One computational innovation transition-based recovery policy for flexible manufacturing systems using Petri nets

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Abstract

In the third and fourth industrial revolutions, smart or artificial intelligence flexible manufacturing systems (FMS) seem to be the key machine equipment for capacity of factory production. However, deadlocks could hence appear due to resources competition between robots. Therefore, how to prevent deadlocks of FMS occurring is a very important and hot issue. Based on Petri nets (PN) theory, in existing literature almost all research adopts control places as their deadlock prevention mean. However, under this strategy the real optimal reachable markings are not achieved even if they claimed that their control policy is maximally permissive. Accordingly, in this paper, the author propose one novel transition-based control policy to solve the deadlock problem of FMS. The proposed control policy could also be viewed as deadlock recovery since it can recover all initial deadlock and quasi-deadlock markings. Furthermore, control transitions can be calculated and obtained once the proposed three-dimension matrix, called generating and comparing aiding matrix (GCAM) in this paper, is built. Finally, an iteration method is used until all deadlock markings become live ones. Experimental results reveal that our control policy seems still the best one among all existing methods in the literature regardless of whether these methods belong to places or transitions based.

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APA

Pan, Y. L. (2020). One computational innovation transition-based recovery policy for flexible manufacturing systems using Petri nets. Applied Sciences (Switzerland), 10(7). https://doi.org/10.3390/app10072332

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