No ratings yet.

3D printing has been one of the technologies that has had a major influence over the past years, for both businesses and consumers. Businesses have been able to use the printers for faster prototyping processes, and digital manufacturing, whereas consumers have been able to create products and tools in their own homes (Rayna & Striukova, 2016). This was made possible because 3D printers have been becoming increasingly cheaper, and thereby, accessible for everyone.

The faster prototype processes are useful for many companies, as different versions of products can be tested much faster. However, this particular use of 3D printing is limited in possibilities when looking at how it could change supply chains and business models in general. Digital manufacturing and 3D metal printers, on the other hand, still have major growth potential to change how current supply chains work.

The opportunities of metal printing

3D metal printers have a lot of potential to change how manufacturing currently works: they could make companies more efficient, and production less costly (Jordan, 2018; Nichols, 2020). Just like a regular 3D printer, metal printers are able to produce many different parts, which can be completely specific to what the user wants when they are needed. By doing so, bottlenecks for certain parts in the supply chain could be removed completely, and traditional manufacturing could become obsolete. Some firms have already started doing this. For example, Airbus has already has been printing tons of specific metal parts each month in-house since 2018, and metal printing has been providing solutions for specific microchips in the medical field (Jordan, 2018).

The constraints of metal printing

Although metal printing has the ability to change how supply chains currently work, some issues on it still have to be resolved. First, although regular 3D printers have been becoming cheaper (Rayna & Striukova, 2016), the same trend has not fully set through in metal printing yet. A small 3D metal printing machine can currently be purchased for $5000 dollars, which could still be useful for rare parts with high lead times (J., 2018), but won’t provide large-scale manufacturing solutions. Printers that are capable of doing that are priced closer to $100,000 dollars instead. The good news is that these prices have been declining steadily overtime.

Second, there are few people with the knowledge to utilize the possibilities of metal printers fully (Jordan, 2018).  The reason for this is that 3D metal printing in requires knowledge in engineering, computer science, and metallurgy among others. Such talented people are currently in short supply Companies that see the possibilities of metal printing would have to embrace the need for training in order to overcome this problem.

What do you think? Will companies be able to overcome the constraints of metal printing, and be able to use it as one of the main methods for manufacturing?

 

J., M. 2018. Iro3d lowers the cost of 3D metal printing with a $ 5,000 machine. 3dnatives. https://www.3dnatives.com/en/iro3d-lowers-cost-3d-metal-printing-machine-271120185/.

Jordan, J. 2018. 3D Printing: 101–124. MIT Press: Essential Knowledge series.

Nichols, T. 2020. Why David Irving Calls 3D Metal Printing A ‘Disruptive Technology’ For N.B. Manufacturing. https://huddle.today/why-david-irving-calls-3d-metal-printing-a-disruptive-technology-for-n-b-manufacturing/.

Rayna, T., & Striukova, L. 2016. From rapid prototyping to home fabrication: How 3D printing is changing business model innovation. Technological Forecasting and Social Change, 102: 214–224.

 

No ratings yet.

A smarter, more transparent, efficient, and sustainable supply chain: that’s what many supermarket chains have been dreaming of. However, this goal is something that is difficult to reach due to the complexity of food supply chains, where food waste, and bottlenecks are still major issues (IBM Food Trust, 2020; Parfitt et al., 2010). In fact, 50% of produced food is estimated to be lost when it moves from the farm to the consumer, due to issues such as inefficient harvesting, transportation, inventory problems, and packaging (Lundqvist et al., 2008). This shows that there is still major room and potential for improvement in food supply chains, and that is exactly what IBM is trying to solve with Food Trust.

Food Trust relies on blockchain in order to bring back transparency into the supply chain (IBM Food Trust, 2020). It does so through heavily encrypted ledgers, in which IBM’s customers can easily track different food items in their specific supply chains. The ledgers are continuously updated, and only accessible if a customer has the right permission. These permissions have been implemented to prevent one of blockchain’s greatest criticisms: the ability for other individuals to put in fraudulent information (Baraniuk, 2020). This process allows customers to be up to date on the journey certain products are making, which in turn gives insights into inventories, the dwell times of certain items, which food items may be at risk, the temperatures of certain items, and so on. This data then offers the potential to make improvements to the supply chain as products move in real-time, and creates transparency for consumers and companies alike.

Food Trust is already being adopted by many different companies. In 2019, IBM reported that 200 companies had already joined the network (IBM, 2019). Companies such as Nestle and Carrefour have been making use of Food Trust in order to be able to show customers where food comes from directly in the supermarket, and to improve the quality of products in their supply chain (Alexandre, 2019). For example, Carrefour’s customers can scan the QR code on certain products to see where it is from, and when the product was harvested.

What do you think? Do you think that blockchain has the potential to change the way supply chains work? Do you think IBM has the potential to reduce waste significantly?

 

Alexandre, A. (2019). Carrefour, Nestlé Use IBM’s Blockchain Platform to Track Infant Formula. Cointelegraph. https://cointelegraph.com/news/carrefour-nestle-use-ibms-blockchain-platform-to-track-infant-formula

Baraniuk, C. (2020, February 11). Blockchain: The revolution that hasn’t quite happened. BBC News. https://www.bbc.com/news/business-51281233

IBM. (2019). IBM BrandVoice: The Food on Your Holiday Table May Have Been Verified by Blockchain. Forbes. https://www.forbes.com/sites/ibm/2019/12/23/the-food-on-your-holiday-table-may-have-been-verified-by-blockchain/

IBM Food Trust (p. 17). (2020). https://www.ibm.com/downloads/cas/E9DBNDJG

Lundqvist, J., de Fraiture, C., & Molden, D. (2008). Saving water: From field to fork—Curbing losses and wastage in the food chain. (SIWI Policy Brief). SIWI. http://dlc.dlib.indiana.edu/dlc/bitstream/handle/10535/5088/PB_From_Filed_to_Fork_2008.pdf?sequence=1&isAllowed=y

Parfitt, J., Barthel, M., & Macnaughton, S. (2010). Food waste within food supply chains: Quantification and potential for change to 2050. Philosophical Transactions of the Royal Society B: Biological Sciences, 365(1554), 3065–3081. https://doi.org/10.1098/rstb.2010.0126

 

No ratings yet.

I think that many people are aware of how AlphaGo Zero managed to defeat Lee Sedol, the then-reigning world champion of Go, with 4 against 1 back in 2016 (Chaiyong, 2020). It was one of the moments where the possibilities and potential of AI became more visible to the public than ever, and Go players around the world were impressed by the unconventional way in which AlphaGo played (Chan, 2017). The best player had been defeated, meaning that AI finally surpassed human capabilities.

The idea behind AlphaGo is as follows: the AI used a rule-based learning process. Using these rules, AlphaGo played against itself millions of times, serving as its own teacher (Silver, Schrittwieser, & Simonyan, 2017). Every time a new game started, the learnings from the last iteration was used to perform better in the next game. Ever since, the company behind AlphaGo, the UK-based DeepMind has been working on AlphaZero. AlphaZero learned how to win games against grandmasters in chess, shogi, and even Starcraft, going beyond what any human player is capable of doing (Greene, 2020).

However, after having defeated the best human players, the team behind AlphaZero found a new use for it: it is now not only able to defeat other players, but also able to play more creatively (Simonite, 2020). For example, playing chess against AlphaZero does not have to be frustrating for players anymore. It can also help hone their skills, and bring creativity back into the game. It can do so in various ways, such as mimicking the style of the player in order to challenge them, or allowing players to choose styles of specific grandmasters would. Then, AlphaZero will mimic the style of that grandmaster and challenge the player as that grandmaster. This is a large step away from the inhuman style that AI were often credited to have (Strogatz, 2018). Instead, it shows that AI can also complement even the best human players and bring creativity and new strategies back into the game (Simonite, 2020).

What do you think about this? Do you mainly see the future of AI as a way to complement human skill, or as a way to go beyond human capabilities?

 

Sources:

Chaiyong, S. 2020. Facing the Future. Bangkok Post. https://www.bangkokpost.com/tech/1982947/facing-the-future.

Chan, D. 2017. The AI That Has Nothing to Learn From Humans. The Atlantic. https://www.theatlantic.com/technology/archive/2017/10/alphago-zero-the-ai-that-taught-itself-go/543450/.

Greene, T. 2020. AlphaZero Beat Humans at Chess and Starcraft, Now it’s Working With Quantum Computers. The Next Web. https://thenextweb.com/artificial-intelligence/2020/01/16/alphazero-beat-humans-at-chess-and-starcraft-now-its-working-with-quantum-computers/.

Silver, D., Schrittwieser, J., & Simonyan, K. 2017. Mastering the Game of Go without Human Knowledge. Nature, 550: 354–359.

Simonite, T. 2020. AI Ruined Chess. Now, it’s Making the Game Beautiful Again. Wired.

Strogatz, S. 2018. One Giant Step For a Chess-Playing Machine. New York Times. https://www.nytimes.com/2018/12/26/science/chess-artificial-intelligence.html .