A Production–Inventory Model for a Push–Pull Manufacturing System with Capacity and Service Level Constraints

Feng Cheng*, Markus Ettl, Yingdong Lu and David D. Yao

Production and Operations Management, 2012, vol. 21, issue 4, 668-681

Abstract: We study a hybrid push–pull production system with a two‐stage manufacturing process, which builds and stocks tested components for just‐in‐time configuration of the final product when a specific customer order is received. The first production stage (fabrication) is a push process where parts are replenished, tested, and assembled into components according to product‐level build plans. The component inventory is kept in stock ready for the final assembly of the end products. The second production stage (fulfillment) is a pull‐based assemble‐to‐order process where the final assembly process is initiated when a customer order is received and no finished goods inventory is kept for end products. One important planning issue is to find the right trade‐off between capacity utilization and inventory cost reduction that strives to meet the quarter‐end peak demand. We present a nonlinear optimization model to minimize the total inventory cost subject to the service level constraints and the production capacity constraints. This results in a convex program with linear constraints. An efficient algorithm using decomposition is developed for solving the nonlinear optimization problem. Numerical results are presented to show the performance improvements achieved by the optimized solutions along with managerial insights provided.

Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

Downloads: (external link)
https://doi.org/10.1111/j.1937-5956.2011.01303.x

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:bla:popmgt:v:21:y:2012:i:4:p:668-681

Ordering information: This journal article can be ordered from
http://onlinelibrary ... 1111/(ISSN)1937-5956

Access Statistics for this article

Production and Operations Management is currently edited by Kalyan Singhal

More articles in Production and Operations Management from Production and Operations Management Society
Bibliographic data for series maintained by Wiley Content Delivery ().