Most retailers and manufacturers are poised to produce items and products in either large or small batches. There’s generally no in between, and it’s difficult –and costly –to swap seamlessly between the two production levels. With 3D printing, however, that’s no longer the case. Small-batch production can help reduce inventory waste, and levels can be scaled down –or up –accordingly to account for demand.
Packaging and shipping will change completely, too. We still use a lot of cardboard boxes and parcels these days, which admittedly are not that durable, especially when you’re shipping something particularly fragile. Thanks to 3D printing, companies can now print packaging materials and containers out of plastic and other materials.
But what about conventional retail ? Are we going to talk about brick-and-mortar stores ? Example ? How will 3D printing factor into that world ?
Imagine walking into a store, choosing an item or product you want from a machine, and getting it in minutes or hours. The item will be custom-made, to your specifications and preferences, in a reasonable amount of time.
That may sound far-fetched, but it’s entirely possible, and it’s headed.
A few years ago the founders of Ministry of Supply where three MIT graduates and students. They asked themselves how to improve clothing.
To answer this question they didn’t study fashion. Instead they studied technology of the garments themselves, what they are made off and how they might be improved. They also addressed the issue of body temperature, creating clothes that allow you to get cooled down faster when it’s warm and keep warmer when it’s cold out. Today they have an online business very successful.
This is only a simple of what Technology can do for any Industry.
Conclusion: To be the first and not beyond the rest of the Enterprises.
Companies need to take this seriously.
Source : Forbes.
Artificial intelligence technologies have come a long way in the past 12 months, so it’s now time for the public sector to take a serious look at practical use cases. By starting small and experimenting with simple AI uses cases, the industry can take a careful, risk-managed approach to implementing the technology more widely in future.
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