Carlos G

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Additive Manufacturing at GE Aviation
Carlos G
Posted on November 13, 2018 at 7:14 pm
Can jet engine parts really be made from powder? General Electric certainly thinks so.

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On November 15, 2018, Carlos G commented on Shooting for the Stars :

Thanks for the article, E.T. It is fascinating to me that NASA is finding effective ideas directly through crowdsourcing. The Planet 9 example you pointed out was incredibly powerful. However, and to your last point, I do think NASA should set some sort of internal controls around this practice in order to avoid possibly getting distracted incorrect/irrelevant ideas. I also find your point on talent acquisition very relevant. Seems like a great introduction to highly qualified candidates.

On November 15, 2018, Carlos G commented on You can pick your friends, and your friends can pack a box, but you can’t pick & pack a box without your friends :

Great article, LLovegood! The picking and packing functions are certainly one of the biggest challenges in Amazon’s fulfillment operation, especially given the scale they have grown to. I was a bit surprised that the company is turning to crowd sourcing for a solution. I guess it speaks to true complexity of the problem. To your question, I do think a possible solution will be easier for the company to come across if they are able to start with a blank slate in regard to warehouse setup. Another aspect that comes to mind with this solution is the management of human capital. Would a solution to this challenge essentially eliminate all of their fulfillment workers?

On November 14, 2018, Carlos G commented on 3D Printing Straighter Smiles :

Great article, Jane! I had never considered the possible applications of additive manufacturing in the dental industry. The technology’s value proposition aligns (pun-intended) very well this product. One point you brought up that really stuck out to me was the company’s focus on material science. If they are able to reach a point where aligners can be printed directly, do you think product pricing would be impacted? I sense that the price point is one of the biggest factors why clear aligners only make up 15% of the current market.

On November 14, 2018, Carlos G commented on How 3D printing is changing the way Nike approaches production and innovation :

I enjoyed your article, Phil. The 16x prototyping speed improvement due to additive manufacturing is truly impressive. Especially when you consider the scope of Nike’s product portfolio. While I fully believe in the prototyping benefits that additive manufacturing can provide, I am hesitant to believe that it can me a viable manufacturing solution for mass-produced goods. For the volumes of product that Nike produces, the process would be too slow and too costly. Though you do raise a good question when it comes to the possible impact that additive could have on premium athletic equipment (golf-clubs, tennis rackets).

User deleted this comment on November 15, 2018
On November 14, 2018, Carlos G commented on How 3D printing is changing the way Nike approaches production and innovation :

I enjoyed your article, Phil. The 16x prototyping speed improvement due to additive manufacturing is truly impressive. Especially when you consider the scope of Nike’s product portfolio. While I fully believe in the prototyping benefits that additive manufacturing can provide, I am hesitant to believe that it can me a viable manufacturing solution for mass-produced goods. For the volumes of products that Nike produces, the process would be too slowly and too costly. Though you do raise a good question when it comes to the possible impact that additive could have on premium athletic equipment (golf-clubs, tennis rackets).

User deleted this comment on November 15, 2018
On November 14, 2018, Carlos G commented on How 3D printing is changing the way Nike approaches production and innovation :

Much like your shoes, I enjoyed your article, Phil. The 16x prototyping speed improvement due to additive manufacturing is truly impressive. Especially when you consider the scope of Nike’s product portfolio. While I fully believe in the prototyping benefits that additive manufacturing can provide, I am hesitant to believe that it can me a viable manufacturing solution for mass-produced goods. For the volumes of products that Nike produces, the process would be too slowly and too costly. Though you do raise a good question when it comes to the possible impact that additive could have on premium athletic equipment (golf-clubs, tennis rackets).

On November 14, 2018, Carlos G commented on Easier Than Shoplifting: How Amazon Go is Revolutionizing Brick & Mortar Retail :

Thanks for sharing, Sam! The thought of revolutionizing brick-and-mortar commerce seems like a daunting challenge, but could we expect anything less from Amazon? One part of your article that really struck me was the potential impact that machine learning could have on inventory in this setting. The constant stream of data and the power of predictive analytics seem like optimal tools to find ideal inventory levels. The potential impact to the $46.8B in inventory shrinkage alone could be game changing. One thought that comes to my mind – would Amazon be better served commercializing some of these technologies and providing them to other retailers, rather than building out more brick-and-mortar themselves?

On November 14, 2018, Carlos G commented on Football and Chess: How Machine Learning Can Improve Playcalling in the NFL :

Great article, Derek! I was unaware that the league is providing teams with these massive amounts of game data. I had also never considered how machine learning could be applied in this context. The possible advantages that you outlined are huge. I found your point regarding the teams having each other’s data to be a very critical one. In my opinion, if the league begins to serve each team this information then the competitive dynamics will shift dramatically. Game plans would be tailored directly to statistical outcomes rather than the creative, awe-striking plays we have come to love. I am all for teams gathering intelligence/data on opponents but I think this would be taking it a bit too far. I am also curious – as a former quarterback yourself, how do you think of the differences between machine-learning-enabled play calling versus a player’s intuition to audible to the best possible play?