IIoT Edge – what is it and why do I feel like this guy?
IIoT – Industrial Internet of Things
IoT is about the transformation of any physical Object into a digital data product.
Hitachi Ltd - $91B and 320k employees
Hitachi is made up of 900+ subsidiary companies
Hitachi in the US - ~90 separate companies
Hitachi Trivia – there are two Hitachi companies just in Greenville, HTA and Hitachi Consulting. (Michael Elliot)
Hitachi High Tech – Japan - $5.3B and 10k+ employees
Hitachi High Tech America - $800M and 500 employees
HTA-SPD – Greenville ~ 20 employees (engineers) – focused primarily on IIoT
HEDUS History – 1990, 1500 employees manufacturing over 6M PRT’s and 1.2M CPT’s/year at our peak.
The economic impact of IoT varies widely, depending on which article or person you read or listen to ….read some of the above stats.
IIoT is a subset of IoT and this is the space that we as manufacturing people focus on.
I could end this right here, but some of the biggest challenges to gaining traction are:
Who owns the data?
Who owns access to the data?
Does it cost money to access the data?
Are we selling data or asset management – I would argue it’s the latter.
How do you show a ROI?
According to Gartner’s 2015 Hype Cycle..
IoT in general is currently at the “Peak of Inflated Expectations”, while IoT platforms are still coming up and in the “Innovation Trigger” space – according to Gartner’s Hype Cycle.
But…are we being bombarded with inflated, hyped and useless info? My guess is yes, probably…
You will also note the huge variation in the Number of connected Devices – between 8B and 75B by 2020.
Who do you believe?? Keep in mind this includes all devices (personal, home, vehicles, enterprises , and the Industrial (IIoT) segments)
According to FirstMark Capital, here is a small portion of the current IoT landscape.
Very busy graphic right?? But if you and your company need a starting point, here is just a sample of companies in each of these spaces/segments.
Of course I was disappointed that I didn’t see Hitachi, so I wrote the author and hopefully he will add it in his next version.
So.. I kept looking, and guess what I found??
Network World did a survey and they came up with a list of the Most Powerful IoT Companies (whatever that means?)
I was glad to see that Hitachi made this list, but you will also see my fellow presenters companies are also featured (GE, IBM and PTC).
<click> I firmly believe that successful IIoT requires a multi company collaboration to ensure success (includes companies of all sizes – small, medium and large)
<click> Challenges & Trends – …..read slide, but emphasize Fog or smart gateway/analytics – due to latency concerns and cost to access data and a belief that data is more valuable at the edge.
Industrial Internet Consortium (IIC)
Great group by the way – focusing exclusively in the Industrial Internet of Things.
>230 companies including most of the companies listed on the previous slide.
Lee asked me to focus on the Edge, but this graphic is a nice way to visualize the entire IIoT architecture.
To offer a solution to the customer you must be aware of and have access and offer solutions to all three tiers.
….Talk about the Edge tier graphic
IT & Operations Technology have traditionally been separate domains –never the two shall meet.
About 10 years ago - I actually was responsible for both our IT and OT (we called it Computer Integrated Manufacturing) groups at Hitachi for awhile –they had an inherent distrust of each other.
I had the challenge of taking two talented but strong headed groups and getting them to work together.
Today is radically different. Why….read above
Here are just a few of many examples.
I can say that when I have toured or read about some of our great local SC manufacturing companies, it appears that many are already doing many, if not all of these.
BMW
Boeing
Bosch
GE Brilliant Factory (Gas Turbine plant)
Michelin
This presentation really is focusing those who are relatively new to the IIoT.
OK, I promise – this is the last of the super busy slides, but it is a good Use Case of potential IIoT areas commonly used in manufacturing.
I spent the first 15 years in the unpopular world of QA.
We loved data! Deming, Juran, Shewhart all preached data and then Lean and 6 Sigma came along – again all data driven concepts.
To be honest, there is so much here, I am unfamiliar with many of these, but…if we are to be process and data driven, the old ways of data collection, excel spread sheets, SPC charts, and human analysis is limited.
How about we select the areas in which the data affects outcomes and put a sensor and analytics on them?
Another Use Case – Smart Manufacturing.
Wouldn’t it be great to have an IIoT solution that gathers data from your:
Supply chain
Incoming material quality data
Process operating conditions
Sensors & control systems
Equipment & tool health
In-process and final product quality
Customer complaints
Then integrates and aggregates all of this data from the various production lines for each plant up through the Platform tier and to the Enterprise?
Use Case – RFID Track & Trace
Material
Tools
People
Reduces human error
Improves inventory accuracy
Speeds up shipping & receiving
Allows for a Digital Twin to be generated to visualize the process and material
Wireless, battery powered sensors
5+ years of battery power
MySQL DB
900MHz mesh capable radios
Remotely managed sensors
Custom dashboards
Some of our customer Use Cases:
Cold Chain – restaurants – refrigerated trailers (like a Major golf tournament recently held in Augusta??
Pharma – vaccines
Manufacturing –solder flux paste – both while in storage and in the wave solder machine
900 Mhz Edge Devices
Glacier – temp -40+60C +/-.05C
Lightening – temp for use in a lab or liquid (propylene glycol) simulant environment.
Storm – temp & humidity
Tested and approved by R-J (Ray & John)
Tested in salt water at 33 feet
Tested in a pond for one year
Dropped repeatedly from 20 feet
Tested on a 4x4 live rear axle for 9 months
Tested in ambient, refrigerated and freezer applications for ~ 2 years
Remote management of the devices is crucial via the gateway:
Sampling intervals must be user configurable to accommodate customers needs
Alerts also must be user configurable – texts, emails, calls
Increased data transmission rates when alarm or trends are detected
Data must be able to be viewed via the web or mobile device
Sensors and gateway must be able to be upgraded remotely
Sensors can store data up to 30 days in case of power or internet outages
Lightening (on your left) –is specifically designed as a (digital twin) to replace sensors used in propylene glycol simulants refrigerated conditions,
But it also has a very fast response time – if needed
And can be calibrated – if needed
Avatar (on your right) – was designed as a multi asset temperature monitoring digital twin. With one device, you can read the ambient temp and simulate via algorithms other asset temp characteristics instead of monitoring each asset with its own separate sensor.
For example – using Avatar
gray line is the actual ambient temp in a refrigerator over time as measured by our Lightening temp sensor.
Blue line is the temp used the traditional thermometer in a propylene glycol simulant @ 50 ml
Dashed red line was measured using the Hitachi Lightening Avatar derived by our algorithm – same sensor as the ambient line.
I keep coming back to this idea of a Digital Twin – but it is a trend that seems to be gaining traction.
Customers not only want to be able to see the data in a graph and/or export to excel, etc., but they also want a quick visualization of their shop floor and see the real-time data form any where in the world/.
This is a test we ran to see how well mesh networking of sensors worked. In this case we were able to read sensor data that was physically located >1.2M away from our facility by having the date hop via a mesh network which allows for date to use other sensors in the network as a kind of router in case the gateway is not available.
Keep in mind these are all battery powered devices and use 900 Mhz radios to communicate with each other.
They are LOS so trees or hills affect the range. In this case we had a total of 5 hops.
Dashboard
Temp/humidity – color coded for quick understanding of good vs NG
Asset name
Range
Signal level
Date/time of last reading
Now if you click on the graph icon you get..
This…
A graph with the data that can be changed by the customer
Green data – in spec
Red data – out o spec
Trend data – defrost cycle
Trend data – coils need cleaning or compressor is going out
Export function – excel etc. for further analysis
Here are some IIoT groups that we in SC should be aware of and possibly join
IIC
IEEE
Industrie 4.0 – Originated out of Germany – Bosch is a key driver in this initiative – has government backing
Made in China 2025 – don’t overlook this group which is also has government backing
Closer to home
CDAIT
NC RIoT
Center for Mfg Innovation
Next Manufacturing Center
What about IIoT for the rest of us