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Redistributed Manufacturing and the Impact of Big Data: A Consumer Goods Perspective

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Zaki, MEH 
Theodoulidis, B 
Shapira, P 
Tepel, MF 


Digitalisation and the growth of big data promise greater customisation as well as change in how manufacturing is distributed. Yet, challenges arise in applying these new approaches 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.



redistributed manufacturing, big data, digital manufacturing, personalisation, customisation, digital factory

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Production Planning and Control

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Taylor & Francis
The work was supported by the Engineering and Physical Sciences Research Council (EPSRC) and the Economic and Social Research Council (ESRC) through The Network in Consumer Goods, Big Data and Re-Distributed Manufacturing (RECODE) hosted at Cranfield University under grant number EP/M017567/1.