Production planning in dynamic cellular manufacturing system using optimization of cell reconfiguration planning time horizon with uncertain demand

Wanyu Li*, Leyi Hu, Tomohiro Murata

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contribution

4 Citations (Scopus)

Abstract

This paper presents a mathematical model for solving a production planning (PP) problem in dynamic cell manufacturing system (DCMS) with uncertain demand. One of the characteristics of the DCMS is the reconfiguration, which is the number of machines in each manufacturing cell is allowed to change over a particular planning horizon. Consequently, the DCMS is more flexible, but complicated in determining an optimal solution, especially with the uncertain demand that confuses the accuracy of the optimization in traditional way. Therefore optimal planning time horizon is introduced as a distinguishing decision variable to handle the penalty from the uncertainty of the demand. The developed model is mixed integer non-linear equations. Numerical example is presented to show the performance of the method, where traditional DCMSs PP is employed for comparison. Improvement rate map has been drawn to illustrate the benefit zone for new method.

Original languageEnglish
Title of host publication2011 IEEE International Conference on Automation and Logistics, ICAL 2011
Pages466-470
Number of pages5
DOIs
Publication statusPublished - 2011 Oct 13
Event2011 IEEE International Conference on Automation and Logistics, ICAL 2011 - Chongqing, China
Duration: 2011 Aug 152011 Aug 16

Publication series

NameIEEE International Conference on Automation and Logistics, ICAL
ISSN (Print)2161-8151

Conference

Conference2011 IEEE International Conference on Automation and Logistics, ICAL 2011
Country/TerritoryChina
CityChongqing
Period11/8/1511/8/16

Keywords

  • Cell manufacturing system
  • Dynamic cell reconfiguration
  • Optimal planning time horizon
  • Production planning
  • Uncertain demand

ASJC Scopus subject areas

  • Control and Systems Engineering

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