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...
Saved in:
Main Authors: | , |
---|---|
Other Authors: | |
Format: | Article |
Language: | English |
Published: |
2013
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/100803 http://hdl.handle.net/10220/18202 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-100803 |
---|---|
record_format |
dspace |
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 |