Understanding the Impacts of the Fourth Industrial Revolution

Understanding the Impacts of the Fourth Industrial Revolution

On December 6th, we continued our panel series, this time focusing on the Manufacturing Industry, specifically Industry 4.0.  Joined by Phil Naglieri (Director of Technology at Shockoe), Mason Brown (UX LEad at Shockoe), Mike Upchurch (Chief Strategy Officer at Notch), and Will Middleton (CEO at Cloudy Data Systems) we explored the results of the Fourth Industrial Revolution – including predictive maintenance, improved decision-making in real time, anticipating inventory based on production, and improved coordination of jobs and people.

We are currently in the Intelligence Age or Age of Information – The Fourth Industrial Revolution, revolution measured around manufacturing, but really on the impact of everything around us.  The one we are currently living is characterized by data, analytics, and the merger of technology with the physical, digital and biological worlds.

To get the full interview, check out our YouTube Channel

A Brief History of the Previous Industrial Revolutions
#1 – Agrarian to Industrial (Textile and Industry) & Steam:  This revolution took place in during the 18th and 19th century.  It was a period marked by the creation of the iron and textile industries as well as the Steam Engine.

#2 – Electricity, Assembly Line, Light Bulb, and Telephone:  The second revolution started in the late 18 hundreds and lasted through the beginning of WWI, this revolution was marked by the creation of the combustion engine, the light bulb, the telephone, and the assembly line.

#3 – Nuclear Power, Computers, Computing, and Internet:  About half a century later, and really the only revolution any of us lived through is the third revolution, which appeared with the emergence of a new type of energy whose potential surpassed its predecessors: nuclear energy. This revolution also brought with it electronics and the internet—such as the transistor, microprocessor, and computers and the world wide web.

Question and Answer with the Panelists:

Can you give me some insight into the following statement:

“Manufacturing workers are retiring in droves, with an estimated 2.7 million jobs being vacated by 2025. At the same time, the growth and advancement of the industry is expected to create an additional 700,000 jobs for skilled manufacturing employees over the next decade. As a result, manufacturers are scrambling to fill this knowledge and skills deficit with the next generation of workers — millennials.”

Answer (Phil):  Mobile is essential to Manufacturing Companies, who are not naive to the process of hiring new generations to fill the roles left by aging workforces as we’ve seen happen in the recent past, Mobile brings a sense of familiarity and allows for quicker adoption.  Not only will employers onboard new employees quicker, it will allow them to streamline their processes better.

Question:  AI and machine learning are getting a lot of press so can you tell us a little about it?  Specifically, as it relates to Manufacturing, where possible

Response (Mike):  At a high level, think of AI and machine learning as that you are using machines to do what a human would do if they had unlimited time and capacity.  So for example, let’s say you are the production manager at a plant and you are trying to improve yield.  You’d look at a bunch of process and machine data in reports, make changes and then evaluate the impact of your change.  Machine learning will do the same thing except use math to look at thousands of variables and their interrelationships.  The other thing to know is that 80% of the work to use machine learning with be data acquisition and management.  To be good a machine learning, you have to be good at data.  Finally, the process is iterative and exploratory.  For example, a project might start with a question like, “of the 3,000 points of data we capture, what combination of factors cause defects?”.  To solve it the data scientist will try different sets and types of data as well as different models to figure out what combination yields the optimal insight.

Question:  With the recent addition of bitcoin to the Chicago Board Options Exchange and the Chicago Mercantile Exchange, bitcoin and blockchain are in the news today more than ever. How are these different and is the hype really worth it?

Response (Will):  I have been heavily involved in the bitcoin and blockchain space for over a year now and recently became the chapter leader for the Government Blockchain Association Richmond Chapter. Bitcoin and blockchain have been a wild ride this year and the hype is most definitely worth it. The technology provided by the blockchain and the decentralized value exchange of bitcoin are both extremely transformational and disruptive.

Blockchain is one of the underlying technologies behind bitcoin. Though public and private key cryptography, it allows different entities (i.e. an organization, a person, or even a machine) to prove that it is the owner of some data stored on a public database. In Bitcoin, the user can prove they are the owner of the account that sits on the public ledger.

Question:   Earlier you talked about machine learning can you tell us how it’s being used in manufacturing?

Response (Mike):  There are three common categories of use – predictive maintenance, improvements in things like yield, capacity, and quality, and systems optimization.

Using machine learning for predictive maintenance has proven to reduce downtime, in some cases as much as 50% and increase machine life by 20% to 40%.  An example would be predicting part failure and fixing the issue before it happens.
Improving yield/throughput/capacity and quality – studies have shown a wide range of results.  In some industries, the increase can be in the 10% range, but in others, like semiconductor manufacturing, where they are already good at yield, the results can 1%.  However, in that business, a  1% improvement in yield is worth $100M.  This is accomplished by looking at the end-to-end process and understanding not only how each machine contributes to defects, but also the interdependencies of each machine to each other as well as environmental factors; such a factory temperature fluctuations.
As for systems optimization, think of looking at the entire process from sales through manufacturing and delivery. An example would be using 1,000 variables and 10,000 constraints to figure out how to optimize system performance.  The company that did it raised earnings 50%.  Quite dramatic.  A lot of simulation is used here.  An example would be that large oil and gas companies have simulations of their entire plant so they can do things like see how changes in maintenance schedules affect the entire system using software and then optimize the schedule before doing any physical changes.

What are the challenges?

  • Data
  • Security – fog/edge/local, not cloud
  • Operational – ready to adopt?
  • Finding talent

To get the full interview, check out our YouTube Channel

How technology leveled the playing field among drivers

How technology leveled the playing field among drivers

Most people may agree that there are two types of drivers – the confident and the not so confident. With the help of technological advancement, the automotive industry is leveling these playing fields, making it difficult to categorize drivers. One of my favorite commercials in the past year is the State Farm Safe Driver which depicted a female receiving a “safe driver refund” check. State Farm not only showed off their refund policy for their Safe Driver program, but highlighted that it was a female who got the refund instead of her husband who was helplessly confused possibly because of the oddly popular female driver stereotype.

Technology has always been able to make our lives easier. Safe driving is not excluded from the list of the daily tasks positively affected by technology. Today, the “not so confident” drivers can rely on an array of technologies to not only make us a tad more confident but ultimately safer drivers. So just how is the automobile industry leveling the playing field? We cannot answer that question without taking a high level look at how automobiles have evolved in recent years specifically with a technology in mind.

First there’s the navigation systems. Ten years ago, having a navigation system in your car cost about 10% of the price of your vehicle. Instead, drivers relied on printable directions from sources like MapQuest to get from point A to point B. Reports show that printed maps were a huge distraction for drivers resulting in safety concerns. If you think texting while driving is a major distraction, try reading a map while driving. Today, the majority of new cars have a navigation system—usually a touch screen—that comes standard. Additionally, the navigation has been voice enabled meaning drivers don’t even need to look at the screen for directions.

After a few more technological leaps came self aware cars. It’s mind blowing to know that your car has a sense of self-awareness. Augmented Reality allows cars to visually project directions, dashboard gauges, and more, in front of the driver’s view eradicating the need to look away. The windscreen of cars are now a massive digital screen with endless opportunities. The navigation, the voice commands, even the auto parallel parking really leveled the playing field for various drivers. AR is usually considered to be a live view of the real world, onto which extra data – usually pulled from the internet – is layered or superimposed. In recent years, we’ve seen more automobile brands incorporate AR to their offerings with a promise to make drivers less distracted, thus being able to focus more on what’s on the road ahead. I’ve driven recent models of luxury automobile equipped with AR used to project the dashboard gauges, current speed, maps, directions and other basic dashboard-like information onto the windscreen. The informative data had the amount of opacity not to impair the driver’s view of the what is on the road while at the same time keeping head and eyes straight ahead, nullifying the need to glance away to a navigational or any other screen(s). Once this becomes mainstream, one may argue we will have no need for street signs, since of course pedestrians will be wearing Google glasses with similar AR technology available.

Distractions are said to be the number one cause of accidents in recent years and reducing driver distraction has been one of the major goals of the automobile industry. First we were given Voice Recognition which meant I can tell my car to “take me home” and navigational guidance to my configured home address would be started automatically and now instead of glancing away to a screen I can now see the directions, current speed and a whole lot more right on my dashboard. This is the kind of technology that invigorates us at Shockoe.

We started 2017 with a focus on Voice Recognition, Augmented and Virtual Reality and I must add that it feels great to be a part of a company that has always been on the cutting edge of technology but even better, a company that is always ahead of the curve on the next big idea in this ever changing industry. So when you’re using your enhanced car windows that allow you to to zoom in on places and objects of interest that you are passing, when the back seat of your car appears transparent while reversing so you can see everything around you, just remember, Shockoe will be right there with you, working with those same technologies that are turning us all into confident drivers.

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