Next Article in Journal / Special Issue
Reimaging Research Methodology as Data Science
Previous Article in Journal
The Internet and the Anti-Vaccine Movement: Tracking the 2017 EU Measles Outbreak
Article Menu
Issue 1 (March) cover image

Export Article

Open AccessArticle
Big Data Cogn. Comput. 2018, 2(1), 3; https://doi.org/10.3390/bdcc2010003

Big Data Processing and Analytics Platform Architecture for Process Industry Factories

Department of Cybernetics and Artificial Intelligence, Technical University Kosice, Letna 9, 04001 Kosice, Slovakia
*
Author to whom correspondence should be addressed.
Received: 26 November 2017 / Revised: 13 January 2018 / Accepted: 23 January 2018 / Published: 26 January 2018
(This article belongs to the Special Issue Big Data Analytic: From Accuracy to Interpretability)
View Full-Text   |   Download PDF [1111 KB, uploaded 26 January 2018]   |  

Abstract

This paper describes the architecture of a cross-sectorial Big Data platform for the process industry domain. The main objective was to design a scalable analytical platform that will support the collection, storage and processing of data from multiple industry domains. Such a platform should be able to connect to the existing environment in the plant and use the data gathered to build predictive functions to optimize the production processes. The analytical platform will contain a development environment with which to build these functions, and a simulation environment to evaluate the models. The platform will be shared among multiple sites from different industry sectors. Cross-sectorial sharing will enable the transfer of knowledge across different domains. During the development, we adopted a user-centered approach to gather requirements from different stakeholders which were used to design architectural models from different viewpoints, from contextual to deployment. The deployed architecture was tested in two process industry domains, one from the aluminium production and the other from the plastic molding industry. View Full-Text
Keywords: Big Data analytics; Big Data architecture; process industries; predictive data analysis Big Data analytics; Big Data architecture; process industries; predictive data analysis
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).
SciFeed

Share & Cite This Article

MDPI and ACS Style

Sarnovsky, M.; Bednar, P.; Smatana, M. Big Data Processing and Analytics Platform Architecture for Process Industry Factories. Big Data Cogn. Comput. 2018, 2, 3.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Big Data Cogn. Comput. EISSN 2504-2289 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top