TechHub: Google’s AI makes one smart cookie, MDS Radios digitizing industrial communications & more

Digitizing Industrial Infrastructure Communication

Running a city with a population in the hundreds of thousands, or millions, in a hot climate like Florida’s leaves no room for error — especially when tourism is a huge sector of the booming economy.

Ensuring residents have all the essentials — including uninterrupted water and wastewater services — requires a constant choreography that is as complex as it is invisible to its users.

One thing is certain: people expect their water and wastewater systems to work all the time, no matter the conditions.

One utility came to us with a huge concern, “if our network goes down, what do we do?”

GrayMatter stepped in to help, implementing a SCADA backup communication system with MDS radios.

MDS Radios

Ethernet connectivity was implemented to their SCADA system with a failover to cellular communication if the signal dropped.

By helping the water utility secure connectivity, machine communication became a guarantee and fear of lost network connections were a worry of the past.

Click here to read more about MDS radios:

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Google Takes AI to the Next Level with Pittsburgh Bakery

Google decided to once again prove the power of artificial intelligence by solving a pressing real-world challenge: designing the best possible chocolate chip cookies using a given set of ingredients.

Through trial and error of batches, matched with rating scores for each recipe by Googlers, the AI learned and adjusted until it was deemed worthy. After coming up with a really good recipe within Google, the team wanted to branch out and see what else they could do with the “smart cookie,” according to Google.

Jeanette Harris & Google Team presenting the chocolate chip and cardamom “smart” cookie. source: Google blog

This led the team to Gluten Free Goat Bakery & Cafe, a gluten-free and vegan bakery that sources local, seasonal and organic ingredients, who happily let the Google team take a crack at a more complex and challenging recipe that fit their style and criteria.

The new AI-generated cookie took over two months and 59 test batches before they landed on the “chocolate chip and cardamom cookie,” which matched unusual ingredients to create a new take on the classic chocolate chip cookie.

“This was such a fun experiment! Being able to create something entirely new and different, with the help of AI, was so exciting and makes me wonder what other unique recipe concepts I can develop for my customers,” said Jeanette Harris, owner of the bakery.

Check out the recipe listed below to replicate the smart cookie yourself. 👇 👇 👇

Ingredients

Tapioca Starch: 1/2 Cup + 2 TBSP

Brown Rice Flour: 1/2 Cup

0G Sugar: 3/4 Cup + 1.5 TBSP

Cardamom: 2 tsp

Flaxseed Meal: 1.5 TBSP

Sorghum Flour: 1/4 Cup

Raw Sugar: 1/4 Cup

Xanthan Gum: 1.5 tsp

Sea Salt: 1.5 tsp

Baking Soda: 1 tsp

Chocolate Chips: 1 Cup

Water: 3/4 Cup

Safflower Oil: 3/4 Cup

Directions

Combine all the dry ingredients except the chocolate chips in a bowl and mix well.

In another bowl, combine all the wet ingredients, and then add to the dry ingredients and mix enough to combine.

Add the chocolate chips and fold in until just mixed. Using a large spoon, drop on parchment lined sheet pan and bake at 350F for 12 minutes.

Life on the Edge: Why Micro Data Centers Are the Next Frontier

Originally Published in CRN, by Lindsey O’Donnell

Pittsburgh-based industrial solution provider GrayMatter has found massive opportunities for edge computing on manufacturing floors where customers may have mission-critical infrastructure that requires high reliability and can’t afford downtime.

“Edge is almost a continuum of possibilities, from servers with tons of edge computing power and storage, down to a really simple, not expensive, lower intelligence to just bridge the data up to the cloud—so it depends on how much latency you can handle in an application, how much local intelligence needs to go on,” said CEO Jim Gillespie. “For a manufacturing plant, it’s very important to close the loop locally, for other applications like lighting going up to the cloud, you don’t need as much at the edge.”

micro data centerGrayMatter has a big role in working with customers to understand where the edge will really drive value and how that will impact business outcomes, according to Gillespie.

“It’s a conversation around the outcomes, so you really have to understand the right questions to ask and the right way to design a solution,” he said. “We would weigh in with the client and design something that meets the outcomes they’re looking for. Almost everything has edge computing, and then it depends where the analytics need to happen, and there’s some sort of connectivity or either local buffering or on ramp to the cloud.”

Read Full Article.

TechHub: Automation Creates More & Better Jobs, Seegrid’s New Self-Driving Pallet Truck and More

JOHN TLUMACKI/GLOBE STAFF

Automation Creates More, Better-paying Jobs

Robots, artificial intelligence and other forms of automation are often feared due to their job-destroying potential when in fact they’re creating more, better-paying jobs.

The brick-and-mortar retail swoon has been accompanied by a less headline-grabbing e-commerce boom that has created more jobs in the U.S. than traditional stores have cut. Those jobs, in turn, pay better, because its workers are so much more productive, according to the Wall Street Journal.

Throughout history, automation commonly creates more, and better-paying, jobs than it destroys. The reason: Companies don’t use automation simply to produce the same thing more cheaply. Instead, they find ways to offer entirely new, improved products. As customers flock to these new offerings, companies have to hire more people.

In the Amazon facility’s packing area, computers tell workers precisely which size box to use. PHOTO: ADAM GLANZMAN FOR THE WALL STREET JOURNAL

James Bessen, an economist at Boston University School of Law, has found in numerous episodes when technology was supposed to annihilate jobs, the opposite occurred.

After the first automated tellers were installed in the 1970s, an executive at Wells, Fargo & Co. predicted ATMs would lead to fewer branches with even fewer staff. And indeed, the average branch used one-third fewer workers in 2004 than in 1988. But, Mr. Bessen found, ATMs made it much cheaper to operate a branch so banks opened more: Total branches rose 43% over that time.

There are still plenty of logistics that only humans can handle. When the new 1.2-million square foot Amazon warehouse opened in Fall River, Massachusetts, Amazon workers had trouble stowing long, narrow things like shovels and rolled-up rugs, which don’t stack very well. Their solution? Large cardboard tubes, typically used to form concrete pillars, were fashioned into rows and rows of improvised barrels, according to the Boston Globe.

“One thing we learned is to find the cheapest and easiest solution possible,” said Andrew Sweatman, the Fall River general manager.

City leaders rolled out the red carpet for Amazon with generous tax incentives and a prime location on Innovation Way. Its arrival was the single biggest job creation event anyone could remember.

“We had people with a skill set that was nontransferable,” says Jasiel F. Correia II, Fall River’s 25-year-old mayor and a first-generation child of immigrants from the former Portuguese territory of Cape Verde. “Where does a person who sewed textiles for 20 years go if they’re laid off? Places such as Amazon fill that gap,” he says. “They got a chance to work for a Fortune 500 company. This community doesn’t get those chances very often.”

Seegrid Rolls Out New Self-Driving Pallet Truck

Seegrid has rolled out a self-driving pallet truck the Pittsburgh-based robotics company said doesn’t need human intervention.

As the leader in connected self-driving vehicles for materials handling, they’ve recently expanded the company’s suite of automated solutions with the announcement of the GP8 Series 6 self-driving pallet truck.

SOURCE: Seegrid

Further enhancing the Seegrid Smart Platform, which combines flexible and reliable infrastructure-free vision guided vehicles with fleet management and enterprise intelligence data, the self-driving truck has fully automated material movement to execute hands-free load exchange from pick-up to drop-off, according to Seegrid.

In the automotive industry, self-driving vehicles are used for consistent delivery of parts to line. The self-driving pallet truck picks up and drops off palletized car parts without human interaction, increasing productivity amidst labor shortages for automakers. In e-commerce, it enables fully autonomous delivery of goods to keep up with fulfillment industry growth and demand.

Operating without wires, lasers, magnets, or tape, it allows manufacturers and distributors to change routes in-house, operate in manual mode, and effortless scale their fleet as they grow.

As part of the Seegrid Smart Platform, the Series 6 is aligned with Industry 4.0 and lean initiatives, helping companies transform into smart factories of the future.

Developing a Work Culture that Embraces its CMMS and Values Data Accuracy

First, establish new behaviors by creating a set of CMMS guiding principles.

Creating a culture that embraces CMMS and values data integrity begins with leaders changing their behavior. If they expect their organization to change, O&M leaders, including materials, procurement, and engineering functions, should jointly develop a set of CMMS guiding principles.

The development process creates ownership and alignment within the cross-functional group around new leadership behaviors. After completion and approval, leaders should post the CMMS principles, which will allow them to hold each other, as well as the organization, accountable. It will also enable the organization to begin adjusting to the new behaviors they observe. When leaders consistently behave differently, the organization will adapt and follow, according to Industry Week.

Guiding Principles

  • No work order, no work
  • 400-percent rule
    • 100% internal labor, 100% of materials, 100% of contractor cost documented on work order, 100% of the time
  • Completed field work documented
  • All equipment failures receive a Root Cause Analysis (RCA)
  • All spare parts have a stores item number
  • All lowest maintainable equipment is identified by unique number, title, hierarchy and criticality rank
  • Measure the process as well as end results
  • Weekly work order audits
  • Periodic communication
  • Periodically audit the CMMS

Developing a culture that embraces utilization of a CMMS and values data integrity starts with leadership vision and behavior.

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Pulling Needles out of Your Data Haystack

3 steps to act on data you’re already collecting. 

The Impossible is Now Possible

Industry 4.0 is moving fast and I’d like to let you in on a few very valuable developments about the data you’ve been collecting. It can now help you make better decisions. You can talk to your industrial data and it’s talking back to you, letting you know what’s working inside your operation and what’s not.

It’s exciting for me to see GrayMatter and our partners innovating by taking the data you’ve been collecting through sensors on industrial equipment and applying artificial intelligence and machine learning in the cloud so you can find insights on performance. Then you know exactly where to make improvements.

You need a system to sort through the haystack of data and pull needles out to focus your subject matter experts. That’s what we can do now.

It all starts by framing up the action strategy in three parts.

Step One: Set Your Goals

Start at the end and work backwards.

What return on investment do you want to see? You don’t need all the data you think you need. What information will help you solve the problems you want to solve? What’s the path to getting there? Having this roadmap first is critical, because otherwise a lot of time and money can be wasted.

Step Two: Start Creating Digital Twins

You hear the term digital twin, but what does it really mean?

Simply put, creating a digital twin is the process of merging physical and digital worlds.

The process takes a physical machine and uses technology to get all the information about past states, present states and predictions. That information creates a digital model that’s alive – taking in a stream of data – using that to adjust so the model is personalized to be a precise representation of the asset.

The software version is used for what used to be a physical inspection – requiring people to be right next to the machine. The virtual version can be done from anywhere and at any time, expanding the value of those inspections and allowing them to have more of a real-time impact. It creates a constant inspection that allows the operators to predict failures sooner.

Digital Twin Value

The digital model of a machine, built and run in a virtual environment used to be available only to the biggest companies with the largest budgets. But the Industrial Internet and an explosion in sensor technology have lowered the cost and broadened the access beyond the elite.

pulling needles out of data haystack

People are not only connected to people, they’re connected to every kind of device at home and now work. Manufacturers stand to win big from this. Factory floors are outfitted with tremendous amounts of sensors to collect data, but because that data has been locked up it hasn’t provided value.

The digital twin allows us to unlock that data and not just for one asset at a time. We can now model machines in groups – for example, a machine builder with thousands of machines installed across hundreds of customers – will now be able to operate best in class using digital twins.

There’s potential to unleash productivity and efficiencies like we’ve never seen before.

Step Three: Get Behavioral Information from Digital Twins

In order to move to more advanced use cases, such as adaptive diagnostics, condition-based maintenance or predictive failure, Industrial IoT systems need to know more than simply the current device state.

They need to know why. Knowing current device state only helps from a monitoring standpoint.  While important, it’s really just the beginning of what we can expect out of IIoT systems. If we know why an asset exhibits a certain state, we can determine what conditions lead to that state and take proactive steps to prevent future occurrences. 

This new layer of getting insight through behavioral information allows you to ask for more. You can search your data and get answers back right away. It’s like an instant messenger for operational technology.

Step Four – Get Digital Twins to Interact

Achieving this may mean digital twins built using multiple discrete machine learning algorithms potentially spread across multiple IoT platforms, not simply relying on one. Eventually, we should expect that digital twins will interact with one another in virtual space.

Leap Ahead

If you’re short on time, staffing or budget – GrayMatter can get you up and running to achieve value quickly. You know you need an Iot strategy in the near future, but may not know how to go about it. Rather than trying to design, source and build it yourself we can put the strategy in place in days or weeks.

You also don’t have to do everything at once, you can start with a limited selection of assets and scale up or down as you learn performance and asset behaviors.

Our strategy is a Salesforce version of a remote monitoring and diagnostics center that you can buy and implement incrementally.

GrayMatter’s Digital Twin Strategy

We use data, predictive capabilities and machine learning to identify your best and worst performers in each asset group. Your operators are automatically alerted to the worst performers, then they use an intuitive web interface, to turn the worst into the best.

Continuous improvement becomes expected, simplified, and routine. As your team builds new improvements or optimized settings, they can be scaled out, automatically, to every instance of a specific machine or piece of equipment.

You Don’t Need a Data Scientist

The complex algorithms that can leverage your data are pre-built so anyone can start creating the models and analytics to generate insights. One person no longer holds the keys to data, with this unique platform everyone gets a better understanding of your businesses processes, so you’re not focusing on the math to bring the insight, you’re focusing on creating better outcomes for your customers.

Think Big, Start Fast

You need to think big to truly transform your organization, but you also have to start acting on your data today.

We’re anxious to spread the word about how easy this is and to un-complicate it for you. Let me know if you’d like to discuss further.

– Jim Gillespie, GrayMatter CEO.

Click to download the case study to start acting on your data:

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TechHub: Digital Transformation in Steel, the Industrial Technology Future & Pittsburgh Tech 50

Gerdau Saves Millions Annually, Accelerates Their Digital Transformation

$4.5 million in annual savings with a complete ROI in only 8 months.

Gerdau has enjoyed a long reputation as a process innovator in the steel industry for more than a century.

For a company with more than 35,000 people across 13 countries, the goal of a 20% reduction in maintenance cost was significant. It would not be easy to accomplish, but accomplishing the reduction was critical to the company’s profitability.

When an asset fails, the company loses an average of $12 thousand per hour in downtime.

The transformation Gerdau needed would take them into uncharted territory for many in the steel industry: the digital realm of the Industrial Internet of Things (IIoT).

Dreaming big pays off

Download the case study to view the roadmap for digital transformation in the steel industry:

Download the Case Study

The Industrial Technology Future

Open software platforms are an increasingly popular trend within the industrial technology sector that is highlighting the important relationship between operational technology (OT) and information technology (IT).

For GE Digital, Predix is the nexus where app engines, digital twins, machine learning and asset performance management meet, said AutomationWorld after a meeting at GE Digital headquarters in San Ramon, Calif.

“Platforms are where tech is going,” said Gytis Barzdukas, head of product management for Predix at GE Digital. “Like Apple, Amazon, Microsoft and Alphabet have their platforms in the consumer space, we want to do the same thing in industrial space. That’s why Predix is an open platform with regulated participation. Predix has been developed as a common data layer into which third-party supplier products can plug into.”

Although the focus in the past on Predix has focused on its cloud-based operations, but Barzdukas was quick to point that Predix can run operate at the edge, in the cloud or in hybrid applications.

cloud platform

A diagram of the GE intelligent platform Predix. Image: AutomationWorld

Addressing cybersecurity concerns around the transmission and storage of such data in the cloud, Barzdukas said Predix currently uses public key encryption and is moving toward inclusion of private key capabilities for users who want it. Predix’s public key encryption security operates in addition to the security provided by Amazon Web Services on which Predix’s cloud functions run. Barzdukas added that Predix will also soon be running on Microsoft Azure.

Pittsburgh Tech 50

The Pittsburgh Technology Council’s Tech 50 finalists were announced, recognizing the most successful and innovative companies in the Pittsburgh area.

Companies range from health IT, life sciences, manufacturing, consumer products, consulting services and more, and are broken up into the following categories:

  • CEO of the Year
  • Solution Provider of the Year, Consulting and IT Services
  • Culture Leader of the Year
  • Innovator of the Year, Consumer Products
  • Solution Provider of the Year, Innovative Technology

GrayMatter is a finalist for Solution Provider of the Year, Innovative Technology, with CEO Jim Gillespie a finalist for CEO of the Year.

The award ceremony will be Thursday, October 12 at the Wyndham Grand Hotel.

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