By Topic

Finite automata decomposition for flexible manufacturing systems control and scheduling

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

3 Author(s)
Darabi, H. ; Dept. of'' Mech. & Ind. Eng., Illinois Univ., Chicago, IL, USA ; Jafari, M.A. ; Manapure, S.S.

Despite the efforts in scheduling and control of flexible manufacturing systems (FMSs) with resource constraints, the current pool of scheduling techniques faces two major drawbacks: modeling and complexity. Modeling is the task of converting the FMS data to a set of information, ready to be processed by a scheduling algorithm. Complexity has a direct relation with the amount of effort required to execute a scheduling algorithm successfully on the information set generated in the modeling phase. In this paper, we use finite automata (FA) theory to develop a modeling formalism and its accompanying scheduling algorithm for control and scheduling of FMS with resource constraints. While the FA-based modeling is completely automatic and does not need any human-designer interference, its related algorithm is both effective and efficient. We use IDEF3 standard to capture the FMS activities and resource data. We propose a three-step procedure. In the first step, the IDEF3 data set is converted to a finite automaton, preserving the activity precedence relationships. In the second step, the resulted finite automaton is decomposed to smaller (in size) scheduling problems that can be independently optimized. In the third step, a heuristic scheduling algorithm is used to handle each problem separately. We applied the developed procedure to 100 problems. The results are satisfactory and promising.

Published in:

Systems, Man, and Cybernetics, Part C: Applications and Reviews, IEEE Transactions on  (Volume:33 ,  Issue: 2 )