Intelligent distributed production control

Abstract

This editorial introduces the special issue of the Springer journal, Journal of Intelligent Manufacturing, on intelligent distributed production control. This special issue contains selected papers presented at the 13th IFAC Symposium on Information Control Problems in Manufacturing-INCOM'2009 (Bakhtadze and Dolgui 2009). The papers in this special issue were selected because of their high quality and their specific way of addressing the variety of issues dealing with intelligent distributed production control. Previous global discussions about the state of the art in intelligent distributed production control are provided, as well as exploratory guidelines for future research in this area.

A Petri net model for constraint satisfaction application in holonic systems

“…5), then the other robot cannot place a part on the same column. For example, if robot R1 plans to place a part in the position with coordinates (2, 2), then robot R2 cannot place a part in (1,2). The predicate associated to this constraint is (all the previously introduced constraints are kept, too): P_Collision 1 ( (*, (2, i), k), (*, (1, j), k) ) = TRUE iff i ≠ j where the first predicate argument regards the choice of robot R1, and the second is for robot R2.…”

“…The distributed approach is the single possibility to handle the present complexity of manufacturing control systems and to satisfy requirements on adaptability and flexibility [1,2]. Besides this, nowadays schemes based on artificial intelligence methods are increasingly often taken into account.…”

A Model for Manufacturing Scheduling Optimization Through Learning Intelligent Products

“…Recently, some research works [3,[5][6][7] present IP as a solution to bring the required reactivity. Providing a complete survey on the topic of active/intelligent product is beyond the scope of this paper, but the interested reader can refer to the surveys [3,5].…”

Reducing myopic behavior in FMS control: A semi-heterarchical simulation–optimization approach

“…Since there is no central control element, these systems can be highly unpredictable and non-expected emergent behaviors can appeared, including chaotic behavior (Hogg and Huberman, 1991;Thomas et al, 2012). In addition to that, incomplete information make difficult to ensure that local decisions are globally coherent, thus it is hard to guarantee a minimum level of performance (Duffie and Prabhu, 1994).…”