Product intelligence in industrial control: Theory and practice

McFarlane, Duncan; Giannikas, Vaggelis; Wong, Alan C.-N.; Harrison, Mark

doi:10.1016/j.arcontrol.2013.03.003

Cited by 105 publications

(70 citation statements)

References 52 publications

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“…Cloud computing is one alternative for handling those large amounts of data. To a certain extent, the cloud effectively serves as the brain to improve decision-making and optimization for IoT-connected objects and interactions [27], although some of those decisions can be made locally (e.g., by the product itself) [19,17]. However, as stated previously, new challenges arise when IoT meets Cloud; e.g.…”

Section: Internet Of Things (Iot)mentioning

confidence: 97%

“…Within this context, a significant body of research emerged, particularly with the IMS (Intelligent Manufacturing System) community with worldwide membership, which is an industry-led, global, collaborative research and de-velopment program established to develop the next generation of manufacturing and processing technologies. The IMS philosophy adopts heterarchical and collaborative control as its information system architecture [23,19,17]. The behavior of the entire manufacturing system therefore becomes collaborative, determined by many interacting subsystems that may have their own independent interests, values, and modes of operation.…”

Section: Manufacturing Paradigms Through the Agesmentioning

confidence: 99%

See 1 more Smart Citation

Technological Theory of Cloud Manufacturing

Kubler

Holmström

Främling

et al. 2016

Service Orientation in Holonic and Multi-Agent Manufacturing

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Over the past decade, a flourishing number of concepts and architectural shifts appeared such as the Internet of Things, Industry 4.0, Big Data, 3D printing, etc. Such concepts are reshaping traditional manufacturing models, which become increasingly network-, service-and intelligent manufacturing-oriented. It sometimes becomes difficult to have a clear vision of how all those concepts are interwoven and what benefits they bring to the global picture (either from a service or business perspective). This paper traces the evolution of the manufacturing paradigms, highlighting the recent shift towards Cloud Manufacturing (CMfg), along with a taxonomy of the technological concepts and technologies underlying CMfg.

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Section: Internet Of Things (Iot)mentioning

confidence: 97%

Section: Manufacturing Paradigms Through the Agesmentioning

confidence: 99%

Technological Theory of Cloud Manufacturing

Kubler

Holmström

Främling

et al. 2016

Service Orientation in Holonic and Multi-Agent Manufacturing

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“…The concept of intelligent products is being studied by the research community in intelligent manufacturing field (a state of the art in the field can be found in (Meyer et al, 2009;McFarlane et al, 2013)). …”

Section: Intelligent Products: Concepts and Deployment Challengesmentioning

confidence: 99%

“…The concept of intelligent product (Meyer, Främling, & Holmströmc, 2009;McFarlane, Giannikas, Wong, & Harrison, 2013) is a new industrial manufacturing control paradigm, aligned with CPS. Intelligent products carry the knowledge about their characteristics, wirelessly connected to share, in real-time, information about their state or environment, or to communicate with other cooperative objects of the Internet of Things (IoT).…”

Section: Introductionmentioning

confidence: 99%

Intelligent products: The grace experience

Leitão

Rodrigues

Barbosa

et al. 2015

Control Engineering Practice

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a b s t r a c tProduct intelligence is a new industrial manufacturing control paradigm aligned with the context of cyber-physical systems and addressing the current requirements of flexibility, reconfigurability and responsiveness. This paradigm introduces benefits in terms of improvement of the entire product's lifecycle, and particularly the product quality and customization, aiming the customer satisfaction. This paper presents an implementation of a system of intelligent products, developed under the scope of the GRACE project, where an agent-based solution was deployed in a factory plant producing laundry washing machines. The achieved results show an increase of the production and energy efficiency, an increase of the product quality and customization, as well as a reduction of the scrap costs.

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“…The products processed by a PDS are considered as intelligent in the sense of [1], i.e "linked to information and rules governing the way [they are] intended to be made, stored or transported and capable to support or influence these operations" (for more information about intelligent products, the reader is advised to read the comprehensive review made by [2]). Products can thus make real-time decision in unexpected situations according to production status.…”

Section: Introductionmentioning

confidence: 99%

Application of Measurement-Based AHP to Product-Driven System Control

Derigent¹,

Voisin²,

Thomas³

et al. 2017

Studies in Computational Intelligence

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Abstract. This paper presents an application of the measurements-based AHP to define a two-stage algorithm for product-driven systems control, in case of an unexpected event. This algorithm is made of two stages: the first one aims to define which kind of strategy the product should adopt (wait¸ react by it self or switch back to centralized mode) while the second one helps to choose the most appropriate resource able to fulfill the product requirements. The methodology is detailed on a simple case study.

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Product intelligence in industrial control: Theory and practice

Cited by 105 publications

References 52 publications

Technological Theory of Cloud Manufacturing

Technological Theory of Cloud Manufacturing

Intelligent products: The grace experience

Application of Measurement-Based AHP to Product-Driven System Control

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