Re-Distributed Manufacturing and the Impact of Big Data: A Consumer Goods PerspectiveCitation formats

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Re-Distributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective. / Zaki, Mohamed; Theodoulidis, Babis; Shapira, Philip; Neely, Andy; Tepel, Matthias Friedrich .

In: Production Planning & Control, 15.05.2019.

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Zaki, Mohamed ; Theodoulidis, Babis ; Shapira, Philip ; Neely, Andy ; Tepel, Matthias Friedrich . / Re-Distributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective. In: Production Planning & Control. 2019.

Bibtex

@article{74aff9c6feae446dbe9e86c13650c118,
title = "Re-Distributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective",
abstract = "Digitalisation and the growth of big data promises more distributed and customised manufacturing. Yet, challenges arise in applying these new technologies in consumer goods industries that often emphasise mass production and extended supply chains. We build a conceptual framework to explore whether big data combined with new manufacturing technologies can facilitate redistributed manufacturing. Through analysis of 24 consumer goods industry cases using primary and secondary data, we investigate evolving manufacturing configurations, their underlying drivers, the role of big data applications, and their impact on the redistribution of manufacturing. We find some applications of redistributed manufacturing concepts, although in other cases existing manufacturing configurations are leveraged for high volume consumer goods products through big data analytics and market segmentation. The analysis indicates that the framework put forward in the paper has broader value in organising thinking about emerging interrelationships between big data and manufacturing. ",
keywords = "redistributed manufacturing, big data, digital manufacturing, personalisation, customisation, digital factory",
author = "Mohamed Zaki and Babis Theodoulidis and Philip Shapira and Andy Neely and Tepel, {Matthias Friedrich}",
year = "2019",
month = may,
day = "15",
doi = "10.1080/09537287.2018.1540068",
language = "English",
journal = "Production Planning and Control",
issn = "0953-7287",
publisher = "Taylor & Francis",

}

RIS

TY - JOUR

T1 - Re-Distributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective

AU - Zaki, Mohamed

AU - Theodoulidis, Babis

AU - Shapira, Philip

AU - Neely, Andy

AU - Tepel, Matthias Friedrich

PY - 2019/5/15

Y1 - 2019/5/15

N2 - Digitalisation and the growth of big data promises more distributed and customised manufacturing. Yet, challenges arise in applying these new technologies in consumer goods industries that often emphasise mass production and extended supply chains. We build a conceptual framework to explore whether big data combined with new manufacturing technologies can facilitate redistributed manufacturing. Through analysis of 24 consumer goods industry cases using primary and secondary data, we investigate evolving manufacturing configurations, their underlying drivers, the role of big data applications, and their impact on the redistribution of manufacturing. We find some applications of redistributed manufacturing concepts, although in other cases existing manufacturing configurations are leveraged for high volume consumer goods products through big data analytics and market segmentation. The analysis indicates that the framework put forward in the paper has broader value in organising thinking about emerging interrelationships between big data and manufacturing.

AB - Digitalisation and the growth of big data promises more distributed and customised manufacturing. Yet, challenges arise in applying these new technologies in consumer goods industries that often emphasise mass production and extended supply chains. We build a conceptual framework to explore whether big data combined with new manufacturing technologies can facilitate redistributed manufacturing. Through analysis of 24 consumer goods industry cases using primary and secondary data, we investigate evolving manufacturing configurations, their underlying drivers, the role of big data applications, and their impact on the redistribution of manufacturing. We find some applications of redistributed manufacturing concepts, although in other cases existing manufacturing configurations are leveraged for high volume consumer goods products through big data analytics and market segmentation. The analysis indicates that the framework put forward in the paper has broader value in organising thinking about emerging interrelationships between big data and manufacturing.

KW - redistributed manufacturing

KW - big data

KW - digital manufacturing

KW - personalisation

KW - customisation

KW - digital factory

U2 - 10.1080/09537287.2018.1540068

DO - 10.1080/09537287.2018.1540068

M3 - Article

JO - Production Planning and Control

JF - Production Planning and Control

SN - 0953-7287

ER -