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Ben S
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I think AM represents different opportunities for different parts of the business. The LEAP engine has >12,000 orders, and is projected to be the best-selling engine ever. Therefore, this helps provide cost savings at scale. For other applications, including in R&D, many products will be very small batch to undergo testing/evaluation. I believe GE has value firstly for its own engines – the production for third-parties should only be used to increase machine utilization or increase knowledge.
For FAA approval, as I understand it, GE typically submits an entire engine for approval upon initial design. The whole engine is then evaluated based on requirements that demonstrate a certain level of durability. Parts can be approved one off, after the fact, but must be tested in a lab to be approved. Therefore, GE batches its engine tests to achieve scale. It may then take the “version 2.0” and either retrofit existing engines or make that the new standard if there are still new engines to be manufactured. Therefore, for this to work, it needs to design its updated parts in concert with its existing improvement test plans.
Great read – Given the new opportunity with AM if Ferrari pursues these partnerships, would you think they should try and iterate on the existing designs using AM, or use the technology to rebuild from the ground up? While I think the former helps them most effectively gain speed and learning for their effort, I wonder if the engineers fully grasp how different a design could be if you essentially eliminated any manufacturing restrictions.
Great article – I think part of the challenge here is there was a perception that the products caused harm to individuals. Are there areas that might have less detrimental effects that could be used to pilot the governance model of Skolkovo, before trying to work across all of the described sectors?
Great article – I imagine that to get scale, AECOM should focus on a single style of construction that they can prove out. However, this could reduce their flexibility and limit the potential applications. I worry about the regulatory question you raised at the end. Zoning rules vary slightly by municipality, and I wonder to what extent you would still need human workers as a follow on to still build the building.
Very interesting article – I think Blockchain serves a real need here. How would Walmart think about absorbing the cost to implement this? It already deals with very low margin suppliers, and I worry about them adding benefit to themselves at the cost of the supplier. To your first question – I think this provides incremental value to the consumer in terms of peace of mind, which Walmart may be able to price into its produce.
How does Latham think about prioritizing its people’s time into improving the integration of Kira? I would think the perspective of the associates would be helpful in improving this, but as you said, their time is already incredibly burdened.
I like how Machine Learning enables 1) solving problems in a more tangible way, and 2) have a clear idea of cost savings possible. I’d be curious the size of the total addressable market here – can they only do buildings or can they pivot to more energy intensive systems like manufacturing plant. I’d love to see a dashboard for companies so they can visualize this usage for these applications, and prioritize initiatives.