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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Main Authors: Srinivasan, Mandyam M., Viswanathan, S.
Other Authors: Nanyang Business School
Format: Article
Language:English
Published: 2013
Subjects:
Online Access:https://hdl.handle.net/10356/100803
http://hdl.handle.net/10220/18202
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1008032023-05-19T06:44:43Z Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems Srinivasan, Mandyam M. Viswanathan, S. Nanyang Business School DRNTU::Business::Operations management 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. Accepted version 2013-12-11T02:41:20Z 2019-12-06T20:28:35Z 2013-12-11T02:41:20Z 2019-12-06T20:28:35Z 2010 2010 Journal Article Srinivasan, M. M., & Viswanathan, S. (2010). Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems. IIE transactions, 42(6), 379-391. 0740-817X https://hdl.handle.net/10356/100803 http://hdl.handle.net/10220/18202 10.1080/07408170902761406 en IIE transactions © 2010 Taylor & Francis Group. This is the author created version of a work that has been peer reviewed and accepted for publication by IIE Transactions, Taylor & Francis. It incorporates referee’s comments but changes resulting from the publishing process, such as copyediting, structural formatting, may not be reflected in this document. The published version is available at: http://dx.doi.org/10.1080/07408170902761406. 12 p. application/pdf
institution Nanyang Technological University
building NTU Library
continent Asia
country Singapore
Singapore
content_provider NTU Library
collection DR-NTU
language English
topic DRNTU::Business::Operations management
spellingShingle DRNTU::Business::Operations management
Srinivasan, Mandyam M.
Viswanathan, S.
Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
description 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.
author2 Nanyang Business School
author_facet Nanyang Business School
Srinivasan, Mandyam M.
Viswanathan, S.
format Article
author Srinivasan, Mandyam M.
Viswanathan, S.
author_sort Srinivasan, Mandyam M.
title Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
title_short Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
title_full Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
title_fullStr Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
title_full_unstemmed Optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
title_sort optimal work-in-process inventory levels for high-variety, low-volume manufacturing systems
publishDate 2013
url https://hdl.handle.net/10356/100803
http://hdl.handle.net/10220/18202
_version_ 1770563569489805312