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Configuring and visualizing the data resources in a cloud-based data collection framework

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

Details

Original languageEnglish
Title of host publication2017 International Conference on Engineering, Technology and Innovation
Subtitle of host publicationEngineering, Technology and Innovation Management Beyond 2020: New Challenges, New Approaches, ICE/ITMC 2017 - Proceedings
PublisherIEEE
Pages1201-1208
Number of pages8
ISBN (Electronic)9781538607749
DOIs
Publication statusPublished - 2 Feb 2018
Publication typeA4 Article in a conference publication
EventInternational Conference on Engineering, Technology and Innovation -
Duration: 1 Jan 1900 → …

Conference

ConferenceInternational Conference on Engineering, Technology and Innovation
Period1/01/00 → …

Abstract

The Manufacturing Enterprise Solutions Association (MESA) provided the abstract and general definition of the Manufacturing Execution Systems (MES). A dedicated function has been reserved for the data collection activities. In this matter, the Cloud Collaborative Manufacturing Networks (C2NET) project tends to provide a cloud based platform for hosting the interactions of the supply chain in a collaborative network. Within the architecture of the C2NET project, a Data Collection Framework (DCF) is designed to fulfill the function of data collection. This allows the companies to provide their data, which can be both enterprise and Internet of Things (IoT) devices type of data to the platform for further use. The collection of the data is achieved by a specific third party application, i.e., the Legacy System Hub (LSH). This research work presents the approach of configuring and visualizing the data resources in the C2NET platform. This approach employs the web-based applications and the help of the LSH. This permits the C2NET platform to adapt to any kind of third party application, which manipulates enterprise data, following the generic and flexible solution of this approach.

Keywords

  • Cloud Based, Data Collection, Data Resources, Supply Chain, Visualization

Publication forum classification

Field of science, Statistics Finland