A reference architecture for the development of socio-cyber-physical condition monitoring systems

Fleischmann, Hans; Kohl, Johannes; Franke, Jörg

doi:10.1109/sysose.2016.7542963

Cited by 19 publications

(7 citation statements)

References 14 publications

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“…Room to improve with a larger data set Information Dai et al [12] Case study of RFID real-time tracking in a shop floor n/a n/a Eiskop et al [14] Production monitoring system architecture adapted for SME Needs to be tested in a manufacturing environment Architecture for machine condition monitoring to lower workers' cognitive overload n/a n/a Fleischmann et al [18] Architecture for socio-cyber-physical systems in machine condition monitoring n/a n/a…”

Section: Informationmentioning

confidence: 99%

Business Intelligence in Industry 4.0: State of the art and research opportunities

Bordeleau¹,

Mosconi²,

Santa-Eulalia³

2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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Data collection and analysis have been at the core of business intelligence (BI) for many years, but traditional BI must be adapted for the large volume of data coming from Industry 4.0 (I4.0) technologies. They generate large amounts of data that need to be processed and used in decision-making to generate value for the companies. Value generation of I4.0 through data analysis and integration into strategic and operational activities is still a new research topic. This study uses a systematic literature review with two objectives in mind: understanding value creation through BI in the context of I4.0 and identifying the main research contributions and gaps. Results show most studies focus on real-time applications and integration of voluminous and unstructured data. For business research, more is needed on business model transformation, methodologies to manage the technological implementation, and frameworks to guide human resources training.

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Section: Informationmentioning

confidence: 99%

Business Intelligence in Industry 4.0: State of the art and research opportunities

Bordeleau¹,

Mosconi²,

Santa-Eulalia³

2018

Proceedings of the Annual Hawaii International Conference on System Sciences

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“…Different contributions on the subject of providing information and data in combination with Industry 4.0 (I4.0) address terms such as machine-interpretable (Sinoara et al, 2018) (Fleischmann et al, 2016), machine-actionable (Nüttgens et al, 2009) or machine-readable (Studer et al, 1997) (Neururer et al, 2015). However, there are no clear definitions of these terms in practical or scientific articles.…”

Section: Procedures For the Transfer Of Standards Into Machine-actionamentioning

confidence: 99%

Procedure for the transfer of standards into machine-actionability

Loibl

Manoharan

Nagarajah

2020

JAMDSM

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The aim of this research is to establish clear concepts for working with standards (e.g. ISO) in the context of connected factory. When machines or other output devices need to communicate with each other, e.g., to autonomously perform processes in manufacturing processes, all the necessary information must be accessible to them. Today, however, the required information is documented in standards that are only available in PDF or even paper form. Thus, a prerequisite for using information from standards is that these are automatically provided in output devices. A deeper look leads to three levels of maturity for using standard information in output devices: machine-readable, machine-actionable and machine-interpretable. Starting from a clear definition of these terms an approach is developed to implement machine-actionable standards. It is assumed that not all standards are suitable for machine-actionability and therefore the first step is to classify the standards in order to identify the appropriate standards. The second step describes how information from standards can be modelled to be available in a machine-actionable form. The last step clarifies how the machine-actionable content must be provided afterwards so that they can be used in all output devices with less effort. This research work closes with the validation of the developed approach. possible to transform them into other objects. For example, diagrams can be transformed into tables.As shown in Fig. 4, to classify the objects into three categories, the following rules are used. If there is a large number of objects that have a high proportion of clear definable objects, they are assigned to formal; if they have a medium proportion, they are assigned to semi-formal, and if they have a low proportion, they are assigned to abstract.Definition abstract standard: Standards which are assigned to the class abstract consist mostly of objects which have a low uniqueness, e.g. texts. These are not further considered for machine-actionability. An example of this category is ISO 9001.Definition semi-formal standard: Semi-formal standards are standards that contain information in various forms of representation. They include not only textual components that describe states, output classifications or test procedures, but also information in formal description like tables with values or mathematical formulas. Or however descriptive/explanatory/definitive texts can be converted easily into if/then instructions. Then it is possible to transform semi-formal norms into formal norms.Definition formal standard: Formal standards can be classified as standards whose information has a high degree of clarity, such as formulas or tables with values. As an example, a standard for the description of component sizes (e.g. for flanges) can be mentioned. Formulas can also be used to determine dimensioning variables.

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“…The cyber-physical properties of mechatronic systems are intensively investigated now in different aspects. For instance, the problems of system architecture [25][26][27], constraints caused by cyber-physical environment [28], efficient technological processes [29,30], relevant methods of software design and modelling [31,32] can be mentioned in this regard. More specific solutions for renewable energy production and environmental systems also received recently attention within the framework of new control design concepts as "Glocal" framework for hierarchical multi-agent networked dynamical systems [33][34][35].…”

Section: ) Cyber-physical Frameworkmentioning

confidence: 99%

Interdisciplinary design methodology for systems of mechatronic systems focus on highly dynamic environmental applications

Ivanov

Ruderman

Schiffer

et al. 2017

IECON 2017 - 43rd Annual Conference of the IEEE Industrial Electronics Society

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A reference architecture for the development of socio-cyber-physical condition monitoring systems

Cited by 19 publications

References 14 publications

Business Intelligence in Industry 4.0: State of the art and research opportunities

Business Intelligence in Industry 4.0: State of the art and research opportunities

Procedure for the transfer of standards into machine-actionability

Interdisciplinary design methodology for systems of mechatronic systems focus on highly dynamic environmental applications

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