EconPapers    
Economics at your fingertips  
 

API-based two-dimensional dispatching decision-making approach for semiconductor wafer fabrication with operation due date–related objectives

You Li, Zhibin Jiang and Wenyou Jia

International Journal of Production Research, 2017, vol. 55, issue 1, 79-95

Abstract: This paper presents an adjacent pairwise interchanges (API)-based two-dimensional dispatching decision-making approach for semiconductor wafer fabrication with operation due date-related objectives. Each time when a machine becomes idle, the proposed dispatcher chooses a target processing job from the competing jobs and assigns it a start time. Giving the operation due date information of each competing job, we formulate this dispatcher as the mean absolute deviation problem to keep the jobs finished around their operation due dates in a proactive way. Dominance properties of this problem are established using proof by APIs. Then, a heuristic comprised of job selection within candidate set, movement of job cluster and local search is designed to solve this problem more efficiently. Numerical experiments validate the efficiency of the proposed heuristic in a single-machine environment as well as in a simulated wafer fab abstracted from practice. In comparison with four most referenced due date-related dispatching rules, the simulation study reveals the benefits brought by the two-dimensional dispatching decision with different due date tightness taken into account.

Date: 2017
References: Add references at CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://hdl.handle.net/10.1080/00207543.2016.1195025 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:taf:tprsxx:v:55:y:2017:i:1:p:79-95

Ordering information: This journal article can be ordered from
http://www.tandfonline.com/pricing/journal/TPRS20

DOI: 10.1080/00207543.2016.1195025

Access Statistics for this article

International Journal of Production Research is currently edited by Professor A. Dolgui

More articles in International Journal of Production Research from Taylor & Francis Journals
Bibliographic data for series maintained by Chris Longhurst ().

 
Page updated 2025-03-20
Handle: RePEc:taf:tprsxx:v:55:y:2017:i:1:p:79-95