An approach for temporal myopia reduction in Heterarchical Control Architectures

Zambrano, Gabriel; Pach, Cyrille; Aissani, Nassima; Berger, Thierry; Trentesaux, Damien

doi:10.1109/isie.2011.5984424

Cited by 15 publications

(6 citation statements)

References 13 publications

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“…For this reason it is difficult to achieve long-term optimization and maintain the levels of performance often attributed to the more hierarchical architectures. Approaches to minimize the system's myopia would have to possibly involve a chain reaction of information exchange (Zambrano et al 2011;Rey et al 2013) which may be time consuming and computationally intensive.…”

Section: Classification Of Control Architecturesmentioning

confidence: 99%

BIOSOARM: a bio-inspired self-organising architecture for manufacturing cyber-physical shopfloors

et al. 2016

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Biological collective systems have been an important source of inspiration for the design of production systems, due to their intrinsic characteristics. In this sense, several high level engineering design principles have been distilled and proposed on a wide number of reference system architectures for production systems. However, the application of bio-inspired concepts is often lost due to design and implementation choices or are simply used as heuristic approaches that solve specific hard optimization problems. This paper proposes a bio-inspired reference architecture for production systems, focused on highly dynamic environments, denominated BIO-inspired Self-Organising Architecture for Manufacturing (BIOSOARM). BIOSOARM aims to strictly adhere to bio-inspired principles. For this purpose, both shopfloor components and product parts are individualized and extended into the virtual environment as fully decoupled autonomous entities, where they interact and cooperate towards the emergence of a self-organising behaviour that leads to the emergence of the necessary production flows. BIOSOARM therefore introduces a fundamentally novel approach to production that decouples the system’s operation from eventual changes, uncertainty or even critical failures, while simultaneously ensures the performance levels and simplifies the deployment and reconfiguration procedures. BIOSOARM was tested into both flow-line and “job shop”-like scenarios to prove its applicability, robustness and performance, both under normal and highly dynamic conditions

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Section: Classification Of Control Architecturesmentioning

confidence: 99%

BIOSOARM: a bio-inspired self-organising architecture for manufacturing cyber-physical shopfloors

et al. 2016

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“…In this respect, we identified two approaches according to the characteristics of the operating mode: constructive-based and characterised-based operating modes. The system with a constructive-based operating mode (Figure 2) evolves to a better configuration to respond to corresponding necessities (Yang et al 2008;Zambrano et al 2011). In fact, the system constructs the new operating mode in response to disruptive events.…”

Section: Literature Reviewmentioning

confidence: 99%

A switching mechanism framework for optimal coupling of predictive scheduling and reactive control in manufacturing hybrid control architectures

Jiménez

Bekrar

Trentesaux

et al. 2016

International Journal of Production Research

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Nowadays, manufacturing systems are seeking control architectures that offer efficient production performance and reactivity to disruptive events. Dynamic hybrid control architectures are a promising approach as they are not only able to switch dynamically between hierarchical, heterarchical and semi-heterarchical structures, they can also switch the level of coupling between predictive scheduling and reactive control techniques. However, few approaches address an efficient switching process in terms of structure and coupling. This paper presents a switching mechanism framework in dynamic hybrid control architectures, which exploits the advantages of hierarchical manufacturing scheduling systems and heterarchical manufacturing execution systems, and also mitigates the respective reactivity and optimality drawbacks. The main feature in this framework is that it monitors the system dynamics online and shifts between different operating modes to attain the most suitable production control strategy. The experiments were carried out in an emulation of a real manufacturing system to illustrate the benefits of including a switching mechanism in simulated scenarios. The results show that the switching mechanism improves response to disruptions in a global performance indicator as it permits to select the best alternative from several operating modes.

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“…One well-known limitation of ERP systems is the inability to handle the events at the lower level of production, and one wellknown ability of distributed control is its reactivity in such a context. One well-known limitation of distributed control is its temporal or spatial myopia (i.e., its lack of visibility in the future or in the data space), while one wellknown ability of ERP systems is their aptitude for optimizing long-term plans (Zambrano et al 2011). It would be interesting to integrate and articulate the two concepts: the upper decision level would be managed using an ERP system, bounding the decisions at the lower level but not explicitly, while the lower level would be managed in a distributed autonomous way, in which local reactive decisions at the MES level, bounded by the ERP system, would help to handle unexpected events with a long-term view.…”

Section: Open Systemsmentioning

confidence: 99%

Intelligent distributed production control

2011

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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.

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An approach for temporal myopia reduction in Heterarchical Control Architectures

Cited by 15 publications

References 13 publications

BIOSOARM: a bio-inspired self-organising architecture for manufacturing cyber-physical shopfloors

BIOSOARM: a bio-inspired self-organising architecture for manufacturing cyber-physical shopfloors

A switching mechanism framework for optimal coupling of predictive scheduling and reactive control in manufacturing hybrid control architectures

Intelligent distributed production control

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