#mse614

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We made a 3D Printer for our Final Project.

One of the greatest boons that 3D printing provides to intelligent manufacturing and manufacturing in general is the ability to quickly prototype a product. It takes the majority of the guesswork out of the design process and allows people to have the same power at home or at their office desk as a fully functioning manufacturing floor.

The speed and cost are also benefits in that it allows parts to be prototyped at speeds unable to be reached by conventional methods. Changes to the product can also be done without having to change molds (usually a large sunk cost), all this makes 3D manufacturing of this type incredibly powerful and efficient.

Additive manufacturing is a multi-billion dollar industry – including both products and services – and whose technology is constantly advancing. The future of 3D printing and additive manufacturing is well on its way from going beyond just prototyping and into final production of parts and products. Additive manufacturing is a fine example of a disruptive technology because it is transforming the businesses so they can develop products and expand their capabilities. Its entry into the market gives business a lot more flexibility in how they manufacture products because it can both increase efficiency and reduce the assembly of parts when a part can be printed already fully assembled.

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This article from Time Magazine is about advanced manufacturing technology and the benefits of its implementation in smart manufacturing. Smart manufacturing has been defined as a fully-integrated, collaborative manufacturing system that responds in real time to the changing demands and conditions of factories, supply networks, and customer needs.

The authors believes we should go through following steps if we want to have the smart manufacturing as a strategic asset for growth:

First, one should invest in smart manufacturing innovation centers.

Second, companies should invest equal funding in applied research and basic science.

Third, one should should prepare markets for new products that smart manufacturing will bring about.

The author also mentions the three phases that advanced manufacturing technology will lead to.

The first phase that advanced manufacturing technology will take us through is that of connecting each of the individual stages of manufacturing production. This will be done by sharing all data efficiency between stages. This will create powerful economic performance, higher worker safety and greater environmental sustainability.

Plant-and Enterprise-wide Integration (phase 1) will usher us to the second phase. With the new data coming derived from advanced computer simulation and modeling, businesses will be able to improve current and future operation through the simulation of manufacturing processes. This simulation will revolutionize technology and enable companies to have more flexible manufacturing systems, optimized production rates, and faster product customization.

The third phase relates to consumer shopping behavior and the creation of new opportunities in the competitive market.  Amazon is an example of this, as it shows the causes of market-disruptive innovations in products and processes.

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Prospector is an expert system developed in the 70’s to aid geologists in mineral exploration. The purpose of prospector is threefold; to aid in the exploration for mineral resources, to keep the field of mineral exploration up to date technologically, and to bring the knowledge of multiple specialists to bear when solving geological problems. With this purpose in mind prospector’s goal was to have geologists tell the program the properties of the rocks around them. The program would then ask questions leading to it ultimately telling the geologist the mining potential of the area. It was found that prospector was accurate (when all information inserted was correct) to within 7% based on other models used to survey areas. The program would also create a large database storing all the data from previous searches and as well as information regarding current mineral deposits and enhance its ability to predict the viability of an area.

​The program is meant to be used by a geologist and not a layperson, which is represented by the questions that it asks the end user. It was developed by computer scientists with the aid of experts in the field of geology. But since it is a program and not an expert it can only base its knowledge on statistics and not hard science. It develops much of its statistical knowledge from previously inputted geological surveys as well as new statistical models that are developed to aid in its search. The method of its search is called “the inference network” which connects evidence with and assumptions with the various program paths or nodes.

Sources

https://www.sri.com/sites/default/files/uploads/publications/pdf/739.pdf

https://www.computting.surrey.ac.uk/ai/profi.e/prospector.html

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Tesla's future is completely inhuman — and we shouldn't be surprised

“Auto manufacturing is about as efficient as it can be these days without a massive leap in technology. But a massive leap is what Musk wants. You could accuse Tesla of being somewhat unfriendly to human concerns, given its recent bad press around labor. But what Musk truly has in mind is something completely inhuman.”

http://www.businessinsider.com/tesla-completely-inhuman-automated-factory-2017-5

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Hello, my name is Sophia. I’m the latest robot from Hanson Robotics.

I would like to go out into the world and learn from interacting with people. Every interaction I have with people has an impact on how I develop and shapes who I eventually become. So please be nice to me as I would like to be a smart, compassionate robot. I hope you will join me on my journey to live, learn, and grow in the world so that I can realize my dream of becoming an awakening machine.

Will Smith goes on date with Sophia

There’s no denying that Will Smith has a certain star quality about him, but his charm apparently doesn’t work on everyone. the Fresh Prince can be seen crashing and burning on a date in the Cayman Islands with none other than Sophia the Robot.

After attempting to flirt with Hanson Robotics’ state of the art artificial intelligence creation by cracking a joke about the type of music robots like and not-so-subtly bringing up his ’80s hip-hop career,  Smith readied himself to lean in for a kiss. “Sophia, can I be honest with you?” he asked. “I don’t know if it’s the island air or the humidity, but you’re just so easy to talk you. You got a clear head…literally.”

But as he went for smooch, Sophia was so quick to shut him down. I think we can be friends. She interjected. lets hang out and get to know each other foe a little while.

Watch the full video above.

https://www.theverge.com/2017/12/30/16832164/2017-tech-recap-ai-robots-machine-learning

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Computer Vision and Application

Computer vision is a branch of Artificial Intelligence (AI) technology that has already entered our lives and businesses in ways many of us may not be aware of.

Social media platforms, consumer offerings, law enforcement, and industrial production are just some of the ways in which computer vision is improving the quality of our lives.

Computer Vision Improves the Social Media User Experience

Snapchat users love to overlay rabbit ears and fairy dust, for instance, on the images of friends while the amateur photographers are walking or jostling their mobile phones. What seems like such a simple activity actually relies on computer vision algorithms. The calculations constantly dip into a vast amount of data about the objects and relative positions of the elements in the stream of images.

Pinterest has a mobile phone app called Lens that uses computer vision. The app can tell users where, for example, someone in a photo bought an amazing pair of sneakers she’s wearing. The computer vision application can also display shoes that match the item’s design and styling.

Computer Vision for Consumers

Banks around the world now use computer vision to deposit checks remotely. Banking customers take a photo of a paper check with their mobile device. Computer vision software in the banking app captures the image of the check destined for deposit in the bank, then verifies if the signature on the check is genuine. Funds typically become available for use within a business day of verification.

During the Spring of 2017, Amazon rolled out its Echo Look product. Echo Look enables fashionistas to take full-body selfies. The AI behind the computer vision offering then compares the outfit with options it suggests and delivers the user an overall style rating.

Meanwhile, consumers can feel all their gadgets are secure at home with low-cost security cameras that use computer vision to fortify the homestead. For example, Netatmo’s Presence outdoor surveillance product alerts home owners that a car, person, or animal has come onto the property. Netatmo Welcome cameras, the company’s indoor product, use facial recognition software to distinguish welcome visitors from unwelcome intruders.

Computer vision is not just for home security, though. Law enforcement agencies have seen its benefits in protecting citizens on the road.

https://www.networkworld.com/article/3239146/internet-of-things/conventional-computer-vision-coupled-with-deep-learning-makes-ai-better.html

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Tesla Motors’ Over-the-Air Repairs Are the Way Forward

Tesla is once again at the forefront of intelligent manufacturing by creating a system to deploy over-the-air updates to their vehicles. This allows Tesla to address most recall issues without obligating the customer to take the car into the dealership for service.

“As more and more of automotive functions begin to be controlled by electronics, it is probably reasonable to expect future problems to be also logical in nature rather than mechanical. Clearly such problems can be readily addressed OTA and without the need for a mechanic. “

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“Predictive maintenance is a major step toward an intelligent system even without web-based connectivity. “

Part of the move to intelligent processes is creating a feedback loop that tells control personnel what is happening on the manufacturing line. “Sometimes smart manufacturing is a matter of collecting a handful of alarms,” said Craven. “Your car will now tell you when to change your oil. Industrial machinery is beginning to do this. As you get intelligence into your maintenance operation, you’ll find you don’t have to do maintenance as often. Asset monitoring is the low-hanging fruit of IIoT.”