Nowadays, manufacturing control systems can respond more effectively to exigent market requirements and real-time demands. Indeed, they take advantage of changing their structural and behavioural arrangements to tailor the control solution from a diverse set of feasible configurations. However, the challenge of this approach is to determine efficient mechanisms that dynamically optimise the configuration between different architectures. This paper presents a dynamic hybrid control architecture that integrates a switching mechanism to control changes at both structural and behavioural level. The switching mechanism is based on a genetic algorithm and strives to find the most suitable operating mode of the architecture with regard to optimality and reactivity. The proposed approach was tested in a real flexible job shop to demonstrate the applicability and efficiency of including an optimisation algorithm in the switching process of a dynamic hybrid control architecture.

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Manufacturing systems, and specifically Flexible Manufacturing Systems (FMS), face the challenge of accomplish global optimal performance and reactiveness at dynamic manufacturing environments. For this reason, manufacturing control systems must incorporate mechanisms that support dynamic custom-build responses. This paper introduces a framework that includes a governance mechanism in control system architectures that dynamically steers the autonomy of decision-making between predictive and reactive approaches. Results from experiments led in simulation show that it is worth studying in depth a governance mechanism that tailors the structure and/or behaviour of a manufacturing control system and, at the same time, potentiate the reactivity required in manufacturing operations.

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Manufacturing systems face the challenge of accomplishing the productive effectiveness and sustainable efficiency goals at operational level. For this, manufacturing control systems must incorporate a mechanism that balances the trade-off between effectiveness and efficiency in perturbed scenarios. This paper proposes a framework of a dynamic hybrid control that manages and balances the trade-off between effectiveness and efficiency objectives. Our proposal integrates this trade-off in three different locations: the predictive-offline scheduling component, the reactive-online control component, and the switching mechanism that changes dynamic architecture. To show the contribution of our approach and the progress of our research, a case study dealing with energy-aware manufacturing control is presented.

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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