Chip's Profile

Thanks, Jeff, for your question. As I understand it, 3D printing can result in lighter components because the technology allows for fabricating more complex designs that are “leaner” than could be produced with traditional methods. It is a matter of the shape, I believe. Here are the sources I found that are most relevant to your question.

Lucas Mearian, “3D printing is now entrenched at Ford,” CIO, August 21, 2017, via ProQuest, accessed November 2018.

Ma Si and Cheng Yu, “3D printing is booming,” China Daily, August 21, 2017, p. 13, via Factiva, accessed November 2018.

Wang Ying, “3D-printed electric cars coming,” China Daily, March 13, 2018, p. 13, via Factiva, accessed November 2018.

Another source mentioned a company (not Ford) that prints a part with a “honeycomb core,” which would not be possible without 3D printing.

Thanks for your comment. I had not thought about the regulatory implications, but they could be significant.

Thanks for the explanation!

Thanks, Joe. My biggest question about the DDF concerns how the fund determines whether and how long to continue investing in medicines for dementia. The examples of open innovation given in our assignment come from the technology industry. In that industry, the cost of failure—both to the “open innovator” and to users providing ideas to that organization—is extremely low. For example, an unhelpful Yelp review takes only a few minutes of a user’s time to write and almost no resources to host on the website. Further, I believe that it will automatically be buried (effectively winnowed out of consideration) as more helpful reviews are added to the page.

By contrast, in drug development the cost of failure is very high, so I assume that there is a greater need—at least with some innovation ideas—to withdraw support from them at a certain stage given their expected probability of success. So how does the DDF evaluate ideas as part of the winnowing process (moving from divergent to convergent thinking, to use the language of IDEO)? What is the process, if any, for deciding not to invest more resources, and what are the criteria?

Thanks, Warrior Cat, for a very clear explanation of the advantages of AM.

You mentioned that AM has been important to GE for a long time, but they only created a dedicated additive unit within the last few years. I’m curious about the history—when did they start getting involved in activities that might be termed “additive,” for example? And will they be able to draw much on what they have learned in past efforts as they develop this new unit?

In such a heavily regulated industry as aircraft manufacturing, I wonder what the regulator’s perspective is. Does the Federal Aviation Administration (FAA) have a positive attitude toward AM, or are they more suspicious about safety issues with AM compared to conventional manufacturing methods? Given GE’s size and dominance in the market, I suspect that they have an opportunity to work with the FAA to craft best-practice guidelines for the use of AM in aircraft.

Thanks, Muneeb, for your analysis.

As I read about Face++ and the goal of identifying suspicious people before they commit crimes, I was reminded of the 2002 film Minority Report. Right now, you report, the government is just using Skynet to identify people who are likely to commit crimes. In the future, will it try to make arrests or prosecutions based on the analysis provided by its technology?

I like your idea of the specialized data appeals court. One theme we have discussed in class is the limitations of expecting machine learning alone to solve complex problems. As some have argued in our class, the way to improve organizations using new computing tools is to use them to guide human decision making, rather than supplanting that decision making altogether. Your proposed court would allow people to come to resolutions, well informed by data.

By the way, would you be able to add your footnotes to the bottom of this post? I was curious to know what some of your sources were.

My question concerns the definition of open innovation. (I wrote on one of the other trends, so I know very little about this one!) Our assignment note said that organizations use open innovation “to seek contributions from those outside the firm” in order to (1) generate content, (2) improve processes, and (3) develop products. Which one (or more) of these uses is happening for the Bounties Network? If none of the above, then would you argue that all platform businesses involve open innovation by definition?

Two aspects of your post struck me. First, you said that Align’s management are “focused on refining existing stereolithography technology,” which made me wonder whether they are doing enough to investigate other forms of additive manufacturing (besides stereolithography). My understanding is that new ways of 3D printing are evolving rapidly, and I would not want Align to overlook an opportunity to incorporate a better form of technology.

Second, I wonder whether materials are a constraint. I assume that they are stuck with the wasteful sacrificial molding process because they are not able to print the aligner directly. I recommend that Align hire materials scientists, or work with materials scientists at other companies, to stay abreast of the latest developments in materials for additive manufacturing.

Thank you, Tasnia, for your comment! I agree that Ford needs to explore thoroughly the possibilities for personalization that customers may demand in the future. One idea that I had pertains to a future (assumed by many these days) in which most cars on the road are self-driving and operated by ride-sharing companies in fleets. In that future, the economics of car sales will be very different, because purchasers of cars (Uber, Lyft) will have much deeper pockets than today’s individual consumer. Perhaps the fleet operators will want more and more ways to customize their cars so as to differentiate themselves to riders—and they will have the means to pay for this customization, which might come through AM.

First, Gossip Girl, I have to thank you for your excellent use of an image of Karen Smith in this post.

I have an idea for monetization: I think that IBM should market Deep Thunder to airlines and airports, which lose a lot of money (many millions of dollars, I assume) each year by canceling flights that could have departed; some of these cancelations are made because of inaccurate or insufficiently localized weather data. On the other hand, if the weather is likely to be too inclement for flights to depart, the earlier the airline can cancel the flight, the easier it is for customers to make alternative arrangements. So in both directions, the more accurate the available information, the better. I would also think about ways to market the product to other businesses that have to make operating decisions based on weather at the last minute (e.g., amusement parks, indoor/outdoor concert or wedding venues).