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Design for mass personalization (DFMP) aims at effectively and efficiently satisfying customers as individuals by offering personally unique products with positive user experience.
Anticipatory analytics, catalysts, and choices interact to allow mass personalization at scale.
It can also be seen as a typical case integrating the frontier techniques to enable mass personalization.
They, however, cannot fully reflect the product development process for mass personalization, and may cause inconsistency in implementing the existing methods into real cases.
Future technologies such as artificial intelligence, machine learning, and cognitive computing hold even more opportunities for revenue growth and strategic differentiation The goals are to achieve mass personalization at scale in an intention driven design.
In order to devise, build and control a self-organizing smart manufacturing system for certain modular product architecture to support mass personalization, it is essential to accurately predict quality and performance of the manufacturing processes among others.
Similar(41)
The advances in artificial intelligence will soon make mass-personalization a feasible goal for many marketers.
As such services proliferate, leading firms will use context to help deliver mass-personalization for their customers, enabling them to better differentiate themselves from their rivals.
(2011) "Value in Co-Created Content Production in Magazine Publishing Case Study of Co-Creationn in Three Scandinavian Magazine Brands". The World Conference on Mass Customization, Personalization, and Co-Creation: Bridging Mass Customization & Open Innovation.
To further enable self-expression, New Era also sells caps in myriad styles in an approach known as mass customization or personalization.
Towards that end, the issues discussed in this paper focus on challenges in the design and planning of manufacturing networks in a mass customization and personalization landscape.
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