Joint cognitive system design and process control

Yurtseven, M. Kudret; Buchanan, Walter W.; Basak, Melek

doi:10.1109/picmet.2009.5261854

Cited by 1 publication

(2 citation statements)

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“…Whereas traditional approaches to system design lead to "human-machine systems" in which humans supervise and control machines through interfaces, in a Joint Cognitive System humans and machines share cognitive functions in a collaborative manner. This can be applied in both product design [7] and system design and control [58,36]. The relationship between JCS and the EAS project is briefly explored in [31].…”

Section: State Of the Artmentioning

confidence: 99%

“…The relationship between JCS and the EAS project is briefly explored in [31]. In particular, the algorithms presented in this paper, along with the general approach from EAS, address a number of considerations raised in JCS system design [58,31]: decentralisation, self-organisation/adaptation, goal-orientation, capacity for evolution (in that goals can be updated over time), and enabling the system design process to take into account the relevant capabilities and resources.…”

Section: State Of the Artmentioning

confidence: 99%

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Synthesising process controllers from formal models of transformable assembly systems

Silva¹,

Felli²,

Sanderson³

et al. 2019

Robotics and Computer-Integrated Manufacturing

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When producing complex and highly customisable products in low volumes (or in 'batch sizes of one'), automation of production systems is critical for competitiveness and profitability in high labour-cost economies. To facilitate batch-size-of-one production, 'topology generation', 'realisability', and 'control' algorithms have been developed as part of the Evolvable Assembly Systems (EAS) project. The topology generation algorithm computes all the possible sequences of parallel activities that assembly resources can perform on parts and is run offline whenever the layout of the production facility changes, whereas realisability checking and controller generation are performed at run-time to check whether a production facility with a given set of assembly resources can assemble a desired product, and how the product should be assembled, e.g., which resources to use, and when. Generated controllers are output in Business to Manufacturing Markup Language (B2MML). Taken together, the algorithms thus represent a step toward a complete path from the formal specification of an assembly system and the products to be assembled, to the automated synthesis of executable process plans. This paper presents each algorithm in sufficient detail to allow their reimplementation by other researchers. Topology generation is the most expensive step in the approach. A preliminary experimental evaluation of the scalability of topology generation is presented, which suggests that, for small to medium sized production facilities, the time required for recomputing the topology is sufficiently small not to preclude frequent factory transformations, e.g., the addition of new resources.

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Section: State Of the Artmentioning

confidence: 99%