. Values of the quantity of backlog and the average inventory amount, as well as their corresponding total costs, are simulated using the Arena software to gain statistical power. Then, the Minitab-response surface methodology is used to find the feasible solutions of the responses, which consist of test power and sample size, full factorial design, and Box–Behnken design. For a numerical example, the computational model is tested with real data to show the efficacy of the model. The result suggests that the effects from the reorder point, target stock, and inventory review policy are significant to the minimum total cost if their levels are set appropriately. The managerial implications of this model’s results not only suggest the best levels of factors for a case study of the leading air compressor manufacturers in Thailand, but also provide a guideline for decision-makers to satisfy customer demand at the minimum possible total inventory cost. Therefore, this paper can be a useful reference for warehouse supervisors, managers, and policymakers to determine the best levels of factors to improve warehouse performance.

Suggested Citation

  • Chia-Nan Wang & Thanh-Tuan Dang & Ngoc-Ai-Thy Nguyen, 2020. "A Computational Model for Determining Levels of Factors in Inventory Management Using Response Surface Methodology," Mathematics, MDPI, vol. 8(8), pages 1-23, July.
    • Handle: RePEc:gam:jmathe:v:8:y:2020:i:8:p:1210-:d:387984
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    References listed on IDEAS

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    Cited by:

    1. Rahal, Imen, 2023. "Analyse de la gestion des stocks de produits périssables en utilisant le modèle EOQ en Tunisie [Analysis of stock management for perishable products using EOQ model in Tunisia]," MPRA Paper 118592, University Library of Munich, Germany.
    2. Ziquan Xiang & Jiaqi Yang & Muhammad Hamza Naseem & Wenjie Ge, 2022. "Research on Dynamic Cooperative Replenishment Optimization of Shipbuilding Enterprise Inventory Control under Uncertainty," Sustainability, MDPI, vol. 14(4), pages 1-15, February.
    3. Afonso Vaz de Oliveira & Carina M. Oliveira Pimentel & Radu Godina & João Carlos de Oliveira Matias & Susana M. Palavra Garrido, 2022. "Improvement of the Logistics Flows in the Receiving Process of a Warehouse," Logistics, MDPI, vol. 6(1), pages 1-23, March.
    4. Rahal, Imen, 2023. "Analyse de la gestion des stocks de produits périssables en utilisant le modèle EOQ en Tunisie Analysis of the management of stocks of perishable products using the EOQ model in Tunisia [Analysis o," MPRA Paper 118193, University Library of Munich, Germany.
    5. Mohammed Alnahhal & Bashir Salah & Rafiq Ahmad, 2022. "Increasing Throughput in Warehouses: The Effect of Storage Reallocation and the Location of Input/Output Station," Sustainability, MDPI, vol. 14(8), pages 1-16, April.

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