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Mass Customization Monday #6

Yet another edition of Mass Customization Monday where the Twikit team sifts through all the mass customization news and selects the relevant stories for you.

Unique glasses from GlassYourself

GlassYourself is a French startup that is offering unique 3D printed and laser cut sunglasses. Hoet and other companies are already making 3D printed glasses and this application seems like a potentially huge one for digital manufacturing and mass customization. Everyone has a unique face. Glasses can be much more comfortable if the bridge and the arms are mass customized just for you. Glasses are also a high value item and a fashion item as well. The personalization could be an additional story for the consumer as well as increasing their comfort.

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GlassYourself can make very outlandish glasses.

GlassYourself uses selective laser sintering to make polyamide (Nylon) glasses. The customer will have to wait a month to get their custom fit glasses which are fitted by an optician. You can add text to the glasses and choose your own colors as well. The glasses cost around $260.

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Commercially however the team has more prosaic offerings available.

It is too early to tell who will become a winner in mass customized glasses. Materialise Luxura, Luxexcell and others are playing in this field. In our opinion it will not take long for industry mayors such as Luxottica and Safilo to make an entrance with customized glasses of their own. The key would seem to be who cracks a fool proof, easy to use way to let people at home use their phone or computers to get accurate facial information. If the phone could 3D scan well for example than people could give the mass customization input from their homes. This would make such a market much more acessible and potentially disruptive. Alternatively, mass customized glasses could remain something that you do in store or with an optician. This would make it a more luxurous but less convenient experience.

 

Machine Learning Algorithms could optimize your supply chain

One of the most difficult things to do in mass customization is to plan and optimize your supply chain. SAP has a new product SAP Clea. This integrates with the SAP Business Planning suite and uses machine learning algorithms to optimize prediction and analysis of supply chains. SAP says that SAP Clea, “takes supply chains past predictive analytics to give organizations access to software that over time learns how to optimize the supply chain. Armed with that capability,…, organizations can then segment supply chains to drive additional business opportunities in the most efficient way possible.” Machine learning and AI stand to make significant gains in manufacturing environments and in the optimization of production. By giving quicker and more accurate analysis of supply chains and learning on how to improve that analysis; machine learning algorithms could have impacts on a company’s product mix and business planning. Deeper and more thorough analysis of what is actually going on in your supply chains may be a way for companies to find considerable savings. It is difficult to tell at the moment which other areas machine learning will impact. “Intelligent” software could emerge to be the central tool by which companies take decisions however if they are properly implemented.

Using the iPhone to collect patient data

Everyone has a smartphone nowadays. These devices are great for connecting people and harvesting data. A series of studies at Mount Sinai Hospital’s Icahn School of Medicine in New York used smartphones to collect data from 2300 asthma patients. The study found that surveys filled in by the patients, correlated with existing research but at the same time there were some differences because things such as symptoms were self reported. The team said that, “Looking forward, the potential of ubiquitous smartphone technology to address the needs of clinical research to better understand health and disease appears to be more promising than ever.” Wide scale iphone based medical research and surveys could contribute significantly to our understanding of disease. It is also easy to see that apps, smartphones and other wearables can be used to collect patient data at an unprecedented scale. If we look at a future where many new treatments are emerging in personalized medicine such self reported and “phone reported” data may be instrumental at delivering unique patient profiles and information to doctors. Personalized and mass customized treatments could be deployed through smartphones at low cost. Would you trust your iPhone with your medical history?

PSFK looks at how customization shapes the beauty industry

A PSFK report looks at personalization in the beauty industry. Their Beauty Debrief looks at how brands can personalize in the beauty industry.

Some utilize genetic testing to create targeted products. Others have developed diagnostic testing solutions to identify skin properties and make tailored product and care recommendations. London-based skincare company Geneu, for example, has created a proprietary DNA test for customers that analyzes certain chemical and molecular properties of the skin in order to formulate two custom serums tailored to the results.

Personalization at this level removes the guesswork in selecting a beauty product by assuring customers that the product has been formulated or recommended uniquely for them. In turn, this translates to heightened trust of the brand and loyal relationships that are likely to bring future purchases.

The PSFK team refers to DNA based personalization as an “atomic personalization” for just one individual. Will genetic testing be a cornerstone of future beauty treatments? Will the enmeshing of beauty and science continue even further than this? The PSFK report recommends creating virtual and physical playgrounds which is exactly what Twikit is capable of doing. Evolving tools into assistants could also be a sea change for cosmetics companies. They also mention that consumers are to evolve into creators, which is also something we wholeheartedly support.

 

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