Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems

This article considers a manufacturing system that operates in a high-variety, low-volume environment, with significant setup times. The goal is to determine the optimal Work-In-Process (WIP) inventory levels for operating the system to meet the required demand for each product. The decision variabl...

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Bibliographic Details
Published in:IIE transactions 2010-06, Vol.42 (6), p.379-391
Main Authors: Srinivasan, Mandyam M., Viswanathan, S.
Format: Article
Language:English
Subjects:
closed queueing networks
CONWIP
Heuristic
Integer programming
Inventories
Job shops
Mathematical analysis
Mathematical models
multiple chains
Networks
non-linear integer program
Nonlinear programming
Optimization
Pallets
Queuing theory
shop floor planning and control
Stockpiling
Studies
Work in process
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Summary:This article considers a manufacturing system that operates in a high-variety, low-volume environment, with significant setup times. The goal is to determine the optimal Work-In-Process (WIP) inventory levels for operating the system to meet the required demand for each product. The decision variables are the number of pallets (containers) for each product and the number of units in each pallet (lot size). The objective is to minimize the total WIP inventory across all products. To capture congestion in the system, it is modeled as a closed queueing network with multiple product types. However, this leads to a complex non-linear integer program with a non-convex objective function. A lower bound on the objective function is developed that is used to develop upper and lower bounds on the number of pallets for each product. The bounds on the number of pallets allow the use of exhaustive enumeration within these bounds to obtain the optimal solution to this complex queueing network-based optimization problem. A simple heuristic is developed to further reduce the number of candidate configurations evaluated in the search for the optimal solution. A computational study reveals that the heuristic obtains the optimal solution in many of the test instances. [Supplementary materials are available for this article. Go to the publisher's online edition of IIE Transactions for supplemental resources containing details on some procedures and heuristics.]
ISSN:0740-817X
2472-5854
1545-8830
2472-5862
DOI:10.1080/07408170902761406