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

^*Bu çalışma için yazışmadan sorumlu yazar

Endüstri Mühendisliği Bölümü

Istanbul Technical University

Araştırma sonucu: Kitap/Rapor/Konferans Bildirisinde Bölüm › Bölüm › bilirkişi

11 Atıf (Scopus)

Özet

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.

Orijinal dil	İngilizce
Ana bilgisayar yayını başlığı	Springer Series in Advanced Manufacturing
Yayınlayan	Springer Nature
Sayfalar	155-172
Sayfa sayısı	18
DOI'lar	https://doi.org/10.1007/978-3-319-57870-5_9
Yayın durumu	Yayınlandı - 2018

Yayın serisi

Adı	Springer Series in Advanced Manufacturing
ISSN (Basılı)	1860-5168
ISSN (Elektronik)	2196-1735

Bibliyografik not

Publisher Copyright:
© 2018, Springer International Publishing Switzerland.

Finansman

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

Finansörler	Finansör numarası
Türkiye Bilimsel ve Teknolojik Araştırma Kurumu	7141451

BM SKH

Bu sonuç, aşağıdaki Sürdürülebilir Kalkınma Hedefine/Hedeflerine katkıda bulunur

SKH 9 Sanayi, Yenilikçilik ve Altyapı

Belgeye Erişim

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

Diğer Dosyalar ve Linkler

Link to publication in Scopus

Alıntı Yap

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title = "Data Analytics in Manufacturing",

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.",

author = "\{Sami Sivri\}, M. and Basar Oztaysi",

note = "Publisher Copyright: {\textcopyright} 2018, Springer International Publishing Switzerland.",

year = "2018",

doi = "10.1007/978-3-319-57870-5\_9",

language = "English",

series = "Springer Series in Advanced Manufacturing",

publisher = "Springer Nature",

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AU - Sami Sivri, M.

AU - Oztaysi, Basar

PY - 2018

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AB - 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.

UR - https://www.scopus.com/pages/publications/85151548072

U2 - 10.1007/978-3-319-57870-5_9

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

M3 - Chapter

AN - SCOPUS:85151548072

T3 - Springer Series in Advanced Manufacturing

SP - 155

EP - 172

BT - Springer Series in Advanced Manufacturing

PB - Springer Nature

ER -

Data Analytics in Manufacturing

Özet

Yayın serisi

Bibliyografik not

Finansman

BM SKH

Belgeye Erişim

Diğer Dosyalar ve Linkler

Parmak izi

Alıntı Yap