By Topic

Optimization of preventive maintenance scheduling for semiconductor manufacturing systems: models and implementation

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Xiaodong Yao ; Inst. for Syst. Res., Maryland Univ., College Park, MD, USA ; Fu, M. ; Marcus, S.I. ; Fernandez-Gaucherand, E.

Preventive maintenance (PM) is a vital activity in semiconductor manufacturing. A good PM schedule can increase the availability of tools by trading off between the planned unproductive down time versus the risk of much costlier unscheduled down time due to tool failures. Cluster tools are highly integrated systems made up of several processing modules (chambers) mechanically linked together, which can perform a sequence of semiconductor manufacturing processes. We present a two-layer hierarchical modeling framework for addressing the PM optimization problem for cluster tools, i.e., a Markov decision process (MDP) model at the higher level, and a mixed linear programming (LP) model at the lower level. Production planning data such as WIP levels are incorporated in these models. The LP model is solved using optimization packages EasyModeler and OSL. A case study comparing the results with a reference schedule is conducted in the simulation environment AutoSched AP, and numerical results are reported

Published in:

Control Applications, 2001. (CCA '01). Proceedings of the 2001 IEEE International Conference on

Date of Conference:

2001