Product-platform design and multi-period, multi-platform lot-sizing for hybrid manufacturing considering stochastic demand and processing time

被引：2

作者：

Sakib, Md Sadman ^{[1
]}

Osman, Hany ^{[1
]}

Azab, Ahmed ^{[1
]}

Baki, Fazle ^{[2
]}

机构：

[1] Univ Windsor, Dept Mech Automot & Mat Engn, Prod & Operat Management Res Lab, Fac Engn, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada

[2] Univ Windsor, Odette Sch Business, 401 Sunset Ave, Windsor, ON N9B 3P4, Canada

来源：

MANUFACTURING LETTERS | 2023年 / 35卷

关键词：

Product platform; Variety management; Stochastic demand; Safety-stock; MAKE-TO-ORDER; SAFETY STOCK; CONFIGURATION; SYSTEM; OPTIMIZATION;

D O I：

10.1016/j.mfglet.2023.07.011

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

In the era of mass customization, customer demand is fluctuating recurrently. To keep pace with this situation, the manufacturer wants to offer a bundle of products in a cost-effective way. The more variety of products is offered, the more fluctuation in demand is observed. Stochastic demand makes mass customization more challenging and expensive. The product platform concept is an effective and economical strategy for product variety management. This concept can help the manufacturer to deal with frequent updates of customer requirements. Moreover, using different platforms for different periods considering stochastic demand is more cost-efficient than having a single platform for all periods. Integrating hybrid (Additive and Subtractive) manufacturing and product platform concepts make it more adaptable for manufacturers. Since there are more variants, the processing time is different for each variant. The stochastic production environment makes the situation more complex. Thus, this study focuses on developing a mixed integer linear programming (MILP) model to minimize manufacturing and holding costs along with considering multi-period stochastic demand. The novelty of this model is to satisfy a certain service level by incorporating inventory and safety stock. An exact optimization solver, Gurobi, is used to find optimal solutions for the proposed model. Finally, a case study of a guiding bushes family is used as an illustrative example. (c) 2023 The Authors. Published by ELSEVIER Ltd.

引用

页码：20 / 27

页数：8

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