Stockout risk of production-inventory systems with compound Poisson demands

被引:16
|
作者
Chang, Jasmine [1 ]
Lu, Haibing [2 ]
Shi, Jim [3 ,4 ]
机构
[1] Rutgers State Univ, Rutgers Business Sch Newark & New Brunswick, Dept Supply Chain Management, Newark, NJ USA
[2] Santa Clara Univ, Dept Operat Management & Informat Syst, Santa Clara, CA 95053 USA
[3] Rutgers State Univ, Rutgers Business Sch Newark & New Brunswick, Newark, NJ 07102 USA
[4] New Jersey Inst Technol, Tuchman Sch Management, Newark, NJ 07102 USA
关键词
Pharmaceutical manufacturing; Drug shortage; Production-inventory systems; Continuous manufacturing; Continuous production; Stockout risk; Risk metrics; MODEL; COST; APPROXIMATIONS; PRIORITY; POLICIES; IMPACT;
D O I
10.1016/j.omega.2018.03.001
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
Production-inventory systems with continuous production or continuous manufacturing have been implemented in a variety of manufacturing contexts. Most recently, the Commissioner of the FDA has called on drug and biological product manufacturers to begin switching from batch manufacturing processes to continuous production. Motivated by prevailing applications and the emerging and promising landscape in the healthcare and pharmaceutical industries, this paper studies a continuous-review production inventory system with a constant production rate and compound Poisson demands, in which the cost of the system is assessed via inventory holding, stockout penalty and production costs. For any initial inventory, we derive a closed-form expression for the expected discounted cost function until stockout occurrence. We systemically quantify the stockout risk on four different dimensions (i.e., time, volume, frequency and percentage) and derive explicit expressions for each type of risk metric. The objective is to derive the production rate that minimizes the expected discounted system cost subject to a given risk tolerance level on stockouts. With the aid of the derived explicit forms of stockout risk and the cost function, we develop a computationally-efficient algorithm for the optimal solution. Extensive numerical studies are conducted to illustrate our results with rich insights. Numerically, we show that it is outrageously costly to reduce stockout risk, especially when this risk is relatively low; the value of risk is more sensitive to the stockout risk level if the demand distribution has a higher volatility. (C) 2018 Elsevier Ltd. All rights reserved.
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页码:181 / 198
页数:18
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