Applying fuzzy logic in selecting press machine for scheduling n-jobs on a single machine

Maulidya, R, Saraswati, D, Lydia, R and Jie, F 2011, 'Applying fuzzy logic in selecting press machine for scheduling n-jobs on a single machine', in Professor Stuart Orr (ed.) 9th ANZAM Operations, Supply Chain and Services Management Symposium, Geelong, Australia, 15-17 June 2011, pp. 85-94.


Document type: Conference Paper
Collection: Conference Papers

Title Applying fuzzy logic in selecting press machine for scheduling n-jobs on a single machine
Author(s) Maulidya, R
Saraswati, D
Lydia, R
Jie, F
Year 2011
Conference name 9th ANZAM Operations, Supply Chain and Services Management Symposium
Conference location Geelong, Australia
Conference dates 15-17 June 2011
Proceedings title 9th ANZAM Operations, Supply Chain and Services Management Symposium
Editor(s) Professor Stuart Orr
Publisher Deakin University and ANZAM
Place of publication Geelong, Australia
Start page 85
End page 94
Total pages 10
Abstract This paper deals with scheduling n-jobs on a single machine. The problem is to determine which machine will be used based on the job characteristics. Since each job has different characteristic according to the customer requirement, the floor shop facing difficulties in selecting the press machine as per requirement. Two steps solution are proposed, first step using fuzzy logic to determine which machine to be used, and the second step to make scheduling n-jobs on selected single press machine following the priority rules EDD (earliest due-date) or SPT (shortest processing time). The fuzzy variables to be considered are speed and pressing capacity of the press machine, while for the non-fuzzy variables are slide, bolster and dies height. The computational experiment is based on 91 jobs with 8 unit press machines supported by software Borland Delphi.
Subjects Logistics and Supply Chain Management
Manufacturing Management
Keyword(s) fuzzy logic
fire strength
job-shop
earliest due-date
shortest processing time
Copyright notice © Deakin Graduate School of Business
ISBN 9781741561616
Versions
Version Filter Type
Access Statistics: 195 Abstract Views  -  Detailed Statistics
Created: Wed, 17 Jul 2013, 15:02:00 EST by Catalyst Administrator
© 2014 RMIT Research Repository • Powered by Fez SoftwareContact us