Schedule execution in autonomic manufacturing execution systems

Valckenaers, Paul; Brussel, Hendrik Van; Verstraete, Paul; Germain, Bart Saint; Hadeli,

doi:10.1016/j.jmsy.2007.12.003

Cited by 36 publications

(27 citation statements)

References 17 publications

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“…Furthermore, in the turbulent manufacturing environment, a key issue of modern manufacturing execution systems is that they cannot plan ahead of time. This phenomenon is named decision myopia and causes undoubtedly significant malfunctions in manufacturing [143]. In the field of layout design and material simulation, some commercial software can represent decoupling data from 3D model and export them in XML or HTML format.…”

Section: Challenges For the Manufacturing Network Life Cyclementioning

confidence: 99%

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Mourtzis

2016

Logist. Res.

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Manufacturers and service providers are called to design, plan, and operate globalised manufacturing networks, addressing to challenges of increasing complexity in all aspects of product and production life cycle. These factors, caused primarily by the increasing demand for product variety and shortened life cycles, generate a number of issues related to the life cycle of manufacturing systems and networks. Focusing on the aspects that affect manufacturing network performance, this work reviews the exiting literature around the design, planning, and control of manufacturing networks in the era of mass customisation and personalisation. The considered life cycle aspects include supplier selection, initial manufacturing network design, supply chain coordination, complexity, logistics management, inventory and capacity planning and management, lot sizing, enterprise resource planning, customer relationship management, and supply chain control. Based on this review and in correlation with the view of the manufacturing networks and facilities of the future, directions for the development of methods and tools to satisfy product-service customisation and personalisation are promoted.

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Section: Challenges For the Manufacturing Network Life Cyclementioning

confidence: 99%

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Mourtzis

2016

Logist. Res.

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“…The authors use pheromone dissemination of stigmergy technology to guide an adequate elements formation after switching. Other examples of bio-inspired mechanisms, namely PROSA and D-MAS, use virtual ants to explore the intentions of future behaviour and guide decisional entities through the decision-making process (Valckenaers et al 2007;Holvoet, Weyns, and Valckenaers 2009;Novas et al 2013). The degree of optimality of bio-inspired approaches is towards-optimal as, while they do not guarantee an optimal solution, they attempt to obtain the best result in a specific metric.…”

Section: Switching Mechanism In D-hcamentioning

confidence: 99%

Pollux: a dynamic hybrid control architecture for flexible job shop systems

Jiménez

Bekrar

Zambrano-Rey

et al. 2016

International Journal of Production Research

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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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“…In the first approach, agents trigger switching locally (local detection in Figure 2). The agents initiate a heterarchical-based solution due to their inability to execute their own objectives (Valckenaers et al 2007;Novas et al 2013;Herrera, Thomas, and Parada 2014). The advantage of this solution is that in cases where perturbations cause degradation in efficiency (not disruptions caused by breakdowns), the distributed entities might only require minor architectural changes and might recover autonomously.…”

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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Schedule execution in autonomic manufacturing execution systems

Cited by 36 publications

References 17 publications

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Challenges and future perspectives for the life cycle of manufacturing networks in the mass customisation era

Pollux: a dynamic hybrid control architecture for flexible job shop systems

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

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