Data Analytics in Manufacturing

M. Sami Sivri; Basar Oztaysi

doi:10.1007/978-3-319-57870-5_9

Data Analytics in Manufacturing

M. Sami Sivri^*, Basar Oztaysi

^*Corresponding author for this work

Department of Industrial Engineering

Istanbul Technical University

Research output: Chapter in Book/Report/Conference proceeding › Chapter › peer-review

10 Citations (Scopus)

Abstract

Development of technology has emerged a new concept, Industry 4.0. It has come with two technological improvements, Cyber-Physical System (CPS) and Internet of Things (IoT) that drive manufacturing companies to Data Analytics by generating the huge amount data. In terms of Industry 4.0, data analytics focus on “what will happen” rather than “what has happened”. These problems are entitled as predictive analytics and aims at building models for forecasting future possibilities or unknown events. The aim of this paper is to give insight about these techniques, provide applications from the literature and show a real world case study from a manufacturing company.

Original language	English
Title of host publication	Springer Series in Advanced Manufacturing
Publisher	Springer Nature
Pages	155-172
Number of pages	18
DOIs	https://doi.org/10.1007/978-3-319-57870-5_9
Publication status	Published - 2018

Publication series

Name	Springer Series in Advanced Manufacturing
ISSN (Print)	1860-5168
ISSN (Electronic)	2196-1735

Bibliographical note

Publisher Copyright:
© 2018, Springer International Publishing Switzerland.

Funding

Acknowledgements This work is supported by Scientific and Technological Research Council of Turkey (TUBİTAK), TEYDEB 1507, Grant No: 7141451.

Funders	Funder number
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	7141451

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1007/978-3-319-57870-5_9

Cite this

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AU - Oztaysi, Basar

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Data Analytics in Manufacturing

Abstract

Publication series

Bibliographical note

Funding

UN SDGs

Access to Document

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